topic-learn

name	topic-learn
description	Learn one topic end to end (学): scoped mission, layered sources, mastery map, verified evidence, canonical article, interview layer, learning records. Modes new or refresh. Use for 主题学习, 技术深挖, 溯源验证; not single-link summaries, blank-page article writing, or codebase audit.

Topic Learn

Role: 学 — Turn one knowledge point into a reusable, source-backed, verifiable topic asset.

Examples: Java reflection, TCP congestion control, Raft, HTTP caching, Postgres MVCC.

Not for: single-link summaries, opinion without sources, shallow cheat sheets, marketing-only article drafts, codebase audit.

Invocation

Required	Optional
Topic (one knowledge point)	mode: new (default) or refresh
Boundary + out of scope	Depth: brief / standard (default) / deep
Success looks like (≥2 outcomes)	Save path, language zh / en
Save directory

Missing Success or boundary → ask at most 3 questions. Do not start Source until Mission is writable.

Depth

Level	Deliverables
brief	Mission + map + sources/INDEX + slim main article (problem, mechanism, sources); interview: one-liner + ≥3 follow-ups
standard	Full checklist; glossary optional
deep	+ glossary and/or reference/; 0–2 side articles; mechanism-heavy topics default to diagrams (article-structure.md)

Detail: references/formats.md → Depth.

Modes (TOPIC.yaml → mode)

Mode	When
new	No workspace yet, or full first pass
refresh	Merge, gap-fill, re-verify, or humanize-only

Refresh variants (detail in references/workflow.md):

• Merge — align scattered drafts; diff-only Write
• Gap-fill — only missing pieces (e.g. interview)
• Verify / polish — re-run demos, fix verified_on, humanize touched files

Before you start

1. Read existing topic dir; set mode in TOPIC.yaml (references/formats.md).
2. New workspace — optional bootstrap:

/path/to/topic-learn/scripts/topic_scaffold.sh /path/to/<topic-dir> <slug> [zh|en]

3. 按需读 — start at references/README.md; never bulk-read all references.

Flow

Scope → Source → Model → Verify → Write → Interviewize → Record → Humanize → Checklist

• new: full flow (references/workflow.md).
• refresh: delta on each step; touch ≤6 files unless full rewrite.

Stop points (user may say「一次跑完」):

1. After Scope — confirm Mission + boundary.
2. After Model — confirm mastery-map + gaps before Write.

Hard rules

• One topic per run.
• No mastery map → no Write.
• No L1/L2 for key claims → no Write (or explicit Open).
• No verification → not complete.
• No interview layer → not complete.
• All prose artifacts in one topic directory (code_repo for runnable code when documented).

Humanize boundary

Polish main + interview when the user asks — preserve sources, verification commands, claims, and glossary terms. User style notes override default tone.

Need	Skill
Learning-topic polish in this workspace	This skill (Step 8)
Neutral de-AI only, no author persona	humanizer (user triggers separately)
Author voice + publish-ready in writing flow	article-write refine stage

Related skills

Skill	When
article-read	Source step — fetch URL/PDF into sources/ (references/source-ingest.md)
humanizer	Finished main/interview, neutral de-AI only
article-write	Turn mastery assets into publish-oriented articles (user triggers separately)
flowguard	Long new/refresh spanning many sessions — wrap with checkpoints

Validation

bash -n topic-learn/scripts/topic_scaffold.sh
bash -n topic-learn/scripts/topic_check.sh
topic-learn/scripts/topic_scaffold.sh /tmp/topic-smoke test-slug zh
topic-learn/scripts/topic_check.sh /tmp/topic-smoke    # expect warnings on fresh scaffold

Before marking phase: shipped, run topic_check.sh on the topic directory.

References

Start at references/README.md. Scripts: topic_scaffold.sh, topic_check.sh.