agentleFS
Sign inStart free
slogsdonslogsdon/skills-vault-knowledge/skills/learned/SKILL.md

learned

Skill0 starsChanged 3 months agoMITView on GitHub

Turn a vault insight or pattern into polished written content — blog draft, LinkedIn post, newsletter section. Use when /learned is invoked, when the user says "write this up", "turn this into a post", "I want to publish about X", or when a /weekly-learnings session surfaces a publishable thread. Do NOT use for raw note-taking (use /log) or for ghost-writing in someone else's voice (use /ghost).

1 other project uses a version of this.

Adopted by

Most recently taken up by

  • Other versions1 project uses a version of this.

    Word for word · 0

    None found.

    Edited · 0

    None found.

    Wrote their own version · 1

    1. zahidakhyar/skills★ 0same name

    How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.

  • In this repository17 other files it gives its agents.

The file

We split this skill into the rules it gives an agent

5 rules. About 0 are common, 3 are distinctive, and 2 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈3

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 2

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Follow Qwen Protocol with:

    line 15
  2. Distinctive:

    If Qwen is unavailable:

    line 22
  3. Very specific:

    Run obsidian search query='[argument]' limit=10 via bash to find notes related to the topic

    line 24
  4. Very specific:

    Read the top 5–10 most relevant notes by running obsidian read file='[note name]' via bash for each

    line 25
  5. Distinctive:

    Use first-person, direct prose (not listicles unless the content demands it)

    line 28

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Skill: /learned [argument]

Transform vault insights into a polished written piece — blog post, essay, or reflection — in Shane's voice, grounded in specific vault material, not a bullet dump.

Don't: produce a bullet list of insights — write narrative prose. Don't start with the most recent note — lead with the most surprising or hard-won insight. Don't invent grounding: Profiles/voice.md is authoritative for voice and its rule binds here — "The voice is portable. The thinking isn't." If the vault holds no material for a claim, leave [TK: your question] in the draft rather than writing a plausible specific.

Steps

  1. Parse the argument/topic from Shane's request.
  2. Follow Qwen Protocol with:
    • task: "Vault access (bash only, no MCP tools): obsidian search query='TERM' limit=10, obsidian read file='Note Name' (no .md). Transform Shane's vault insights about '[argument]' into a polished written piece — a blog post, essay, or reflection. Use his authentic voice."
    • skill: "learned"
  3. Review Qwen's result, synthesize if needed, and present to Shane.

Fallback

If Qwen is unavailable:

  1. Run obsidian search query='[argument]' limit=10 via bash to find notes related to the topic
  2. Read the top 5–10 most relevant notes by running obsidian read file='[note name]' via bash for each
  3. Extract key insights, observations, and recurring ideas from those notes
  4. Transform them into a polished written piece in Shane's voice:
    • Use first-person, direct prose (not listicles unless the content demands it)
    • Lead with the most surprising or hard-won insight
    • Build a narrative arc: what changed, what was learned, why it matters
    • Land the ending: close with a punch that restates the thesis in compressed form. Do not summarise what was just said, and do not add an open question, a motivational close, or a tagged-on CTA.
  5. Report every [TK] you left, and name which parts came from vault notes versus which you wrote. Never invent the grounding detail.
  6. Present the piece to Shane

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

Check your setup, free