Use when module planning and source coverage are done and the run needs writer-ready per-module packs.
中文简介正在准备中。当前显示原文说明。
查看安装方法安装前可以查看交给 AI 代理的指令内容。
source-tutorial 的 C2，已有 module plan + source coverage，需要组织成稳定写作输入。Combines module structure, source coverage, and source snippets into one deterministic JSONL pack per module.
outline/module_plan.ymloutline/source_coverage.jsonlsources/provenance.jsonloutline/tutorial_context_packs.jsonlEach pack must include:
module_idtitleobjectivecore_conceptsexercise_seedsource_snippetsscripts/run.py should:
Keep snippet ranking and pack synthesis in shared tutorial tooling rather than in the thin wrapper script.
module_id and objective还没有评价。欢迎分享你的使用感受。
无需登录即可发表。欢迎分享使用感受、提问，或说明在哪些环境下无法运行。
还没有评论。来写第一条吧。
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`.
中文简介正在准备中。当前显示原文说明。
Download a small corpus of open-access arXiv survey/review PDFs about agentic systems and extract text for style learning.
中文简介正在准备中。当前显示原文说明。
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.
中文简介正在准备中。当前显示原文说明。
Curate reader-facing survey tables for the Appendix (clean layout + high information density), using only in-scope evidence and existing citation keys.
中文简介正在准备中。当前显示原文说明。
Build a final, machine-readable argument snapshot from current H3 sections and refresh section fingerprints before merge.
中文简介正在准备中。当前显示原文说明。
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.
中文简介正在准备中。当前显示原文说明。