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[efficiency-improver] Monthly Activity 2026-05Β #5

Description

@github-actions

πŸ€– Efficiency Improver here β€” I'm an automated AI assistant focused on reducing the energy consumption and computational footprint of this repository.

Activity for May 2026

Suggested Actions for Maintainer

Energy Efficiency Backlog

Priority Focus Area Opportunity Estimated Impact
MEDIUM Frontend / UI Energy & Networking Optimise docs/green-software-with-ai.jpeg (482 KB hero image referenced from README.md:1) WebP q=85: βˆ’34% (βˆ’165 KB) or JPEG optimize+progressive q=85: βˆ’37% (βˆ’178 KB). Measured via Pillow; PSNR 32.55 dB.
LOW Documentation Token efficiency of agent/skill markdown when loaded into Claude context ~10–15% theoretical; readability cost likely outweighs β€” not actioning.

Discovered Commands

No build, test, benchmark, lint, or format commands exist β€” this is a documentation/configuration-only repository (Claude Code agent + skill definitions, markdown docs). The only "executable" surface is the gh-aw workflow itself, which is operated upstream.

Run History

2026-05-21 β€” Run

2026-05-19 22:57 UTC - Run

2026-05-18 23:21 UTC - Run

  • πŸ” First-run repo scan: confirmed docs-only repo (no application code, no build/test commands).
  • πŸ“Š Measured docs/green-software-with-ai.jpeg (482 KB) against WebP and optimized-JPEG alternatives. Best in-format saving: 37% / 178 KB (JPEG q=85 optimize+progressive). Best cross-format saving: 44.7% / 215 KB (WebP q=80).
  • πŸ”§ Filed efficiency opportunities issue [efficiency-improver] Energy efficiency opportunities β€” initial scan (2026-05)Β #4 with measured trade-offs β€” awaiting maintainer choice of format before opening a PR (no breaking binary swaps without approval).
  • 🌱 GSF principle applied: Networking β€” every byte saved on the hero image translates to less energy across CDN, network, and client decode.

Generated by Efficiency Improver Β· ● 7.5M Β· β—·

To install this agentic workflow, run

gh aw add githubnext/agentics/workflows/efficiency-improver.md@79c99dfd73f3b7ad8ab2b0f4944838018dbe4736

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