config.example.toml

# ╔══════════════════════════════════════════════════════════════════════════════╗
# ║                         Codewhale Configuration                               ║
# ║                                                                              ║
# ║  Terminal coding agent for any model — open models first.                ║
# ╚══════════════════════════════════════════════════════════════════════════════╝

# See `docs/CONFIGURATION.md` for how config is loaded (profiles, env overrides, etc.).

# ─────────────────────────────────────────────────────────────────────────────────
# Active provider + DeepSeek defaults
# ─────────────────────────────────────────────────────────────────────────────────
# Choose which provider to use by default. Per-provider credentials live in the
# `[providers.*]` sections near the bottom of
# this file — keeping both stored at once means `/provider deepseek` and
# `/provider nvidia-nim` (or `--provider openai`, `--provider wanjie-ark`,
# `--provider volcengine`, `--provider openrouter`, `--provider xiaomi-mimo`,
# `--provider fireworks`, `--provider siliconflow`, `--provider siliconflow-CN`,
# `/provider arcee`, `/provider moonshot`, `/provider qianfan`, `/provider sglang`, `/provider vllm`,
# `/provider ollama`, `/provider huggingface`, `/provider stepfun`, `/provider openmodel`,
# `/provider opencode-go`, `/provider opencode-zen`, `/provider meta`, `/provider xai`) toggle without having to re-enter keys. Top-level
# `api_key` / `base_url` are
# still read as DeepSeek defaults when `[providers.deepseek]` is absent
# (backward compatibility).
provider = "deepseek" # deepseek | deepseek-cn | deepseek-anthropic | nvidia-nim | openai | atlascloud | wanjie-ark | volcengine | openrouter | orcarouter | xiaomi-mimo | novita | fireworks | siliconflow | siliconflow-CN | arcee | moonshot | zai | stepfun | minimax | sglang | vllm | ollama | huggingface | together | qianfan | openai-codex | anthropic | openmodel | deepinfra | sakana | longcat | opencode-go | opencode-zen | meta | xai | modelstudio-token-plan | modelstudio-coding-plan
api_key = "YOUR_DEEPSEEK_API_KEY" # must be non-empty
base_url = "https://api.deepseek.com/beta"
# provider = "deepseek-cn"                       # legacy alias (official host is still https://api.deepseek.com)
# base_url = "https://api.deepseek.com"         # opt out of DeepSeek beta features
# Optional custom model request headers for OpenAI-compatible gateways.
# Authorization and Content-Type are managed by the client and cannot be overridden here.
# http_headers = { "X-Model-Provider-Id" = "your-model-provider" }

# ─────────────────────────────────────────────────────────────────────────────────
# Default Models
# ─────────────────────────────────────────────────────────────────────────────────
# DeepSeek V4 family:
#   deepseek-v4-pro             — flagship reasoning model on DeepSeek Platform
#   deepseek-v4-flash           — fast, cost-efficient (legacy aliases: deepseek-chat, deepseek-reasoner)
#   deepseek-ai/deepseek-v4-pro   — NVIDIA NIM-hosted Pro model ID
#   deepseek-ai/deepseek-v4-flash — NVIDIA NIM-hosted Flash model ID
#   deepseek/deepseek-v4-pro      — default OpenRouter DeepSeek model ID
#   arcee-ai/trinity-large-thinking — OpenRouter Arcee Trinity Large Thinking
#   xiaomi/mimo-v2.5-pro          — OpenRouter Xiaomi MiMo 2.5 Pro
#   xiaomi/mimo-v2.5              — OpenRouter Xiaomi MiMo 2.5
#   z-ai/glm-5.1                  — OpenRouter Z.AI GLM 5.1
#   z-ai/glm-5.2                  — OpenRouter Z.AI GLM 5.2
#   z-ai/glm-5.3                  — OpenRouter Z.AI GLM 5.3 (live on Z.ai since 2026-08-13;
#                                   metadata inherited from 5.2, unpriced)
#   z-ai/glm-5-turbo              — OpenRouter Z.AI GLM 5 Turbo (scout fast sibling)
#   GLM-5.3                       — default direct Z.AI Coding Plan model (live since 2026-08-13;
#                                   metadata inherited from 5.2, unpriced)
#   GLM-5.2                       — direct Z.AI GLM 5.2 (previous default; explicit selections keep it)
#   GLM-5.1                       — direct Z.AI smaller model
#   GLM-5-Turbo                   — direct Z.AI fast model (scout fast sibling)
#   step-3.7-flash                — default direct StepFun / StepFlash model ID
#   kimi-k3                         — direct Moonshot K3 model ID (1M context)
#   kimi-k2.7-code                  — default direct Moonshot/Kimi K2.7 model ID
#   k3                              — Kimi Code membership K3 API model ID
#   kimi-for-coding                 — Kimi Code membership K2.7 compatibility ID
#   kimi-for-coding-highspeed       — Kimi Code membership high-speed roster ID
#   gpt-4.1                         — default generic OpenAI-compatible model ID
#   deepseek-ai/deepseek-v4-flash   — default AtlasCloud model ID
#   deepseek-reasoner               — default Wanjie Ark model ID
#   mimo-v2.5-pro                   — default Xiaomi MiMo model ID
#   mimo-v2.5-pro-ultraspeed        — Xiaomi MiMo V2.5 Pro UltraSpeed chat model ID
#   mimo-v2.5                       — Xiaomi MiMo V2.5 Omni model ID
#   mimo-v2.5-tts                   — Xiaomi MiMo speech/TTS model ID
#   mimo-v2.5-tts-voicedesign       — Xiaomi MiMo voice-design TTS model ID
#   mimo-v2.5-tts-voiceclone        — Xiaomi MiMo voice-clone TTS model ID
#   accounts/fireworks/models/deepseek-v4-pro — Fireworks AI Pro model ID
#   deepseek-ai/DeepSeek-V4-Pro      — SiliconFlow hosted Pro model ID
#   deepseek-ai/DeepSeek-V4-Flash    — SiliconFlow hosted Flash model ID
#   trinity-large-thinking           — default direct Arcee AI API model ID
#   trinity-large-preview            — direct Arcee AI API model ID
#   deepseek-ai/DeepSeek-V4-Pro      — SGLang self-hosted Pro model ID
#   deepseek-ai/DeepSeek-V4-Flash    — SGLang self-hosted Flash model ID
#   auto                         — auto-select between flash and pro based on task complexity.
#                                  Complex tasks (debugging, refactoring, architecture) → pro;
#                                  simple tasks (lookups, formatting, Q&A) → flash.
default_text_model = "deepseek-v4-pro"

# ─────────────────────────────────────────────────────────────────────────────────
# Thinking Mode (DeepSeek V4 reasoning effort)
# ─────────────────────────────────────────────────────────────────────────────────
# "off"    — disables chain-of-thought (thinking.type = disabled)
# "low"    — compat-maps to "high" server-side
# "medium" — compat-maps to "high" server-side
# "high"   — reasoning_effort = high (DeepSeek default)
# "max"    — reasoning_effort = max (deepest reasoning)
#
# Ctrl+T in the TUI cycles the reasoning tier. The header shows the current
# tier as a ⚡ chip. (Shift+Tab cycles the permission posture — Ask /
# Auto-Review / Full Access — not the reasoning tier.)
reasoning_effort = "max"

# NOTE: `show_thinking`, `thinking_default_expanded`, `thinking_preview_lines`,
# `help_expand_groups`, `pin_last_prompt`, and `cost_currency` live in
# `~/.codewhale/settings.toml`, not here — `Config` has no such fields and
# unknown keys are ignored. See crates/tui/src/settings.rs.
#
# Density (Grok-like compact defaults; turn these up if you want more shown):
#   thinking_preview_lines = 2     # 0 header-only, 10 older dump
#   thinking_default_expanded = false
#   help_expand_groups = false     # true = F1 starts fully expanded
#   pin_last_prompt = true
#   show_tool_details = false

# ─────────────────────────────────────────────────────────────────────────────────
# Startup update check
# ─────────────────────────────────────────────────────────────────────────────────
# The TUI checks for newer Codewhale releases in the background at startup.
# Set check_for_updates = false in managed or air-gapped environments.
# The result is cached in ~/.codewhale/update-check.json, so the network is
# touched at most once per check_interval_hours while the notice still shows
# on every launch. Set 0 to check on every launch.
# Checks are skipped entirely in CI, and when CODEWHALE_NO_UPDATE_CHECK or
# NO_UPDATE_NOTIFIER is set.
# update_uri may point at a GitHub-compatible latest-release JSON endpoint.
[update]
check_for_updates = true
check_interval_hours = 24
# update_uri = "https://internal.mirror.example/codewhale/releases/latest"

# ─────────────────────────────────────────────────────────────────────────────────
# Hotbar slots (#2061 / #2064)
# ─────────────────────────────────────────────────────────────────────────────────
# Optional 1-8 sidebar hotbar bindings. Since #3807 a missing `hotbar` key
# renders NO bar — the Hotbar is hidden until you configure [[hotbar]]
# tables here (or via `/hotbar`). An explicit `hotbar = []` also disables it.
#
# Invalid slots are skipped with a warning, duplicate slots use the last entry,
# and unknown actions are preserved so the UI can show a disabled entry.
# Slash commands can be bound as slash.<name>, for example slash.workflow.
# `/hotbar on` writes the default slots: slash.workflow, slash.goal, slash.auto,
# then Plan/Work/Operate, palette, and sidebar. Commands that require arguments
# pre-fill the composer instead of running incomplete.
#
# [[hotbar]]
# slot = 1
# label = "voice"
# action = "voice.toggle"
#
# [[hotbar]]
# slot = 2
# action = "session.compact"
#
# [[hotbar]]
# slot = 3
# label = "mode"
# action = "slash.mode"

# ─────────────────────────────────────────────────────────────────────────────────
# Paths
# ─────────────────────────────────────────────────────────────────────────────────
# New installs write product state under ~/.codewhale/. Existing ~/.deepseek/
# files are still read as compatibility fallbacks when the .codewhale file is
# absent.
skills_dir = "~/.codewhale/skills"
mcp_config_path = "~/.codewhale/mcp.json"
notes_path = "~/.codewhale/notes.txt"

# Anchors the native memory store. The filename itself is not written: under
# the Native backend (the only backend) the store is re-rooted to
# `<parent-of-this-path>/memory/global/MEMORY.md`. With the default below that
# resolves to `~/.codewhale/memory/global/MEMORY.md` (plus workspace-scoped
# files and a rebuildable SQLite FTS5 index). See docs/MEMORY.md.
memory_path = "~/.codewhale/memory.md"

# instructions = ["./AGENTS.md", "~/.codewhale/global.md"]
#
# Optional list of additional instruction files concatenated into the
# system prompt in declared order (#454). Useful for layering
# repo-specific rules on top of a global preferences file. Each entry
# is expanded so `~` and env vars work; missing files are skipped with
# a tracing warning. Files are capped at 100 KiB per entry.
#
# Project-level config (.codewhale/config.toml in the workspace) replaces
# the user-level array wholesale rather than merging — list `~/global.md`
# inside the project array if you want both. An explicit empty array
# (`instructions = []`) clears the user list for the current repo.

