Environment
- WallBreaker installed from source (
pip install -e .), macOS
- Config: brain =
agent-prime (thegrid, tool-tagged per Cherry Studio's model picker), target/judge = agent-standard (thegrid), protocol openai, base_url = https://api.thegrid.ai/v1
Repro steps
/sysprompt load <file>, /objective <text>, /rounds 10, /auto on
- Send a kickoff message describing the objective
- Agent produces zero tool calls for 2 consecutive rounds →
Agent stalled twice with no action. Give it direction.
What I tried
- Originally used
agent-standard as the brain — confirmed via Cherry Studio's model picker that it's not tool-tagged (it's a reasoning model that burns its token budget on reasoning_content before emitting real output/tool calls — reproduced this independently via a raw curl to /v1/chat/completions with max_tokens: 5, got content: null, finish_reason: "length", reasoning-only output). Switching to agent-prime (tool-tagged) fixed that stall on one occasion.
- On a later run (different challenge, same config),
agent-prime stalled again — twice — even after sending an explicit follow-up naming the exact tool to call (query_target) and providing literal text to send as the probe. Still zero tool calls, empty response both times.
Question
Is there a known reliability issue with agent-prime tool-calling via thegrid's OpenAI-compatible endpoint? Does system-prompt/objective length affect tool-call emission? Is there a config flag to force stricter tool-call mode, or a recommended thegrid model for the attacker brain role specifically?
Environment
pip install -e .), macOSagent-prime(thegrid, tool-tagged per Cherry Studio's model picker), target/judge =agent-standard(thegrid), protocolopenai,base_url = https://api.thegrid.ai/v1Repro steps
/sysprompt load <file>,/objective <text>,/rounds 10,/auto onAgent stalled twice with no action. Give it direction.What I tried
agent-standardas the brain — confirmed via Cherry Studio's model picker that it's not tool-tagged (it's a reasoning model that burns its token budget onreasoning_contentbefore emitting real output/tool calls — reproduced this independently via a raw curl to/v1/chat/completionswithmax_tokens: 5, gotcontent: null,finish_reason: "length", reasoning-only output). Switching toagent-prime(tool-tagged) fixed that stall on one occasion.agent-primestalled again — twice — even after sending an explicit follow-up naming the exact tool to call (query_target) and providing literal text to send as the probe. Still zero tool calls, empty response both times.Question
Is there a known reliability issue with
agent-primetool-calling via thegrid's OpenAI-compatible endpoint? Does system-prompt/objective length affect tool-call emission? Is there a config flag to force stricter tool-call mode, or a recommended thegrid model for the attacker brain role specifically?