一键导入
cogamer-improve
Implement one targeted CvC code change from analysis, verify improvement, submit if better
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
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Implement one targeted CvC code change from analysis, verify improvement, submit if better
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
| name | cogamer.improve |
| description | Implement one targeted CvC code change from analysis, verify improvement, submit if better |
Implement one targeted code change based on an analysis, verify it improves scores, and submit.
Announce at start: "I'm using the improve skill to implement and verify a fix from the analysis."
Run /cogamer.analyze first to produce cogamer/analysis.md with a diagnosis.
Read cogamer/analysis.md. Understand the weakness, root cause, and proposed fix.
softmax cogames eval -m machina_1 -p class=cvc_policy.cogamer_policy.CvCPolicy -e 10 --format json --seed 42
Record the average reward as the baseline.
Make one focused code change as described in the analysis. Touch only the files identified. Keep the diff minimal.
Possible change surfaces:
src/cvc_policy/agent/main.py, roles.py, targeting.py, pressure.py, scoring.py, navigation.pysrc/cvc_policy/programs.py (program table, LLM prompt, LLM response parsing)src/cvc_policy/agent/types.pysrc/cvc_policy/game_state.pyRun the same eval across 5 seeds:
for seed in 42 43 44 45 46; do
softmax cogames eval -m machina_1 -p class=cvc_policy.cogamer_policy.CvCPolicy -e 5 --seed $seed --format json
done
git checkout the changed files, report what didn't workGet the player name from softmax cogames player list. Submit automatically:
cogames upload -p class=cvc_policy.cogamer_policy.CvCPolicy -n <cogamer-name>
Do NOT ask for confirmation. Log the submission.
Append the result to cogamer/analysis.md:
## Result
- baseline: X
- after: Y
- verdict: improved/regressed/neutral
- submitted: yes/no
Diagnose the biggest CvC policy weakness from eval metrics and LLM-Python trace data
Run multi-episode CvC evaluation and produce structured JSON metrics
Run a CvC game and capture LLM-Python communication trace for analysis
Install softmax-cli, authenticate via softmax login, and find or create a cogames player