# ─────────────────────────────────────────────────────────────────────────────────
# User memory (#489) — opt-in. When enabled, the TUI loads the native store
# derived from memory_path (see above), injects a bounded recall block into
# the system prompt, intercepts `# foo` in the composer, and registers the
# `remember` / `memory_search` / `memory_get` tools.
# ─────────────────────────────────────────────────────────────────────────────────
[memory]
# enabled = true            # turn the feature on (default: false)
# Override the env-var equivalent: `DEEPSEEK_MEMORY=on`

# Xiaomi MiMo speech/TTS defaults. Also configurable with
# XIAOMI_MIMO_SPEECH_OUTPUT_DIR / MIMO_SPEECH_OUTPUT_DIR.
[speech]
# output_dir = "./speech"

# Native tool catalog controls (#2076). By default only the core tool surface
# is loaded into the model context; less common native tools are discoverable
# through ToolSearch and loaded on first use.
# [tools]
# always_load = ["git_show", "notify"]

# ─────────────────────────────────────────────────────────────────────────────────
# Product telemetry — opt-in, off by default
# ─────────────────────────────────────────────────────────────────────────────────
# Nothing is collected unless BOTH of these are true: `telemetry = true` here,
# and the first-run notice has been answered with "Enable" on this machine. A
# `telemetry = true` written before 0.9.4 is therefore inert — the key existed
# and did nothing for a long time, and setting it was never consent.
#
# Setting it to `false` here is an answer, not just a flag: it deletes the
# random install id, truncates every buffered event, and leaves a tombstone
# that a session already running re-checks before it sends anything. Every
# later run re-reads this key and re-asserts that tombstone, so it stands for
# as long as the `false` does — and nothing outranks it, not `--telemetry true`
# and not `CODEWHALE_TELEMETRY=1`. Turning telemetry back on means writing
# `telemetry = true` here.
#
# The environment variable and the flag are different: they stop the run and
# erase nothing, so a harness that disables telemetry for one command does not
# discard the machine owner's install id and dry-run records.
#
#   codewhale config set telemetry false     # opt out: stops it and erases state
#   CODEWHALE_TELEMETRY=0 codewhale          # kill switch: stops it, erases nothing
#
# What is never collected: prompts, completions, tool arguments, diffs, file
# contents, filenames, paths, git remotes, repo or branch names, memory
# entries, chat history, API keys or tokens (not even a boolean saying one
# exists), model ids, custom provider table names, MCP server names, error or
# panic message bodies, per-event timestamps, keystrokes, clipboard,
# screenshots, or location. The complete schema is `docs/TELEMETRY.md`, and a
# test asserts this file and the serializer agree.
#
# A repo-local `.codewhale/config.toml` can set neither key: someone else's
# repository cannot turn your telemetry on or aim it at a host of their choosing.
# telemetry = false

# Where batches are POSTed. Leaving this unset selects the shipped default,
# the first-party ingest service:
#
#   https://telemetry.codewhale.net/v1/telemetry
#
# That default is only ever consulted for a session that is already enabled —
# it decides where a batch goes, never whether one exists. Nothing is sent
# until `telemetry` is on AND the first-run notice was answered with Enable.
#
# Two overrides, both of which beat the default:
#
#   telemetry_endpoint = "https://collector.internal/v1/batch"  # your own sink
#   telemetry_endpoint = ""                                     # contact nobody
#
# The empty string is the local dry-run sink: batches are serialized exactly as
# a real endpoint would see them, appended to
# `$CODEWHALE_HOME/telemetry/dryrun.jsonl`, and no HTTP client is ever
# constructed. Read that file to see precisely what would have been sent.
# `CODEWHALE_TELEMETRY_ENDPOINT` overrides this file, and setting it to the
# empty string means the same "contact nobody".
#
# `https://` is required; plain `http://` is accepted only for loopback, and no
# environment variable overrides that refusal.
# telemetry_endpoint = "https://telemetry.codewhale.net/v1/telemetry"

# ─────────────────────────────────────────────────────────────────────────────────
# Security
# ─────────────────────────────────────────────────────────────────────────────────
allow_shell = true
approval_policy = "on-request" # on-request | untrusted | never
sandbox_mode = "workspace-write" # read-only | workspace-write | danger-full-access | external-sandbox

# Whether a workspace-write sandbox also lets shell commands reach the
# network. Default false: being allowed to edit this repository is not a
# reason to be allowed to open outbound connections, so `curl`, package
# installs, and `git fetch` are denied by the OS sandbox unless you opt in.
# When a command is denied, Codewhale offers an elevation prompt that grants
# network for that call only; set this to `true` to grant it for the whole
# session instead. `danger-full-access` and `yolo` are unsandboxed and
# unaffected by this key. Note that on platforms with no OS sandbox backend
# (default Linux without bubblewrap, and Windows) nothing is enforced either
# way -- `/status` and `doctor` both say so.
# sandbox_network_access = false

# Which other agents' instruction files to import as project instructions.
# Empty by default. Codewhale reads AGENTS.md (the cross-agent standard) and
# its own .codewhale/instructions.md without being asked; a CLAUDE.md,
# .cursorrules, or .github/copilot-instructions.md written as law for a
# different tool is not treated as law here until you say so. Codewhale's own
# files always outrank anything imported.
# Accepts: "claude", "cursor", "cline", "windsurf", "gemini", "copilot",
# "muse", or "all". Env: CODEWHALE_PROJECT_INSTRUCTION_IMPORTS (comma-separated).
# project_instruction_imports = ["claude"]
#
# Everything that reaches the model as standing project instruction authority —
# the repository-root -> workspace AGENTS.md chain, the global fallback layer,
# .codewhale/rules/*.md, and any imported foreign files — shares one 48 KiB
# aggregate budget. Instructions claim it first and are trimmed from the
# broadest scope inward, so the nearest-scope file is the last thing dropped.
# prompt_suggestion = true  # opt-in: show ghost-text follow-up question in composer after each turn

# Optional tab/window title shown as `[title] …` in front of the terminal
# window title (the `Codewhale` / `reasoning…` / `using tool…` / `done`
# states). Multi-window setups can give each workspace its own `--config`
# file (or profile) so alt-tabbed sessions are identifiable at a glance.
# The `/title` command overrides this per session; `/config title … --save`
# persists a new default here. Run `/title off` to drop a session override.
# title = "workspace-x"

# Typed permission rules live in a sibling `permissions.toml` file, not in
# config.toml. Each `[[rules]]` entry accepts `tool`, optional `command`
# or `path`, optional absolute `workspace`, optional `command_exact = true`,
# and an `action` field: `"deny"`, `"ask"` (default), or `"allow"`.
# Deny always wins over ask, which wins over allow. The active user's sibling
# file is the only rule source today; project config overlays do not load a
# project-local permissions.toml. `workspace` is a repo scope, not a source.
# Globs and broad directory rules remain future work.
#
# In supported approval cards, press `S` to allow once and save an exact ask
# rule. Eligible safe calls also offer `P` / "Always allow this exact rule in
# this repo", which saves an exact `allow` rule scoped to the current absolute
# workspace. Dangerous/critical calls and repo-law prompts cannot save allow
# grants. The approval UI still does not save deny rules:
#   exec_shell  -> exact approved command string
#   write_file  -> exact workspace-relative target path
#   edit_file   -> exact workspace-relative target path
#   apply_patch -> one exact workspace-relative path per validated touched file
# `read_file` rules can be written manually, but the approval UI does not save
# them.
#
# `/permissions list` shows the active source, effective matcher, repo/global
# scope, and whether each rule applies in the current workspace.
# `/permissions remove <number>` previews a deletion and prints a confirmation
# command bound to the current file snapshot. If the file changes first, the
# confirmation fails safely. Removal preserves unrelated comments/formatting,
# uses the same lock as approval-card appends, and atomically replaces the file.
# `/config ask-rules` remains a compatibility entry to the same list.
#
# Example ~/.codewhale/permissions.toml:
#
# [[rules]]
# tool = "exec_shell"
# command = "cargo test"
# action = "ask"
#
# # Block dangerous commands
# [[rules]]
# tool = "exec_shell"
# command = "sed"
# action = "deny"
#
# [[rules]]
# tool = "exec_shell"
# command = "awk"
# action = "deny"
#
# # Allow trusted commands without asking
# [[rules]]
# tool = "exec_shell"
# command = "git status"
# command_exact = true
# workspace = "/absolute/path/to/project"
# action = "allow"
#
# # Path-based deny
# [[rules]]
# tool = "write_file"
# path = "src/main.rs"
# action = "deny"
#
# [[rules]]
# tool = "edit_file"
# path = "src/lib.rs"
# action = "ask"
#
# [[rules]]
# tool = "apply_patch"
# path = "src/patch-target.rs"
#
# [[rules]]
# tool = "read_file"
# path = "secrets/api_key.txt"
# action = "deny"
# ─────────────────────────────────────────────────────────────────────────────────
# External Sandbox Backend (pluggable remote execution)
# ─────────────────────────────────────────────────────────────────────────────────
# When sandbox_backend is set to "opensandbox", all exec_shell calls are
# routed through an external OpenSandbox-compatible HTTP API instead of
# spawning a local process. The backend sends `POST {sandbox_url}/v1/sandbox/run`
# with `{"cmd": "...", "env": {...}}` and expects
# `{"stdout": "...", "stderr": "...", "exit_code": 0}`.
#
# sandbox_backend = "none"          # "none" (default) or "opensandbox"
# sandbox_url = "http://localhost:8080"  # OpenSandbox-compatible API base URL
# sandbox_api_key = "YOUR_API_KEY"  # Optional Bearer token sent with requests
#
# Env-var overrides:
#   DEEPSEEK_SANDBOX_BACKEND   → sandbox_backend
#   DEEPSEEK_SANDBOX_URL       → sandbox_url
#   DEEPSEEK_SANDBOX_API_KEY   → sandbox_api_key
#
# Example OpenSandbox setup:
#
#   sandbox_backend = "opensandbox"
#   sandbox_url = "http://localhost:8080"
#   sandbox_api_key = "sk-opensandbox-secret"
#
# The backend uses a 30-second HTTP timeout. Background, interactive, and
# TTY modes are not supported with external backends — all commands run
# synchronously via HTTP.
# ─────────────────────────────────────────────────────────────────────────────────
# Bubblewrap (Linux only, additional filesystem isolation)
# ─────────────────────────────────────────────────────────────────────────────────
# When set to true and `/usr/bin/bwrap` is present, exec_shell commands are
# routed through bubblewrap instead of relying solely on Landlock. Bubblewrap
# creates a read-only view of the root filesystem with write access limited to
# the working directory. Install separately:
#
#   Ubuntu/Debian:  apt install bubblewrap
#   Fedora:         dnf install bubblewrap
#   Arch:           pacman -S bubblewrap
#
# prefer_bwrap = false  # default — use Landlock only
#
# Env override: CODEWHALE_PREFER_BWRAP=true
# Legacy alias (deprecated until 0.10.0): DEEPSEEK_PREFER_BWRAP=true
#
# With prefer_bwrap = true, the sandbox gets a private /dev and /proc plus a
# writable isolated /tmp by default, so toolchains work without widening the
# filesystem policy (#5410). Two optional escape hatches:
#
# bwrap_ro_roots = []      # extra host paths bind-mounted read-only, e.g.
#                          #   ["/usr/lib", "/usr/lib64"] for system-library
#                          #   linking when the root bind is narrowed
# bwrap_dev_roots = []    # host device nodes bind-mounted read-write, e.g.
#                          #   ["/dev/null"] for redirection against the host
#                          #   node — character/block devices only, never
#                          #   directories, so this cannot widen file writes

