grade-iterate
当已上线的托管智能体需要按评分标准进行评分并改进时使用(“给我的智能体评分”“它是否足够好”)。用 outcome_builder.py 构建结果,用 verdict_reader.py 读取判定,并从 eval_scaffold.py 运行留出评估。
机器翻译查看英文原文
Use when a launched managed agent needs grading against a rubric and improving ('grade my agent', 'is it good enough'). Builds the outcome with outcome_builder.py, reads verdicts with verdict_reader.py and runs held-back evals from eval_scaffold.py.
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原作者说明节选
从固定版本的 SKILL.md 提取,保留原文语言。以下内容属于作者说明,本站尚未验证安装、兼容或运行结果。
查看英文原文
原文涵盖的主题
- Phase 3 — Grade → Iterate (the bounded loop)
- Workflow
- Hard rules
- Forcing-question library (recommend + cite)
- Tools
This is the plugin's loop: CMA's outcome primitive self-grades the agent's work in an isolated context and feeds failing verdicts back for the next attempt. It is always bounded by maxiterations (1..20) — never "improve forever". See ../../references/loops-and-workflows.md and the outcome section of ../../references/cma-primitives.md. 1. Define the outcome. The rubric is required; maxiterations is clamped to 1..20. Send the payload as a user.defineoutcome event (append to the running session). 2. Read every verdict first. Tables the rubric outcome and recommends: SHIP (satisfied), SHARPEN then re-run (needsrevision), ESCALATE (maxiterationsreached / failed), RESUME (interrupted). With ≤1 iteration left it flips to "make the single highest-value fix or escalate now". 3. Loop invariant. Each iteration must move ≥1 rubric line fail→pass, or the run halts at the cap and escalates. Don't burn the budget on cosmetic edits. 4. Once a version passes, run held-back eval. Held-back cases (never seen during iteration) run in parallel, capped at the 25-thread CMA ceiling, each graded against the same rubric. 5. Decide. SHIP as v0, or promote to a scheduled deployment (Phase 4). Record the verd
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- 来源仓库
- alirezarezvani/claude-skills
- 源文件
- agent-launcher/skills/grade-iterate/SKILL.md
- 固定版本
- 8f082544116fc0d014188e521ca40304cdfc86b0
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原作者:alirezarezvani/claude-skills · 原作者仓库元数据。文档核查:未核查。最近来源检查:2026-11-09T14:01:45.923Z。
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