Use when an approved tutorial spec exists and the run needs a deterministic prerequisite graph before module planning.
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Run score Not tested
See how to installReview the instructions the agent will receive before you install.
source-tutorial 的 C2，已有 output/TUTORIAL_SPEC.md，需要把教程概念转成可排序的 DAG。Materializes the tutorial spec's structured concept inventory into outline/concept_graph.yml.
output/TUTORIAL_SPEC.mdoutline/concept_graph.ymlThe graph must contain:
nodes: {id, title, summary, source_ids, objective_refs}edges: {from, to} meaning prerequisite orderscripts/run.py should:
Do not duplicate spec-parsing heuristics in multiple places; keep them in shared tutorial tooling.
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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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