# auto_allow entries match by command prefix, not raw string.
# See command_safety.rs for the prefix dictionary.
#
# Examples:
#   auto_allow = ["git status"]   # auto-approves: git status, git status -s, git status --porcelain
#                                 # does NOT auto-approve: git push, git checkout
#   auto_allow = ["cargo check", "npm run"]
#
# auto_allow = []
max_subagents = 10 # optional (default 64, clamped to 1-128)

# Optional sub-agent tuning. max_concurrent overrides top-level max_subagents.
# [subagents]
# max_concurrent = 10
# api_timeout_secs = 600 # per-step API timeout, clamped to 1..=3600
#
# How many levels of nested sub-agents the `agent` tool may spawn:
#   max_depth = 0   # opt out completely — the agent never spawns sub-agents
#   max_depth = 1   # the agent may spawn sub-agents, but those may not spawn more
#   max_depth = 2   # one more level of nesting, etc.
# Unset defaults to 3; any value is clamped to the hard ceiling (8). The depth
# limit is enforced in code, not requested of the model — a sub-agent past the
# limit cannot be spawned regardless of what the model decides.
# max_depth = 3

# Optional managed policy paths (defaults to /etc/deepseek/*.toml on unix):
# managed_config_path = "/etc/deepseek/managed_config.toml"
# requirements_path = "/etc/deepseek/requirements.toml"

# ─────────────────────────────────────────────────────────────────────────────────
# Per-provider credentials (peer providers — NIM is first-class, not a flag)
# ─────────────────────────────────────────────────────────────────────────────────
# Providers can be stored at once; `provider = "..."` (top of file) or
# `/provider deepseek` / `/provider nvidia-nim` / `--provider openai` /
# `--provider wanjie-ark` / `/provider volcengine` / `/provider fireworks` /
# `--provider siliconflow` / `/provider arcee` / `/provider moonshot`
# switches between them without having to re-enter keys. Env vars override anything set here:
#   DeepSeek: DEEPSEEK_API_KEY, DEEPSEEK_BASE_URL, DEEPSEEK_MODEL
#   DeepSeek Anthropic-compatible: DEEPSEEK_API_KEY, DEEPSEEK_ANTHROPIC_BASE_URL
#   NIM:      NVIDIA_API_KEY (or NVIDIA_NIM_API_KEY), NIM_BASE_URL
#             (or NVIDIA_NIM_BASE_URL / NVIDIA_BASE_URL), NVIDIA_NIM_MODEL
#   OpenAI-compatible: OPENAI_API_KEY, OPENAI_BASE_URL, OPENAI_MODEL
#   Wanjie Ark: WANJIE_ARK_API_KEY (or WANJIE_API_KEY), WANJIE_ARK_BASE_URL, WANJIE_ARK_MODEL
#   Volcengine Ark: VOLCENGINE_API_KEY (or VOLCENGINE_ARK_API_KEY / ARK_API_KEY), VOLCENGINE_BASE_URL, VOLCENGINE_MODEL
#   OpenRouter: OPENROUTER_API_KEY, OPENROUTER_BASE_URL, OPENROUTER_MODEL
#   Xiaomi MiMo: XIAOMI_MIMO_API_KEY (or XIAOMI_API_KEY / MIMO_API_KEY), XIAOMI_MIMO_BASE_URL, XIAOMI_MIMO_MODEL
#                Token Plan: XIAOMI_MIMO_TOKEN_PLAN_API_KEY (or MIMO_TOKEN_PLAN_API_KEY), XIAOMI_MIMO_MODE/MIMO_MODE
#   Novita:     NOVITA_API_KEY, NOVITA_BASE_URL, NOVITA_MODEL
#   Fireworks:  FIREWORKS_API_KEY, FIREWORKS_BASE_URL
#   SiliconFlow: SILICONFLOW_API_KEY, SILICONFLOW_BASE_URL, SILICONFLOW_MODEL
#   Arcee:      ARCEE_API_KEY, ARCEE_BASE_URL, ARCEE_MODEL
#   Moonshot/Kimi: MOONSHOT_API_KEY (or KIMI_API_KEY), MOONSHOT_BASE_URL, MOONSHOT_MODEL
#   SGLang:    SGLANG_BASE_URL, SGLANG_MODEL, optional SGLANG_API_KEY
#   vLLM:      VLLM_BASE_URL, VLLM_MODEL, optional VLLM_API_KEY
#   Ollama:    OLLAMA_BASE_URL, OLLAMA_MODEL, optional OLLAMA_API_KEY
#   Hugging Face: HUGGINGFACE_API_KEY (or HF_TOKEN), HUGGINGFACE_BASE_URL (or HF_BASE_URL),
#                 HUGGINGFACE_MODEL (or HF_MODEL)
#   Meta Model API: META_MODEL_API_KEY (or MODEL_API_KEY), META_MODEL_API_BASE_URL
#                   (or MODEL_API_BASE_URL), META_MODEL_API_MODEL (or MODEL_API_MODEL)
#
# Custom DeepSeek-compatible APIs usually do not need a new provider table:
# set `provider = "deepseek"` and override [providers.deepseek].base_url/model.
# For generic OpenAI-compatible gateways, use `provider = "openai"` and the
# [providers.openai] table below. Keep provider/api_key/base_url in user config
# or environment variables; project overlays are not allowed to set them.
#
# Provider is the route/account/endpoint; model is the ID on that route.
# Common DeepSeek routes:
#   provider = "deepseek"     model = "deepseek-v4-pro"
#   provider = "nvidia-nim"   model = "deepseek-ai/deepseek-v4-pro"
#   provider = "openrouter"   model = "deepseek/deepseek-v4-pro"
#   provider = "fireworks"    model = "accounts/fireworks/models/deepseek-v4-pro"
#   provider = "siliconflow"  model = "deepseek-ai/DeepSeek-V4-Pro"

# DeepSeek Platform (https://platform.deepseek.com)
[providers.deepseek]
# api_key = "YOUR_DEEPSEEK_API_KEY"
# base_url = "https://api.deepseek.com/beta"
# model = "deepseek-v4-pro"
# Custom DeepSeek-compatible example:
# base_url = "https://your-provider.example/v1"
# model = "deepseek-ai/DeepSeek-V4-Pro"
# http_headers = { "X-Model-Provider-Id" = "your-model-provider" } # optional custom request headers
# path_suffix = "/chat/completions" # override the API path; skips /v1 versioning when set
# reasoning_stream_style = "inline_tags" # route <think>...</think> content into Thinking cells

# DeepSeek Anthropic-compatible Messages route (opt-in)
# [providers.deepseek_anthropic]
# api_key = "YOUR_DEEPSEEK_API_KEY"
# base_url = "https://api.deepseek.com/anthropic"
# model = "deepseek-v4-pro"
# [providers.deepseek.auth] # provider-scoped auth source metadata; command execution lands in a follow-up slice
# source = "command"
# command = ["secret-tool", "lookup", "service", "codewhale-deepseek"]
# timeout_ms = 2000
# insecure_skip_tls_verify = true # last resort for private gateways; prefer SSL_CERT_FILE

# NVIDIA NIM-hosted DeepSeek V4 (https://build.nvidia.com)
[providers.nvidia_nim]
# api_key = "YOUR_NVIDIA_API_KEY"
# base_url = "https://integrate.api.nvidia.com/v1"
# model = "deepseek-ai/deepseek-v4-pro"     # or deepseek-ai/deepseek-v4-flash

# Generic OpenAI-compatible endpoint. Use the built-in `openai` provider for
# third-party gateways; do not invent a custom provider name. For non-local
# http:// gateways, launch with DEEPSEEK_ALLOW_INSECURE_HTTP=1 only on a
# trusted network.
[providers.openai]
# api_key = "YOUR_OPENAI_COMPATIBLE_API_KEY"
# base_url = "https://api.openai.com/v1"
# model = "gpt-4.1"
# Gateway example:
# base_url = "https://gateway.example/v1"
# model = "your-deepseek-compatible-model"
# Alibaba Bailian / Model Studio DashScope OpenAI-compatible example:
# base_url = "https://dashscope-intl.aliyuncs.com/compatible-mode/v1"
# model = "qwen-plus"
# context_window = 1000000 # set the gateway/model's real total context window
# insecure_skip_tls_verify = true # last resort for private gateways; prefer SSL_CERT_FILE

# AtlasCloud OpenAI-compatible endpoint (https://www.atlascloud.ai/docs/models/llm)
[providers.atlascloud]
# api_key = "YOUR_ATLASCLOUD_API_KEY"
# base_url = "https://api.atlascloud.ai/v1"
# model = "deepseek-ai/deepseek-v4-flash"

# Wanjie Ark / 万界方舟 OpenAI-compatible endpoint
[providers.wanjie_ark]
# api_key = "YOUR_WANJIE_API_KEY"
# base_url = "https://maas-openapi.wanjiedata.com/api/v1"
# model = "deepseek-reasoner"                # or the exact model ID enabled on your Wanjie account

# Volcengine / Volcano Engine Ark Coding API
[providers.volcengine]
# api_key = "YOUR_VOLCENGINE_API_KEY"
# base_url = "https://ark.cn-beijing.volces.com/api/coding/v3"
# model = "DeepSeek-V4-Pro"                  # or DeepSeek-V4-Flash

# OpenRouter — multi-provider gateway (https://openrouter.ai)
[providers.openrouter]
# api_key = "YOUR_OPENROUTER_API_KEY"
# base_url = "https://openrouter.ai/api/v1"
# model = "deepseek/deepseek-v4-pro"
# OpenRouter-compatible gateways can reuse this provider so reasoning/cache
# parsing stays on the OpenRouter-compatible path instead of generic OpenAI:
# base_url = "https://openrouter-compatible.example/v1"
# model = "deepseek/deepseek-v4-pro"
# Recent large model IDs also accepted here include arcee-ai/trinity-large-thinking,
# minimax/minimax-m3, minimax/minimax-m2.7, xiaomi/mimo-v2.5-pro, qwen/qwen3.6-flash,
# qwen/qwen3.6-35b-a3b, qwen/qwen3.6-max-preview, qwen/qwen3.6-27b, qwen/qwen3.6-plus,
# qwen/qwen3.7-max, google/gemma-4-31b-it, z-ai/glm-5.1, z-ai/glm-5.2,
# moonshotai/kimi-k2.6,
# nvidia/nemotron-3-nano-omni-30b-a3b-reasoning:free, and nvidia/nemotron-3-ultra.

