Use when a tutorial module plan exists but each module still needs a verifiable teaching loop.
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查看安装方法安装前可以查看交给 AI 代理的指令内容。
outline/module_plan.yml，需要为每个模块补齐 exercise / expected output / verification steps。Adds the minimal deterministic exercise contract to each planned tutorial module.
outline/module_plan.ymloutline/module_plan.ymlEach module must end up with at least one exercise containing:
promptexpected_outputverification_stepsscripts/run.py should:
Keep exercise phrasing logic in shared tutorial tooling rather than hardcoding it repeatedly in the skill script.
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Internal template for creating or refactoring a skill into the repository's reference-first shape. **Trigger**: reference-first template, blueprint skill, create a reusable skill, refactor a script-heavy skill. **Use when**: you need a lean `SKILL.md`, explicit `references/`, machine-readable `assets/`, and a minimal deterministic `run.py`.
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Download a small corpus of open-access arXiv survey/review PDFs about agentic systems and extract text for style learning.
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Extract per-subsection “anchor facts” (NO PROSE) from evidence packs so the writer is forced to include concrete numbers/benchmarks/limitations instead of generic summaries.
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Curate reader-facing survey tables for the Appendix (clean layout + high information density), using only in-scope evidence and existing citation keys.
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Build a final, machine-readable argument snapshot from current H3 sections and refresh section fingerprints before merge.
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Audit one research Workspace for declared Unit outputs and Pipeline target Artifacts, writing `output/CONTRACT_REPORT.md`; use for mid-Run coverage snapshots or final delivery completeness, not deep provenance integrity.
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