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Skill phucbm/skills/skills/meta/learn

Scan the current codebase, compare against existing phucbm/skills knowledge, and suggest new skills to save or existing skills to update. Use when the user says "learn from this repo", "what can I save from here", or "run learn".From its SKILL.md

Install
npx -y skills add phucbm/skills --skill learn

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

2 things to look at

  • no licenseNo license file was found in the repository. Code published without one is not open source by default, so using it at work is a question for whoever answers licensing questions where you are.
  • 2 stars2 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

SKILL.md

4.4 KB, ~1.0k tokens by cl100k_base, as published. Nobody here has run it

What this skill does

Reads your existing skills from phucbm/skills README, scans the current codebase, diffs the two, and presents a ranked list of save/update candidates with recommended file paths. You pick which ones to act on.

Steps

Phase 1 — Pull existing skills index (read README only)

gh repo clone phucbm/skills /tmp/phucbm-skills 2>/dev/null || git -C /tmp/phucbm-skills pull

Read /tmp/phucbm-skills/README.md only. Extract:

  • Knowledge table: topic names and descriptions (what's already saved)
  • Skills table: skill names (operational skills already known)

Phase 2 — Scan current codebase (run in parallel)

Read these in parallel:

  • package.json / composer.json / pyproject.toml / Cargo.toml / go.mod — deps and scripts
  • Config files at root: next.config.*, vite.config.*, drizzle.config.*, biome.jsonc, playwright.config.*, tailwind.config.*
  • .github/workflows/*.yml — CI/CD patterns
  • scripts/ directory — custom tooling
  • Key source entry files: lib/, src/, app/ top-level only (don't recurse deep — read index/entry files)
  • .claude/CLAUDE.md and .claude/docs/ if present — already-documented patterns

Extract topics: libraries used, non-obvious configurations, custom patterns, architectural decisions, CI/CD tricks.

Phase 3 — Diff and rank

Cross-reference found topics against existing README knowledge and skills tables.

Produce two lists with recommended file paths for every item:

NEW — topics found in codebase with no match in existing knowledge/skills:

[N] Topic name — one-line reason it's worth saving
    skill:     skills/<topic>/SKILL.md
    knowledge: knowledge/<category>/<slug>.md

If multiple new topics share knowledge (e.g. rag + pinecone), show the relationship:

[N] RAG pipeline — generic chunk→embed→query pattern, reusable with any vector DB
    skill:     skills/rag/SKILL.md
    knowledge: knowledge/rag/concepts.md

[N+1] Pinecone — vector DB setup, upsert, query, metadata filters
    skill:     skills/pinecone/SKILL.md
    knowledge: knowledge/pinecone/setup.md
    note:      skills/rag will also reference knowledge/pinecone/setup.md

UPDATE — topics that overlap an existing entry but the codebase shows something new:

[N] update: <existing-topic> — what's new or different
    file: knowledge/<category>/<slug>.md

Rank by: reusability across projects × non-obviousness (things you'd have to figure out again from scratch).

Skip topics that are: trivial to look up, fully covered already, or project-specific with no transfer value.

Phase 4 — User picks, then act

Present the full list and ask: "Which ones to save? (e.g. 1, 3, update 4 — or 'all')"

Wait for response. Then for each selected item:

  • NEW picks → invoke add-skill flow: draft skills/<topic>/SKILL.md + knowledge/<category>/<slug>.md, show both, confirm, push
  • UPDATE picks → invoke update-skill flow: show diff of proposed changes to existing knowledge file, confirm, push

Each item is confirmed individually. Never batch-push without showing what will change.

After all pushes: confirm final state and remind user to run /plugin marketplace update phucbm in other projects to get the new skills.

Rules

  • Phase 1 reads README.md only — no file tree scanning of the skills repo (saves tokens)
  • Phase 2 reads breadth-first — top-level files only, don't recurse into deep source dirs
  • Always output recommended file paths in Phase 3 — user must confirm names before any files are written
  • Skills are flat: skills/<topic>/SKILL.md — one level only, no bucket subdirectories
  • Knowledge can be namespaced: knowledge/<category>/<slug>.md — flag when shared across skills
  • Never suggest saving secrets, API keys, or project-specific data (user IDs, URLs, credentials)
  • Knowledge files are generic — cite specific projects as examples only, never as facts
  • Always confirm per-item before pushing
  • If nothing new is found, say so clearly rather than inventing suggestions

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.

Gives 0 of the 12 instructions most learn study skills give in ~1.0k tokens

Counted across 545 of the 593 authors here whose files we hold, read 2026-09-06

  • Treat the current directory as a teaching workspacein 20 of 545, across 17 files
  • Teach knowledge first then practice skillsin 19 of 545, across 16 files
  • Design lessons which build long-term retentionin 15 of 545, across 12 files
  • Save each lesson as a self-contained HTML filein 15 of 545, across 12 files
  • Question the user on why they want to learn thisin 15 of 545, across 12 files
  • Reuse components from the assets directoryin 14 of 545, across 11 files
  • Never trust your parametric knowledgein 13 of 545, across 10 files
  • Record user preferences in NOTES.mdin 11 of 545, across 8 files
  • Ground all teaching in the MISSION.md documentin 11 of 545, across 8 files
  • Save each lesson to the lessons directoryin 8 of 545
  • Question the user if the mission is unclearin 7 of 545
  • Gather primary sources onlyin 7 of 545, across 4 files

Said here and by no other author read

  • Read existing skills from the repository
  • Scan the current codebase in parallel
  • Diff found topics against existing knowledge
  • Present a ranked list of candidates
  • Ask the user which items to save
  • Confirm each item individually before pushing

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

Keep looking

Skills are one crate of 325,949. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.