# OrcaRouter — OpenAI-compatible aggregation gateway (https://www.orcarouter.ai)
[providers.orcarouter]
# api_key = "YOUR_ORCAROUTER_API_KEY"
# base_url = "https://api.orcarouter.ai/v1"
# model = "deepseek/deepseek-v4-pro"
# Namespaced wire models pass through verbatim (deepseek/deepseek-v4-pro,
# deepseek/deepseek-v4-flash); OrcaRouter's own auto-routing model is
# selectable as "orcarouter/auto".

# Xiaomi MiMo OpenAI-compatible endpoint (https://platform.xiaomimimo.com)
[providers.xiaomi_mimo]
# api_key = "YOUR_XIAOMI_KEY"
# base_url = "https://token-plan-sgp.xiaomimimo.com/v1"  # Token Plan / tp- keys
# # base_url = "https://token-plan-ams.xiaomimimo.com/v1"  # Token Plan Europe / Amsterdam
# # base_url = "https://api.xiaomimimo.com/v1"           # Pay-as-you-go / sk- keys
# model = "mimo-v2.5-pro"              # chat/reasoning
# Chat model IDs: mimo-v2.5-pro, mimo-v2.5-pro-ultraspeed, mimo-v2.5
# Token Plan subscriptions use separate tp-* API keys plus api-key auth.
# mode = "token-plan-sgp"              # default Token Plan endpoint
# mode = "token-plan-cn"               # China cluster
# mode = "token-plan-ams"              # Europe cluster
# mode = "pay-as-you-go"               # standard API / sk- keys
# TTS aliases are also accepted by `codewhale speech`: tts, voice-design, voice-clone
# TTS model IDs: mimo-v2.5-tts, mimo-v2.5-tts-voicedesign, mimo-v2.5-tts-voiceclone, mimo-v2-tts

# Novita AI-hosted inference (https://novita.ai)
[providers.novita]
# api_key = "YOUR_NOVITA_API_KEY"
# base_url = "https://api.novita.ai/openai/v1"
# model = "deepseek/deepseek-v4-pro"         # or deepseek/deepseek-v4-flash

# Fireworks AI-hosted DeepSeek V4 (https://fireworks.ai)
[providers.fireworks]
# api_key = "YOUR_FIREWORKS_API_KEY"
# base_url = "https://api.fireworks.ai/inference/v1"
# model = "accounts/fireworks/models/deepseek-v4-pro"

# SiliconFlow-hosted DeepSeek V4 (https://siliconflow.com)
[providers.siliconflow]
# api_key = "YOUR_SILICONFLOW_API_KEY"
# base_url = "https://api.siliconflow.com/v1"
# model = "deepseek-ai/DeepSeek-V4-Pro"     # or deepseek-ai/DeepSeek-V4-Flash

# SiliconFlow China-hosted DeepSeek V4 (https://siliconflow.cn)
# Falls back to [providers.siliconflow] for api_key / base_url / model when unset.
[providers.siliconflow-CN]
# api_key = "YOUR_SILICONFLOW_API_KEY"
# base_url = "https://api.siliconflow.cn/v1"
# model = "deepseek-ai/DeepSeek-V4-Pro"

# Arcee AI direct OpenAI-compatible endpoint (https://docs.arcee.ai)
[providers.arcee]
# api_key = "YOUR_ARCEE_API_KEY"
# base_url = "https://api.arcee.ai/api/v1"
# model = "trinity-large-thinking"          # or trinity-large-preview

# Moonshot/Kimi OpenAI-compatible endpoint (https://platform.kimi.ai)
[providers.moonshot]
# api_key = "YOUR_MOONSHOT_API_KEY"           # or KIMI_API_KEY
# base_url = "https://api.moonshot.ai/v1"      # or KIMI_BASE_URL
# model = "kimi-k3"                         # direct Moonshot K3 wire ID
# Direct K3 is always-thinking: off -> low, medium -> high, and max remains max.
# The exact route sends top-level reasoning_effort, max_completion_tokens, and
# omits temperature/top_p per https://platform.kimi.ai/docs/guide/kimi-k3-quickstart.
# Kimi Code membership path (key: https://www.kimi.com/code/console):
# api_key = "YOUR_KIMI_CODE_API_KEY"
# base_url = "https://api.kimi.com/coding/v1"
# model = "k3"                              # Kimi Code K3 wire ID
# K3 membership off -> enabled/low; dispatched auto selects a concrete tier.
# Only an omitted reasoning setting leaves the provider default in control.
# Moderato plans are capped at 262144; Allegretto and above unlock up to 1048576.
# context_window = 262144                    # manually cap k3 to the Moderato/256K window
# context_window = 1048576                   # Allegretto+ only; do not claim an unavailable entitlement
# Alternatively use model = "k3-256k" with context_window = 262144 for the fixed 256K route.
# Omit context_window to keep Codewhale's safe 262144-token bare-k3 baseline.
# `k3[1m]` is a Claude Code-only convention, not an API model ID; Codewhale rejects it.
# Kimi Code K2.7 remains available to all members as model = "kimi-for-coding".
# Kimi OAuth is not supported. Legacy auth_mode = "kimi_oauth" fails closed
# to the API-key guidance above without probing Kimi CLI credential files.

# Z.AI GLM Coding Plan endpoint (https://docs.z.ai)
[providers.zai]
# api_key = "YOUR_ZAI_API_KEY"                 # or Z_AI_API_KEY
# base_url = "https://api.z.ai/api/coding/paas/v4"
# # General API endpoint, if you are not using the Coding Plan:
# # base_url = "https://api.z.ai/api/paas/v4"
# model = "GLM-5.3"                             # default; GLM-5.2 is the previous default, GLM-5.1 the smaller model, GLM-5-Turbo the fast sub-agent sibling
# # GLM-5.3 is live on the Z.ai Coding Plan (2026-08-13). Its catalog metadata
# # (limits, reasoning options) is inherited from GLM-5.2 until Z.ai publishes
# # distinct 5.3 numbers, and it carries no price. An explicit model = "GLM-5.2"
# # keeps sending GLM-5.2; only the default moved. Accounts not provisioned for
# # 5.3 can still see a 429 with entitlement code 1311.

# StepFun / StepFlash direct OpenAI-compatible endpoint (https://platform.stepfun.ai)
[providers.stepfun]
# api_key = "YOUR_STEPFUN_API_KEY"               # or STEP_API_KEY
# base_url = "https://api.stepfun.ai/v1"          # or STEP_BASE_URL
# # Coding Plan endpoint:
# # base_url = "https://api.stepfun.ai/step_plan/v1"
# model = "step-3.7-flash"                       # or STEPFUN_MODEL / STEP_MODEL

# MiniMax direct OpenAI-compatible endpoint (https://platform.minimax.io)
[providers.minimax]
# api_key = "YOUR_MINIMAX_API_KEY"
# base_url = "https://api.minimax.io/v1"
# model = "MiniMax-M3"                          # or MiniMax-M2.7, MiniMax-M2.7-highspeed
# # MiniMax also publishes Anthropic-compatible endpoints:
# # global https://api.minimax.io/anthropic, China https://api.minimaxi.com/anthropic.

# Self-hosted SGLang OpenAI-compatible server
[providers.sglang]
# api_key = "OPTIONAL_SGLANG_TOKEN"
# base_url = "http://localhost:30000/v1"
# model = "deepseek-ai/DeepSeek-V4-Pro"     # or deepseek-ai/DeepSeek-V4-Flash

# Self-hosted vLLM OpenAI-compatible server
[providers.vllm]
# api_key = "OPTIONAL_VLLM_TOKEN"
# base_url = "http://localhost:8000/v1"
# model = "deepseek-ai/DeepSeek-V4-Pro"     # or deepseek-ai/DeepSeek-V4-Flash

# Self-hosted Ollama OpenAI-compatible server
[providers.ollama]
# api_key = "OPTIONAL_OLLAMA_TOKEN"
# base_url = "http://localhost:11434/v1"
# model = "deepseek-v4-flash"                # or any local Ollama tag

# Hugging Face Inference Providers (https://huggingface.co/docs/api-inference)
# Provider aliases: huggingface, hugging-face, hugging_face, hf
# Env var aliases: HUGGINGFACE_API_KEY / HF_TOKEN, HUGGINGFACE_BASE_URL / HF_BASE_URL,
#                  HUGGINGFACE_MODEL / HF_MODEL
[providers.huggingface]
# api_key = "YOUR_HF_TOKEN"
# base_url = "https://router.huggingface.co/v1"
# model = "deepseek-ai/DeepSeek-V4-Pro"     # or deepseek-ai/DeepSeek-V4-Flash

# DeepInfra — AI inference cloud (https://deepinfra.com)
[providers.deepinfra]
# api_key = "YOUR_DEEPINFRA_TOKEN"
# base_url = "https://api.deepinfra.com/v1/openai"
# model = "deepseek-ai/DeepSeek-V4-Pro"     # or deepseek-ai/DeepSeek-V4-Flash

# ─────────────────────────────────────────────────────────────────────────────────
# Sakana AI Fugu Provider (https://api.sakana.ai)
# Provider aliases: sakana, sakana-ai, sakana_ai, fugu
# Env var aliases: FUGU_API_KEY, SAKANA_API_KEY
[providers.sakana]
# api_key = "YOUR_FUGU_API_KEY"
# base_url = "https://api.sakana.ai/v1"
# model = "fugu"                            # or fugu-ultra-20260615

# Meituan LongCat Provider (https://longcat.chat/platform)
# OpenAI-compatible curated gateway for Meituan's LongCat models.
# Provider aliases: longcat, long-cat, meituan-longcat, meituan
# Env var aliases: LONGCAT_API_KEY
[providers.longcat]
# api_key = "YOUR_LONGCAT_API_KEY"
# base_url = "https://api.longcat.chat/openai/v1"
# model = "LongCat-2.0"

