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generate-docs.py learns the agent-launcher domain (5 hardcoded maps extended); regenerated docs tree: 343 skill pages / 96 agent pages / 122 command pages (561 total). mkdocs.yml nav gains the Agent Launcher skill section (7 pages), 4 cs-agent-* agent entries, and 8 /cs:* command entries; all nav targets verified to exist. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_012FwXG6TqCXKZQvF4iD69cv
29 lines
1.4 KiB
Markdown
29 lines
1.4 KiB
Markdown
---
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title: "/cs-grade — Slash Command for AI Coding Agents"
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description: "Phase 3 — the bounded grade→iterate loop. Define a CMA outcome (required rubric, max_iterations 1..20), read each grader verdict, decide the next. Slash command for Claude Code, Codex CLI, Gemini CLI."
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---
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# /cs-grade
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<div class="page-meta" markdown>
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<span class="meta-badge">:material-console: Slash Command</span>
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<span class="meta-badge">:material-github: <a href="https://github.com/alirezarezvani/2-claude-skills/tree/main/agent-launcher/commands/cs-grade.md">Source</a></span>
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</div>
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Run the `grade-iterate` skill.
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**$ARGUMENTS**
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## Steps
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1. `python3 agent-launcher/skills/grade-iterate/scripts/outcome_builder.py --sheet ./my-agent/build-sheet.json --max-iterations 5 --out ./my-agent/payloads/outcome.json`
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— rubric required; send as a `user.define_outcome` event.
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2. On each verdict: `python3 agent-launcher/skills/grade-iterate/scripts/verdict_reader.py --result ./my-agent/last-verdict.json`
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→ SHIP / SHARPEN / ESCALATE / RESUME. Each iteration must move ≥1 rubric line
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fail→pass.
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3. Once a version passes: `python3 agent-launcher/skills/grade-iterate/scripts/eval_scaffold.py --sheet ./my-agent/build-sheet.json --out ./my-agent/eval.json`
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— held-back cases in parallel (≤25 threads).
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4. Decide: ship v0, or `goal_state.py set --phase run-without-you`.
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Bounded loops only. Read the verdict before acting. Held-back cases stay held back.
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