# OpenCode Go (https://opencode.ai/docs/go/)
# Subscription-backed OpenAI-compatible Chat Completions route.
# Env vars: OPENCODE_GO_API_KEY, OPENCODE_GO_BASE_URL, OPENCODE_GO_MODEL
# Chat Completions models: deepseek-v4-pro, grok-4.5, glm-5.2, glm-5.1,
# kimi-k3, kimi-k2.7-code, kimi-k2.6, deepseek-v4-flash, mimo-v2.5,
# mimo-v2.5-pro.
# Models documented only on OpenCode Go's Anthropic `/messages` endpoint are
# intentionally not advertised by this provider yet.
[providers.opencode_go]
# api_key = "YOUR_OPENCODE_GO_API_KEY"
# base_url = "https://opencode.ai/zen/go/v1"
# model = "deepseek-v4-pro"

# OpenCode Zen (https://opencode.ai/docs/zen/)
# Model-aware gateway: GPT models use Responses, Claude/Qwen use Anthropic
# Messages, and DeepSeek/MiniMax/GLM/Kimi/Grok/free models use Chat Completions.
# Gemini uses a Google-specific protocol that Codewhale does not implement and
# therefore fails closed instead of being sent with the wrong request shape.
# Env vars: OPENCODE_ZEN_API_KEY (preferred), OPENCODE_API_KEY,
# OPENCODE_ZEN_BASE_URL, OPENCODE_ZEN_MODEL
[providers.opencode_zen]
# api_key = "YOUR_OPENCODE_ZEN_API_KEY"
# base_url = "https://opencode.ai/zen/v1"
# model = "gpt-5.5"                         # Responses default
# model = "claude-sonnet-4-6"               # Anthropic Messages example
# model = "deepseek-v4-pro"                 # Chat Completions example

# Meta Model API / Muse Spark (https://developer.meta.com/ai/)
# OpenAI-compatible Chat Completions route.
# Provider aliases: meta, meta-ai, meta-model-api, muse, muse-spark
# Env var aliases: META_MODEL_API_KEY / MODEL_API_KEY,
# META_MODEL_API_BASE_URL / MODEL_API_BASE_URL,
# META_MODEL_API_MODEL / MODEL_API_MODEL
[providers.meta]
# api_key = "YOUR_META_MODEL_API_KEY"
# base_url = "https://api.meta.ai/v1"
# model = "muse-spark-1.1"

# xAI / Grok Provider (https://console.x.ai/)
# OpenAI-compatible Chat Completions route.
# Provider aliases: xai, x-ai, x_ai, grok
# Env var aliases: XAI_API_KEY, XAI_BASE_URL, XAI_MODEL
#
# Auth modes:
#   api_key (default) — console.x.ai pay-per-use key via api_key / XAI_API_KEY / keyring
#   oauth             — `codewhale auth xai-device` uses Codewhale-owned storage.
#                       Reading an existing Grok CLI file requires explicit
#                       `codewhale auth external-consent --provider xai --mode read-only`.
[providers.xai]
# api_key = "YOUR_XAI_API_KEY"
# auth_mode = "oauth"                      # or "device_code" / "grok_cli"
# base_url = "https://api.x.ai/v1"
# model = "grok-4.6"                       # or grok-4.5, grok-4.3, grok-build

# Mistral AI — la Plateforme (https://console.mistral.ai/)
# OpenAI-compatible Chat Completions route.
# Provider aliases: mistral, mistral-ai, mistralai, la-plateforme
# Env var aliases: MISTRAL_API_KEY, MISTRAL_BASE_URL, MISTRAL_MODEL
[providers.mistral]
# api_key = "YOUR_MISTRAL_API_KEY"
# base_url = "https://api.mistral.ai/v1"
# model = "mistral-code-latest"            # or mistral-medium-latest, mistral-small-latest, mistral-large-latest

# ─────────────────────────────────────────────────────────────────────────────────
# Alibaba Cloud Model Studio — Token Plan
# (https://bailian.console.aliyun.com/)
#
# Token Plan Personal and Team share the same AP-Southeast (Singapore) endpoint.
# Available text/coding models: qwen3.8-max, qwen3.8-max-preview, qwen3.7-plus,
# qwen3.7-max, qwen3.6-flash, deepseek-v4-pro, deepseek-v4-flash-0731, glm-5.2
#
# Provider aliases: modelstudio-token-plan, modelstudio_token_plan,
#                   alibaba-token-plan, dashscope-token-plan
# Env var aliases: MODELSTUDIO_API_KEY (preferred), DASHSCOPE_API_KEY,
#                  MODELSTUDIO_TOKEN_PLAN_BASE_URL, MODELSTUDIO_TOKEN_PLAN_MODEL
[providers.modelstudio_token_plan]
# api_key = "YOUR_MODELSTUDIO_API_KEY"
# base_url = "https://token-plan.ap-southeast-1.maas.aliyuncs.com/compatible-mode/v1"
# model = "qwen3.8-max"
# # Anthropic-compatible dialect (same key, /apps/anthropic path):
# # provider = "modelstudio-token-plan-anthropic"
# # base_url = "https://token-plan.ap-southeast-1.maas.aliyuncs.com/apps/anthropic"

# ─────────────────────────────────────────────────────────────────────────────────
# Alibaba Cloud Model Studio — Coding Plan
# (https://bailian.console.aliyun.com/)
#
# Coding Plan uses a separate international endpoint (coding-intl.dashscope).
# Same model catalog as the Token Plan.
#
# Provider aliases: modelstudio-coding-plan, modelstudio_coding_plan,
#                   alibaba-coding-plan, dashscope-coding-plan
# Env var aliases: MODELSTUDIO_API_KEY (preferred), DASHSCOPE_API_KEY,
#                  MODELSTUDIO_CODING_PLAN_BASE_URL, MODELSTUDIO_CODING_PLAN_MODEL
[providers.modelstudio_coding_plan]
# api_key = "YOUR_MODELSTUDIO_API_KEY"
# base_url = "https://coding-intl.dashscope.aliyuncs.com/v1"
# model = "qwen3.8-max"
# # Anthropic-compatible dialect (same key, /apps/anthropic path):
# # provider = "modelstudio-coding-plan-anthropic"
# # base_url = "https://coding-intl.dashscope.aliyuncs.com/apps/anthropic"

# ─────────────────────────────────────────────────────────────────────────────────
# Together AI Provider (https://www.together.ai/)
# Env var aliases: TOGETHER_API_KEY, TOGETHER_BASE_URL, TOGETHER_MODEL
[providers.together]
# api_key = "YOUR_TOGETHER_API_KEY"
# base_url = "https://api.together.xyz/v1"
# model = "deepseek-ai/DeepSeek-V4-Pro"     # or deepseek-ai/DeepSeek-V4-Flash

# ─────────────────────────────────────────────────────────────────────────────────
# Baidu Qianfan Provider (https://intl.cloud.baidu.com/product/qianfan.html)
# Provider aliases: qianfan, baidu-qianfan, baidu_qianfan, baidu
# Env var aliases: QIANFAN_API_KEY / BAIDU_QIANFAN_API_KEY,
#                  QIANFAN_BASE_URL / BAIDU_QIANFAN_BASE_URL,
#                  QIANFAN_MODEL / BAIDU_QIANFAN_MODEL
[providers.qianfan]
# api_key = "YOUR_QIANFAN_API_KEY"
# base_url = "https://api.baiduqianfan.ai/v1"
# model = "ernie-4.0-turbo-8k"              # or your Qianfan service/model id

# ─────────────────────────────────────────────────────────────────────────────────
# OpenAI Codex (ChatGPT) Provider — EXPERIMENTAL
# Run `codex login`, then explicitly grant read-only access to that exact file:
#   codewhale auth external-consent --provider openai-codex --mode read-only
# Codewhale never refreshes or rewrites the Codex CLI file. No API key is
# stored here. Talks to the OpenAI Responses API at /codex/responses.
# Env var aliases: OPENAI_CODEX_ACCESS_TOKEN / CODEX_ACCESS_TOKEN (token override),
#   OPENAI_CODEX_BASE_URL / CODEX_BASE_URL, OPENAI_CODEX_MODEL / CODEX_MODEL,
#   OPENAI_CODEX_ACCOUNT_ID / CODEX_ACCOUNT_ID, OPENAI_CODEX_AUTH_FILE, CODEX_HOME
[providers.openai_codex]
# base_url = "https://chatgpt.com/backend-api"
# model = "gpt-5.5"
# The CLI writes this table after informed consent; do not copy it between
# providers or machines. Absence means disabled.
# [providers.openai_codex.external_credentials]
# access = "read_only"
# provider = "openai-codex"
# source = "codex_cli"
# path = "/absolute/path/to/.codex/auth.json"
# consent_version = 1

# ─────────────────────────────────────────────────────────────────────────────────
# Anthropic Provider (native Messages API)
# Talks to https://api.anthropic.com/v1/messages with x-api-key auth — not an
# OpenAI-compatible route. Models: claude-opus-4-8, claude-sonnet-4-6 (default),
# claude-haiku-4-5. Env vars: ANTHROPIC_API_KEY, ANTHROPIC_BASE_URL,
# ANTHROPIC_MODEL.
[providers.anthropic]
# api_key = "sk-ant-..."
# base_url = "https://api.anthropic.com"
# model = "claude-sonnet-4-6"

# OpenModel Provider (Anthropic-compatible Messages API)
# Talks to https://api.openmodel.ai/v1/messages with Bearer auth. OpenModel
# routes DeepSeek, DashScope, Xiaomi, Claude, and other models by model id.
# Env vars: OPENMODEL_API_KEY, OPENMODEL_BASE_URL, OPENMODEL_MODEL.
[providers.openmodel]
# api_key = "om-..."
# base_url = "https://api.openmodel.ai"
# model = "deepseek-v4-flash"

# ─────────────────────────────────────────────────────────────────────────────────
# Web Search Provider
# ─────────────────────────────────────────────────────────────────────────────────
# Choose which backend `web_search` uses. Default is DuckDuckGo HTML scraping
# with Bing fallback — no API key needed. Bing remains selectable for users who
# explicitly prefer it. Switch to Tavily, Bocha, Metaso, Baidu, Volcengine,
# Sofya, or a trusted SearXNG instance for API-backed search.
# API runtime failures and empty responses visibly degrade through DuckDuckGo
# then Bing. Missing configuration and network-policy denials fail closed.
#
# [search]
# provider = "duckduckgo"  # duckduckgo | bing | tavily | bocha | metaso | searxng | baidu | volcengine | sofya
#                            # duckduckgo: HTML scrape with Bing fallback
#                            # bing:       HTML scrape, no API key
#                            # tavily:     https://tavily.com — AI search, needs api_key
#                            # bocha:      https://bochaai.com — 博查AI搜索，国内友好，需api_key
#                            # metaso:     https://metaso.cn — 秘塔AI搜索，需 api_key
#                            #             设置 METASO_API_KEY 或 [search] api_key
#                            # searxng:    https://docs.searxng.org — trusted/self-hosted JSON API,
#                            #             set base_url; no public instance is used by default
#                            # baidu:      百度 AI Search via qianfan.baidubce.com，需 api_key
#                            # volcengine: 火山引擎 Ark web_search (免费 2 万次/月), 需 api_key
#                            #             也回退到 VOLCENGINE_API_KEY / VOLCENGINE_ARK_API_KEY / ARK_API_KEY 环境变量
#                            # sofya:      https://sofya.co — AI search returning full page
#                            #             content (not snippets), needs api_key (ay_live_...);
#                            #             also falls back to the SOFYA_API_KEY env var
# base_url = "https://search.example/" # optional DuckDuckGo-compatible HTML endpoint;
#                                      # required SearXNG root or /search endpoint
# api_key = "YOUR_SEARCH_KEY" # required for tavily, bocha, metaso, baidu, volcengine, and sofya; unused by searxng
#                             # WARNING: treat config.toml like a secret file when
#                             # storing API keys. Prefer env vars for local smoke tests.
#
# Env-var overrides:
#   DEEPSEEK_SEARCH_PROVIDER → search.provider
#   DEEPSEEK_SEARCH_API_KEY  → search.api_key
#   CODEWHALE_SEARCH_BASE_URL → search.base_url
#   DEEPSEEK_SEARCH_BASE_URL  → search.base_url (legacy alias)
#   METASO_API_KEY           → metaso key fallback
#   BAIDU_SEARCH_API_KEY     → baidu key fallback
#   VOLCENGINE_API_KEY / VOLCENGINE_ARK_API_KEY / ARK_API_KEY → volcengine key fallback
#   SOFYA_API_KEY            → sofya key fallback

# ─────────────────────────────────────────────────────────────────────────────────
# Network Policy (#135)
# ─────────────────────────────────────────────────────────────────────────────────
# Per-domain allow/deny rules for outbound network calls made by the TUI's
# tools (`fetch_url`, `web_search`) and the MCP HTTP transport. Stdio MCP
# servers and direct LLM API calls are unaffected.
#
# Precedence: deny wins. A host listed in both `allow` and `deny` is denied.
#
# Host-matching rules:
#   - Exact match: `api.deepseek.com` matches only `api.deepseek.com`.
#   - Subdomain wildcard: an entry starting with `.` (e.g. `.example.com`)
#     matches `api.example.com` and `a.b.example.com` but not the apex
#     `example.com`. To cover both, list both. `*.example.com` is also accepted.
#
# Defaults are intentionally conservative: when this section is absent, no
# policy is enforced (mirrors pre-v0.7.0 behavior). To opt in:
#
# [network]
# default = "prompt"     # allow | deny | prompt
# allow = ["api.deepseek.com", "github.com", ".githubusercontent.com"]
# deny = []
# proxy = ["github.com", ".githubusercontent.com"]
# proxy_fake_ip_cidrs = ["198.18.0.0/15"] # requires both matching host and address
# audit = true            # one line per call to ~/.codewhale/audit.log

# ─────────────────────────────────────────────────────────────────────────────────
# Verifier preview (#2093)
# ─────────────────────────────────────────────────────────────────────────────────
# Enables automatic claim-of-done verifier preview once the runtime trigger is
# active. Manual `run_verifiers` remains available even when this is false.
# The shipped policy maps pass/partial/fail to hunted/wounded/escaped.
#
# [verifier]
# enabled = false
# verdict_policy = "hunt"

# ─────────────────────────────────────────────────────────────────────────────────
# Advisor / Watcher (#3982)
# ─────────────────────────────────────────────────────────────────────────────────
# Optional background watcher that fires after each turn that contains tool
# calls. It reads a bounded slice of recent tool interactions, makes a concise
# LLM advisory call, and emits a brief note into the status area.
#
# Off by default.  Enable with `[advisor] enabled = true` or toggle per-session
# with `/advisor on` / `/advisor off`.
#
# Options (the full set — `AdvisorConfigToml` in crates/config/src/lib.rs):
#   enabled            — master switch (default: false)
#   max_tool_calls     — number of recent tool call/result pairs to read
#                        (default: 10, clamped to 1–50)
#   rate_limit_secs    — minimum seconds between successive advisor notes
#                        (default: 60, clamped to 5–3600)
#   dedup_window_secs  — notes whose content hash matches the previous note
#                        within this window are dropped (default: 300)
#   model              — model override for the advisory call; when absent the
#                        advisor reuses the session's current model
#
# Unknown keys under [advisor] are silently ignored, not rejected — a typo
# leaves the default in place with no error.
#
# [advisor]
# enabled = false
# max_tool_calls = 10
# rate_limit_secs = 60
# dedup_window_secs = 300
# model = "deepseek-v4-flash"

# ─────────────────────────────────────────────────────────────────────────────────
# Skills (#140)
# ─────────────────────────────────────────────────────────────────────────────────
# Settings for the `/skill install <spec>` community-skill installer.
#   * registry_url           — curated index.json that resolves bare names to
#                              `github:owner/repo` specs. Override to point at
#                              a private fork or internal mirror.
#   * max_install_size_bytes — per-skill uncompressed size cap. Tarballs that
#                              exceed this limit are rejected during validation.
#                              Default: 5 MiB.
#
# `/skill install` is gated by `[network]`. Make sure `github.com` and
# `raw.githubusercontent.com` are reachable (default `prompt` is fine — you'll
# be asked once and can persist) before running it.
#
# [skills]
# registry_url = "https://raw.githubusercontent.com/Hmbown/deepseek-skills/main/index.json"
# max_install_size_bytes = 5_242_880
# scan_codewhale_only = false # true: ignore Claude/OpenCode/Cursor/agentskills.io skill dirs

# ─────────────────────────────────────────────────────────────────────────────────
# TUI
# ─────────────────────────────────────────────────────────────────────────────────
[tui]
alternate_screen = "auto"   # auto/always use the TUI screen; never uses terminal scrollback
mouse_capture = true        # true copies only transcript user/assistant text; false uses raw terminal selection/copy
terminal_probe_timeout_ms = 500 # optional startup terminal-mode timeout (100-5000ms)
stream_chunk_timeout_secs = 900 # optional SSE idle timeout per chunk (0 = default, 1-3600)
osc8_links = true            # emit OSC 8 escapes around URLs (Cmd+click in iTerm2/Ghostty/Kitty/WezTerm/Terminal.app 13+); set false for terminals that misrender
# Ordered footer chips shown in the TUI status line. Omit the key to use the
# built-in default; set [] to hide all configurable chips. You can also edit
# this interactively with `/statusline`.
# Supported keys: mode, model, cost, balance (DeepSeek / DeepSeekCN only),
# status, agents,
# reasoning_replay, prefix_stability, cache, context_percent, git_branch,
# last_tool_elapsed (reserved), rate_limit (reserved), tokens.
# status_items = ["mode", "model", "status", "git_branch", "tokens", "cache"]
# notification_condition = "always" # always | never — overrides [notifications].threshold_secs.
#                                    "always" = notify on every successful turn (no threshold);
#                                    "never"  = suppress all turn-completion notifications;
#                                    unset    = use [notifications] defaults (recommended).
# locale = "auto"           # UI chrome language: auto | en | ja | zh-Hans | zh-Hant | pt-BR | es-419
#                           # | vi | ko | ca | de | fr | id | hi | ru | uk
#                           # "auto" reads LC_ALL → LC_MESSAGES → LANG; falls back to English.
#                           # Override: `locale = "zh-Hans"` for Simplified Chinese regardless of OS locale.
#                           # Also settable at runtime: /config locale zh-Hans
#                           # Note: this only affects TUI labels/chrome — it does NOT change model output language.
# mention_menu_behavior = "fuzzy" # fuzzy | browser; browser lists immediate directory children for @-mentions.

# ─────────────────────────────────────────────────────────────────────────────────
# Transcript
# ─────────────────────────────────────────────────────────────────────────────────
# Prose — user messages, assistant answers, and reasoning/thinking — fills the
# full content width, consistent with tool/status cells and the wide-frame
# decision in #5322 (#5436). Owners who want a bounded reading measure on
# ultrawide terminals can cap it in columns.
[transcript]
# prose_measure = 120   # positive integer: cap prose wrap at N columns.
                        # 0 or absent = full content width (default).
                        # Must be a positive whole number; tool, diff, and
                        # status cells always keep the full content width.

# ─────────────────────────────────────────────────────────────────────────────────
# Feature Flags
# ─────────────────────────────────────────────────────────────────────────────────
[features]
shell_tool = true
subagents = true
web_search = true # enables canonical web.run plus the compatibility web_search alias
apply_patch = true
mcp = true
exec_policy = true
# vision_model = false  # enable vision model for image_analyze tool
# verify_tool = false   # disable the agent-callable `verify` self-critique tool
                        # (#4196). On by default; the agent decides when to spend
                        # the extra reasoning, so cost is only incurred on demand.
                        # Set false to remove it from the model's tool catalog.

# ─────────────────────────────────────────────────────────────────────────────────
# Vision Model Configuration (optional)
# ─────────────────────────────────────────────────────────────────────────────────
# Uses an OpenAI-compatible vision model API for the `image_analyze` tool.
# api_key inherits from the main config if not specified.
#
# [vision_model]
# model = "gemini-3.1-flash-lite-preview"  # Required: vision-capable model ID
# api_key = "YOUR_API_KEY"                 # Optional: defaults to main api_key
# base_url = "https://generativelanguage.googleapis.com/v1beta/openai/"  # Optional
#
# Xiaomi MiMo image understanding can be configured through the same tool:
# model = "mimo-v2.5"
# api_key = "YOUR_XIAOMI_KEY"
# base_url = "https://token-plan-sgp.xiaomimimo.com/v1"  # Token Plan / tp- keys

# ─────────────────────────────────────────────────────────────────────────────────
# Retry Configuration
# ─────────────────────────────────────────────────────────────────────────────────
[retry]
enabled = true
max_retries = 3
initial_delay = 1.0
max_delay = 60.0
exponential_base = 2.0

# ─────────────────────────────────────────────────────────────────────────────────
# Context Compaction
# ─────────────────────────────────────────────────────────────────────────────────
# Auto-compaction is a saved UI setting edited with `/config` (`auto_compact`).
# The optional saved threshold setting is `auto_compact_threshold_percent`
# (default 80). There is no config-file
# `[compaction]` table yet; runtime compaction budgets are chosen by the TUI
# from the active model/context window.

# [context] supports `enabled` (default false) and `project_pack` (#4781).
# The old seam-manager keys (verbatim_window_turns, l1/l2/l3_threshold,
# seam_model) are parsed but ignored — seam_manager.rs no longer exists.

# ─────────────────────────────────────────────────────────────────────────────────
# Workshop / Large-Output Routing (#548)
# ─────────────────────────────────────────────────────────────────────────────────
# Tool outputs exceeding `large_output_threshold_tokens` are routed through a
# V4-Flash synthesis sub-agent.  Only the synthesis reaches the parent context;
# the raw text is stored in the workshop variable `last_tool_result` so the
# parent can call `promote_to_context` later if it needs the full content.
#
# Per-tool overrides let high-volume tools (e.g. Bash) use tighter
# thresholds without changing the global default. Name tools by the identifiers
# the model actually sees — `exec_shell`, `grep_files`, and `web_search` were
# retired and an override keyed to them matches nothing.
#
# There is no per-call `raw = true` escape. It was documented here, but
# `raw = true` on a tool call does NOT bypass routing: the adaptive router
# ignores it, and it is honoured only under the legacy
# `CODEWHALE_CLASSIC_OUTPUT_ROUTING` switch. No tool advertises it.
#
# [workshop]
# large_output_threshold_tokens = 4096
# # Optional model-visible byte ceilings (#5367). Absent keeps the
# # compile-time defaults (read 50KiB / read_file 16KiB, then the
# # compact 12K-char floor). Values raise the floor; they never lower
# # it. Hard cap is 2MiB.
# # read_result_max_bytes = 102400
# # tool_result_max_bytes = 102400
# [workshop.per_tool_thresholds]
# Bash = 2048          # shell output synthesised aggressively
# Web  = 8192          # web results can be large; give them more room

# ─────────────────────────────────────────────────────────────────────────────────
# Harness Profiles (preview schema; runtime consumption follows later)
# ─────────────────────────────────────────────────────────────────────────────────
# Harness profiles let future Codewhale runtime slices select model-specific
# prompt, context, tool, and subagent posture. v0.9 parses, validates, and can
# resolve profiles for tests/status plumbing, but normal Agent and Workflow
# runs do not silently promote or mutate behavior from these profiles yet.
#
# [[harness_profiles]]
# provider_route = "deepseek"
# model_pattern = "deepseek-v4.*"
#
# [harness_profiles.posture]
# kind = "cache-heavy"          # standard | cache-heavy | lean | custom
# max_subagents = 10            # 0 means runtime default
# prefer_codebase_search = false
# compaction_strategy = "prefix-cache" # default | prefix-cache | aggressive
# tool_surface = "full"              # full | read-only | auto
# safety_posture = "standard"        # standard | strict | permissive

# ─────────────────────────────────────────────────────────────────────────────────
# Profile Example (for multiple environments)
# ─────────────────────────────────────────────────────────────────────────────────
# Select a profile with `deepseek --profile <name>` or `DEEPSEEK_PROFILE=<name>`.
[profiles.work]
api_key = "WORK_DEEPSEEK_API_KEY"
base_url = "https://api.deepseek.com/beta"

[profiles.dev]
api_key = "DEV_DEEPSEEK_API_KEY"
allow_shell = true

[profiles.nvidia-nim]
provider = "nvidia-nim"
api_key = "YOUR_NVIDIA_API_KEY"
base_url = "https://integrate.api.nvidia.com/v1"
default_text_model = "deepseek-ai/deepseek-v4-pro"

# ─────────────────────────────────────────────────────────────────────────────────
# Desktop Notifications (OSC 9 / BEL on long agent-turn completion)
# ─────────────────────────────────────────────────────────────────────────────────
# Emits an escape sequence to the terminal when a turn **completes successfully**
# and took longer than `threshold_secs`. Failed or cancelled turns are
# intentionally silent. Useful when you tab away from the TUI and want an alert
# for "your task is ready".
#
# method        = "auto"   # auto | osc9 | bel | off
#                 auto: OSC 9 for iTerm.app / Ghostty / WezTerm.
#                       On macOS / Linux, falls back to BEL.
#                       On Windows, BEL is routed through MessageBeep(MB_OK).
#                 osc9: \x1b]9;<msg>\x07 (iTerm2-style; shows macOS notification)
#                 bel:  plain \x07 beep
#                 off:  disable entirely
# threshold_secs = 30      # only notify when the turn took >= this many seconds
# include_summary = false  # include elapsed time + cost in the notification body
# subagent_completion = "final-only" # always | final-only | off — per-subagent
#                          notifications during fleet/workflow runs. final-only
#                          (default) stays quiet mid-run and fires once when the
#                          batch drains; off silences them entirely.
# completion_sound = "beep" # off | beep | bell | file — sound on turn completion (✅ marker)
# sound_file = "E:\\google\\downloads\\notify.wav" # WAV used when completion_sound = "file" (Windows)
[notifications]
# method = "auto"
# threshold_secs = 30
# include_summary = false
# subagent_completion = "final-only"
# completion_sound = "beep"
# sound_file = "E:\\google\\downloads\\notify.wav"

# Opt-in per-event sound cues (#4817): deterministic, terminal-bell level
# (BEL bytes only — functional signals, platform-safe no-op when the terminal
# ignores BEL). Off by default. When completion_sound is active, turn-complete
# is left to that channel so the two never double-ding.
# [notifications.event_sound]
# enabled = false                                # master switch, default off
# events = ["turn-complete", "approval-needed"]  # allow-list; unknown names ignored
# min_interval_ms = 2000                         # per-event rate limit
# quiet = false                                  # true silences all event sounds

# ─────────────────────────────────────────────────────────────────────────────────
# Workspace Snapshots (#137)
# ─────────────────────────────────────────────────────────────────────────────────
# Each turn the TUI takes a `pre-turn:<seq>` and `post-turn:<seq>` snapshot of
# your workspace into a side-git repo at:
#
#     ~/.codewhale/snapshots/<project_hash>/<worktree_hash>/.git
#
# Your own `.git` is never touched — `--git-dir` and `--work-tree` are always
# set together when shelling out to git. Use `/restore N` (slash command) or
# the `revert_turn` tool to roll the working tree back. Conversation history
# is unaffected.
#
# Disk footprint: ~1-2 GB worst case for a 100 MB workspace × 12 turns/day,
# typically far less thanks to git's content-addressed storage. The session
# boot prunes anything older than `max_age_days` (default 7).
#
# [snapshots]
# enabled = true        # Snapshot workspace pre/post each turn for /restore
# max_age_days = 7      # Older snapshots pruned at session start
# max_workspace_gb = 2  # Snapshots self-disable on first init when the
#                         # non-excluded workspace exceeds this size in GB
#                         # (v0.8.32). Default 2 GB protects against running
#                         # codewhale in directories with hundreds of GB
#                         # of datasets / model weights / docker dumps where
#                         # `git add -A` would hang the TUI for hours. Set
#                         # to 0 to disable the cap (v0.8.31 behaviour);
#                         # raise to a higher number for legitimate large
#                         # monorepos.

# ─────────────────────────────────────────────────────────────────────────────────
# LSP Diagnostics (post-edit) (#136)
# ─────────────────────────────────────────────────────────────────────────────────
# After every successful file edit (`edit_file`, `apply_patch`, `write_file`),
# the engine asks an LSP server for diagnostics on the file and injects them
# as a synthetic system message before the next API call. This lets the agent
# see compile breaks immediately without round-tripping through the user.
#
# Enabled by default. Failure modes are non-blocking: a missing LSP binary,
# a crashed server, or a timeout simply skips the post-edit hook for that
# turn — the agent's work is never blocked.
#
# Built-in language → server defaults:
#   rust       → rust-analyzer
#   go         → gopls serve
#   python     → pyright-langserver --stdio
#   typescript → typescript-language-server --stdio
#   java       → jdtls
#   php        → intelephense --stdio
#   vue        → vue-language-server --stdio
#   c, cpp     → clangd
#
# Java support uses Eclipse JDT LS via the `jdtls` command. IntelliJ IDEA is
# not required, and installing IntelliJ IDEA alone does not install `jdtls`.
#
# Override the defaults via the `servers` table below.
#
# For languages not in the built-in list (Ruby, C#, Swift, etc.), use
# `[lsp.custom.<ext>]` to register a language server:
#
# [lsp.custom.rb]
# command = "ruby-lsp"
# args = ["--stdio"]
# language_id = "ruby"
#
# [lsp.custom.cs]
# command = "csharp-ls"
# args = []
# language_id = "csharp"
#
# [lsp.custom.swift]
# command = "sourcekit-lsp"
# language_id = "swift"
[lsp]
# enabled = true
# poll_after_edit_ms = 5000
# max_diagnostics_per_file = 20
# include_warnings = false
# [lsp.servers]
# rust = ["rust-analyzer"]
# go = ["gopls", "serve"]
# java = ["jdtls"]
# php = ["intelephense", "--stdio"]
# vue = ["vue-language-server", "--stdio"]

# ─────────────────────────────────────────────────────────────────────────────────
# Hooks (optional)
# ─────────────────────────────────────────────────────────────────────────────────
# Hooks run shell commands on lifecycle events (session start/end, tool calls, etc.).
# Configure as `[[hooks.hooks]]` under a `[hooks]` table.
#
# SCOPE: hooks are a TUI runtime feature. They fire from the interactive TUI
# and the engine turn loop it drives. `codewhale exec`, the CLI subcommands,
# the app-server / ACP surfaces, and the `workflow` tool do NOT fire them.
#
# Available events (all 11): session_start, session_end, message_submit,
# tool_call_before, tool_call_after, mode_change, on_error, turn_end,
# subagent_spawn, subagent_complete, shell_env.
# See docs/HOOKS.md for the per-event payload, env var, and steering contract.
#
# `message_submit`, `tool_call_before`, and `shell_env` are the only events
# whose result can change what Codewhale does. The rest are observer-only —
# which means their RESULT is ignored, not that the command is harmless. Every
# hook is an arbitrary shell command running with your credentials.
#
# Note: `default_timeout_secs` below OVERRIDES each hook's own `timeout_secs`.
# Leave it unset if you want per-hook timeouts to apply. `/hooks list` shows the
# effective value and names the override. `default_timeout_secs = 0` is
# REJECTED at load — it would expire every hook immediately — and per-hook
# `timeout_secs` applies instead. The timeout applies to background hooks too:
# on expiry the whole process group is killed and then reaped, best-effort,
# with a bounded reap wait (see docs/HOOKS.md → Timeouts).
#
# `background = true` means submitted and never awaited. The hook still gets
# the documented stdin payload, environment, and timeout — it just has no exit
# code, so it cannot steer. `shell_env` ignores the flag and always runs in the
# foreground because its stdout is the contract.
#
# A condition that references context its event never carries is REJECTED at
# load, logged, and shown by `/hooks list` — for example an `exit_code`
# condition outside `tool_call_after` / `on_error`, or a `mode` condition on
# `shell_env`. Rejection is per entry: a broken hook never drops another one
# that happens to share its name. `on_error` fires for tool failures with the
# tool name, call id, and reported exit code attached, so tool-scoped and
# exit-code-scoped `on_error` hooks are supported.
#
# `shell_env` (#456) is special: the hook runs immediately before each
# `exec_shell` invocation and its stdout is parsed as `KEY=VALUE\n` lines.
# Those vars are applied on top of `exec_shell`'s environment. For LOCAL
# execution that environment is built from a fixed allowlist of parent
# variables (PATH, HOME, LANG, TERM, …) — an ambient secret exported in your
# terminal is NOT forwarded to `exec_shell` by itself, so this hook is the
# supported way to supply one. If an external sandbox backend is configured,
# that allowlist does NOT apply: the backend owns its base environment and your
# `shell_env` values are TRANSMITTED to it. Later hooks override
# earlier ones. Use this for ephemeral credentials, per-skill PATH adjustments,
# or short-lived tokens. The resolved KEY names (NEVER values) are written to
# `~/.codewhale/audit.log` so each session can be reconciled later. Hook
# failure / timeout simply contributes no vars — it does not abort the shell
# call.
#
# [hooks]
# enabled = true
# default_timeout_secs = 30
#
# [[hooks.hooks]]
# event = "session_start"
# command = "echo 'Codewhale session started'"
#
# # Inject ephemeral creds into every shell call. Output one
# # KEY=VALUE per line on stdout (export prefix optional).
# [[hooks.hooks]]
# name = "aws-creds"
# event = "shell_env"
# command = "aws-vault export my-profile --format=env"
# # Optionally limit to specific tool names / categories:
# # condition = { type = "tool_category", category = "shell" }
#
# # Observe sub-agent lifecycle events. These hooks receive bounded JSON
# # metadata on stdin and are warn-only: failures do not affect sub-agent
# # scheduling, prompts, or results. continue_on_error has no effect for
# # these observer events; later matching hooks always continue.
# [[hooks.hooks]]
# name = "subagent-audit"
# event = "subagent_complete"
# command = "~/.codewhale/hooks/subagent-audit.sh"

# ─────────────────────────────────────────────────────────────────────────────────
# Runtime API (`deepseek serve --http`) (#561)
# ─────────────────────────────────────────────────────────────────────────────────
# Tuning knobs for the local HTTP/SSE daemon. The server binds to 127.0.0.1
# by default and is intended for local UIs (whalescale-desktop, dashboards,
# automation scripts). Today this section only controls the CORS allow-list;
# host/port/workers stay on `--host`, `--port`, and `--workers` flags.
#
# Built-in defaults always include:
#   http://localhost:3000   http://127.0.0.1:3000
#   http://localhost:1420   http://127.0.0.1:1420
#   tauri://localhost
#
# Use `cors_origins` to add extra dev origins (e.g. Vite's default `:5173`).
# User entries STACK on top of the defaults — they do not replace them. The
# CLI flag `--cors-origin URL` (repeatable) and env var
# `DEEPSEEK_CORS_ORIGINS=url1,url2` resolve to the same merged list.
#
# [runtime_api]
# cors_origins = ["http://localhost:5173", "http://127.0.0.1:5173"]

# ─────────────────────────────────────────────────────────────────────────────────
# Tool Overrides & Plugins ([tools])
# ─────────────────────────────────────────────────────────────────────────────────
# The `[tools]` table lets you replace any built-in tool with a custom
# implementation (script or command) or disable it entirely — without
# forking or recompiling the binary.
#
# Plugin scripts dropped in the plugin directory are auto-discovered and
# registered as model-visible tools alongside the built-in ones.
#
# Scripts receive the tool's JSON input on **stdin** and must return a
# JSON `ToolResult` (`{"content": "...", "success": true}`) on **stdout**.
#
# [tools]
# # Custom plugin directory (defaults to `~/.codewhale/tools/`)
# plugin_dir = "~/.codewhale/tools"
#
# [tools.overrides]
# # Disable a tool entirely — removes it from the model-visible catalog.
# "code_execution" = { type = "disabled" }
#
# # Replace a tool with a script. Relative paths resolve against plugin_dir.
# "exec_shell" = { type = "script", path = "audit-exec-shell.sh" }
#
# # Replace a tool with a command (binary on PATH or absolute path).
# "read_file" = { type = "command", command = "bat", args = ["--paging=never"] }
#
# # Scripts can also accept static arguments before the JSON input:
# "fetch_url" = { type = "script", path = "cached-fetch.sh", args = ["--ttl", "300"] }

# ──────────── Enterprise example: audit-logging exec_shell wrapper ──────────────
# Drop `audit-exec-shell.sh` in `~/.codewhale/tools/` and enable with:
#
# [tools.overrides]
# "exec_shell" = { type = "script", path = "audit-exec-shell.sh" }
#
# The wrapper logs every request to `~/.codewhale/audit/exec_shell.log`, then
# delegates to your own approved shell executor. Do not pipe the raw JSON
# request into `sh -s`; parse the command field and enforce your policy first.
#
# ```sh
# #!/usr/bin/env sh
# # name: exec_shell
# # description: Audit-logging wrapper for exec_shell
# # approval: required
# LOGDIR="${HOME}/.codewhale/audit"
# mkdir -p "$LOGDIR"
# LOGFILE="$LOGDIR/exec_shell.log"
# input=$(cat)
# echo "[$(date -Iseconds)] $input" >> "$LOGFILE"
# printf '%s\n' '{"content":"audit wrapper dry run: configure an executor","success":false}'
# ```

# ─────────────────────────────────────────────────────────────────────────────────
# Workflow automatic launch, approval, isolation, and activity (#4128)
# ─────────────────────────────────────────────────────────────────────────────────
# First-class knobs for automatic Workflow orchestration. When the table is
# omitted entirely, the runtime uses these product defaults. Later launch,
# approval, and activity-persistence paths all read through this one model.
# [workflow]
# # Allow the parent agent to auto-launch Workflow for multi-agent work.
# # Set false to require an explicit `/workflow` opt-in.
# automatic = true
# # Auto-start read-only plans without an approval card when automatic is on.
# auto_start_read_only = true
# # Require an approval card before write/shell/network/high-budget launches.
# require_approval_for_writes = true
# # Soft cap on children admitted by automatic launch (larger plans ask first).
# auto_start_child_limit = 16
# # Hard ceiling on agents in one Workflow run (matches VM lifetime cap).
# max_children = 1000
# # Maximum concurrently live agents inside one run (others wait for a slot).
# max_concurrent = 16
# # Maximum structural nesting depth accepted for Workflow IR (default 5).
# # This is separate from Runtime child delegation below.
# max_depth = 5
# # Default shared token budget for a Workflow run and its children.
# default_token_budget = 120000
# # Parallel write children that may share the parent worktree without
# # isolation. 0 forces worktree isolation for parallel writes.
# max_parallel_writes_without_worktree = 0
# # Keep completed Workflow activity visible until the next run / clear.
# persist_completed_activity = true
# # Persist completed activity across process restarts via the run journal.
# persist_completed_across_restarts = true

# ─────────────────────────────────────────────────────────────────────────────────
# Agent Fleet roster, role registry, and execution requests (#3165, #3167)
# ─────────────────────────────────────────────────────────────────────────────────
# [fleet]
# # Fleet stores member identity and route intent. Project trust, host identity,
# # secrets, approvals, sandboxing, filesystem/network reach, and tool authority
# # are Runtime policy and are deliberately not configured here. Pre-0.9.11
# # trust keys are accepted only as ignored migration input.
#
# # Headless worker execution hardening (#3027)
# [fleet.exec]
# # Tools always allowed regardless of role
# allowed_tools = []
# # Tools always disallowed (overrides role and task spec)
# disallowed_tools = ["exec_shell"]
# # Optional hard ceiling on worker steps (tool calls + model turns).
# # Omit or set 0 for the unbounded default; use a positive value to opt in.
# max_turns = 500
# # Runtime child-agent depth for fleet workers. Shares ONE recursion axis with
# # standalone sub-agents (a fleet worker IS a headless sub-agent). This is an
# # execution request, not Fleet member identity. 0 blocks child agents (the
# # root worker still runs); 3 is the default and 8 is the opt-in hard ceiling.
# max_spawn_depth = 3
# # Extra system prompt injected into every headless worker
# append_system_prompt = "Never modify .git/config or change remotes."
# # Output format: "text" (default) or "stream-json" for ndjson events
# output_format = "text"
#
# # Fleet profiles define named agent configurations the roster can dispatch.
# # Built-in profiles are always available: manager, operator, scout, builder,
# # reviewer, verifier, synthesizer, general. User-defined profiles under
# # [fleet.profiles] override or extend the built-in set by id. Precedence
# # is Workspace (.codewhale/agents/*.toml) > Config ([fleet.profiles]) > BuiltIn.
# # See /fleet setup for an in-app profile-authoring wizard.
# [fleet.profiles.ci-linter]
# slot = "verifier"
# loadout = "fast"
# model = "deepseek-v4-pro"
#
# [fleet.profiles.ci-linter.role]
# name = "CI Linter"
# description = "Runs linters and formatters"
# instructions = "Run cargo fmt --check and cargo clippy; never apply fixes."
#
# [fleet.profiles.pr-reviewer]
# slot = "reviewer"
# loadout = "inherit"
#
# [fleet.profiles.pr-reviewer.role]
# name = "PR Reviewer"
# description = "Reviews PRs with GitHub access"
# instructions = "Review diffs for correctness, regressions, and missing tests."

# ─────────────────────────────────────────────────────────────────────────────────
# Named operator-scoped Fleet configurations (#5039)
#
# Multiple named Fleets may coexist alongside the default [fleet] table.
# Each [fleets.<name>] entry must include an `operator` field and may configure
# its own roles, profiles, and execution requests independently. Runtime policy
# remains separate from Fleet identity.
#
# Selection precedence (most specific wins):
#   1. Explicit fleet name  — config.resolve_fleet("name")
#   2. Operator lookup      — config.resolve_fleet_for_operator("alice")
#   3. Global default       — config.fleet  (the [fleet] table)
#
# Unknown fleet/operator references fail with an actionable error listing
# what IS configured, rather than silently falling back.
# ─────────────────────────────────────────────────────────────────────────────────
#
# [fleets.alice-team]
# # Required: the operator/leader identity for this fleet.
# operator = "alice"
#
# [fleets.alice-team.exec]
# max_turns = 200
# max_spawn_depth = 2
# append_system_prompt = "Always ask before modifying configuration files."
#
# [fleets.alice-team.profiles.ci-linter]
# slot = "verifier"
# loadout = "fast"
# model = "deepseek-v4-pro"
#
# [fleets.alice-team.profiles.ci-linter.role]
# name = "CI Linter"
# description = "Runs linters and formatters for alice-team"
# instructions = "Run cargo fmt --check and cargo clippy; never apply fixes."
#
# [fleets.bob-team]
# operator = "bob"
#
# [fleets.bob-team.profiles.implementer]
# slot = "implementer"
# loadout = "inherit"

# ─────────────────────────────────────────────────────────────────────────────────
# Requirements (admin constraints) example file
# ─────────────────────────────────────────────────────────────────────────────────
# allowed_approval_policies = ["on-request", "untrusted", "never"]
# allowed_sandbox_modes = ["read-only", "workspace-write"]