Learn
Skill25 starsChanged 7 days agoMITView on GitHub
Capture structured learning notes in the vault with relevance and reconsideration triggers. Use when reading a repo, watching a talk, or learning a tool.
195 other projects use a version of this.
Adopted by
Most recently taken up by
- Doist/todoist-aitheir own version, first seen Nov 9, 2026
- Doist/todoist-clitheir own version, first seen Nov 8, 2026
- HughYau/AcademicForgetheir own version, first seen Nov 8, 2026
- dimsedra/skillstheir own version, first seen Nov 8, 2026
- rajanrx/skillstheir own version, first seen Nov 8, 2026
- edwinidrus/dragonhoardtheir own version, first seen Nov 8, 2026
Used with
Projects with it also use add-anydoc, add-clidash and 10 more.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
TomGranotSkilladd-anydoc
Add local office-document-to-Markdown conversion to NanoClaw agent containers with the pinned Firecrawl AnyDoc CLI. Use when agents need to read attached Word, PowerPoint, Excel, OpenDocument, RTF, EPUB, CSV, or text-based PDF files without uploading them to a hosted parser.
Also in 5 projects that use this
TomGranotSkilladd-clidash
Add clidash — a zero-dependency, read-only web dashboard that derives its tabs and tables at runtime from any CLI that lists resources as JSON. Ships pre-wired for NanoClaw's ncl CLI (agent groups, sessions, channels, users, roles), plus message-activity charts, a log tail, and a read-only file viewer for group skills/CLAUDE.md/profiles.
Also in 5 projects that use this
seek888Skillopen-gstack-browser
Launch GStack Browser — AI-controlled Chromium with the sidebar extension baked in. Opens a visible browser window where you can watch every action in real time. The sidebar shows a live activity feed and chat. Anti-bot stealth built in. Use when asked to "open gstack browser", "launch browser", "connect chrome", "open chrome", "real browser", "launch chrome", "side panel", or "control my browser". Voice triggers (speech-to-text aliases): "show me the browser".
Also in 11 projects that use this
Saqlain-811Skillios-sync
Regenerate the iOS debug bridge against the latest upstream gstack templates. (gstack)
Also in 6 projects that use this
MicrosoftSkilladd-codex
Use Codex (CLI + AppServer) as the full agent provider — planning, tool orchestration, native compaction, MCP tools, session resume — in place of the Claude Agent SDK. ChatGPT subscription or OPENAI_API_KEY. Per-group via agent_provider. Distinct from using OpenAI as an MCP tool (where Claude remains the planner).
Also in 6 projects that use this
MicrosoftSkilladd-deltachat
Add DeltaChat channel integration via @deltachat/stdio-rpc-server. Native adapter — no Chat SDK bridge. Email-based messaging with end-to-end encryption.
Also in 6 projects that use this
- +5 more from TomGranot
- +1 more from microsoft
Other versions195 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 195
- garrytan/gstack★ 141ksame name
- rohitg00/ai-engineering-from-scratch★ 78ksame name
- gavrielc/nanoclaw★ 31ksame name
- nanocoai/nanoclaw★ 31ksame name
- qwibitai/nanoclaw★ 31ksame name
- tigerless-labs/autoharness★ 11ksame name
- tw93/claude-health★ 7.5ksame name
- tw93/Waza★ 7.5ksame name
- nykooi1/vibe-wise★ 3.5ksame name
- HughYau/AcademicForge★ 2.6ksame name
185 more not listed
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 repository71 other files it gives its agents.
- CLAUDE.mdCLAUDE.md
- docs/llms.txtllms.txt
- llms.txtllms.txt
- agent-fitnessSkill
- body-checkSkill
- briefSkill
- capsule-compactSkill
- closeSkill
- codex-adapterSkill
- cognitive-updateSkill
- comms-summarizeSkill
- compact-noteSkill
- context-capsuleSkill
- context-hygieneSkill
- critique-planSkill
- decideSkill
- deep-reconSkill
- DiagnoseSkill
- digestSkill
- dreamSkill
- EnvelopeSkill
- find-weaknessSkill
- First 10 MovesSkill
- first-winSkill
- frontend-slidesSkill
- Honesty CheckSkill
- humanize-docsSkill
- impeccableSkill
- learn-from-failureSkill
- memory-bridgeSkill
- meta-improveSkill
- meta-improve-vaultSkill
- nightly-close-paritySkill
- nightly-ledger-captureSkill
- nightlySkill
- openSkill
- operator-setupSkill
- orientSkill
- pauseSkill
- ponytailSkill
- port-specSkill
- PromoteSkill
- reconcileSkill
- research-deepSkill
- resumeSkill
- Sandbox RoutingSkill
- scout-vaultSkill
- Self-ReviewSkill
- semantic-searchSkill
- setupSkill
- ship-adapterSkill
- Skill AuditSkill
- skill-huntSkill
- skill-recallSkill
- solution-huntSkill
- sprite-specSkill
- startSkill
- statusSkill
- StuckSkill
- supersedeSkill
- The first 60 shown.
The file
We split this skill into the rules it gives an agent
5 rules. 0 are common, 5 are distinctive, and 0 are very specific to this project.
0
Common
Most of the 170 edited versions we read keep these.
5
Distinctive
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 15
After any session where the input was *learning*, not *doing*
- Distinctive: line 16
Use on prompts like: "/learn", "I just read", "evaluating", "looked into", "should I use", "what did we decide about", "captured this", …
- Distinctive: line 27
If any field is missing, ask one focused question to get it.
- Distinctive: line 40
If it doesn't fit cleanly on the stack, it's either a doctrine concept (note that explicitly) or an artifact-of-AI-trends category (e.g., …
- Distinctive: line 118
Not knowing whether a tool was rejected or just unread
“Common” is measured: kept by at least 6 in 10 of the 170 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Learn
The learning compounding skill. Most principals lose the value of a learning sweep within 48 hours — they read three repos, watch one talk, evaluate two tools, and a week later can't remember what they decided about any of them. /learn captures the structured outcome of every such sweep.
When to use
- The principal has just read a repo, paper, talk, or tool description
- The principal is evaluating something but doesn't have an immediate need
- The principal asks "should I be using X?" or "what did we decide about Y?"
- After any session where the input was learning, not doing
- Use on prompts like: "/learn", "I just read", "evaluating", "looked into", "should I use", "what did we decide about", "captured this", "interesting tool", "considered tool"
How to execute
Step 1 — Take the input
The principal provides:
- Subject: the thing being evaluated (tool, technique, concept, repo, paper, idea)
- Source: where it came from (URL, talk title, conversation, repo name)
- Snapshot: 2-5 sentences on what the thing is and what it claims to do
If any field is missing, ask one focused question to get it.
Step 2 — Locate it on the modern AI stack
Reference [[Modern AI Infrastructure Stack]]. Place the subject at the right layer:
- Application
- Persistence
- Messaging
- Isolation
- Compute
- Observability
- Orchestration
If it doesn't fit cleanly on the stack, it's either a doctrine concept (note that explicitly) or an artifact-of-AI-trends category (e.g., "agent framework", "prompt-engineering pattern").
Step 3 — Assess relevance
Three categories:
- ADOPT — fits an actual current bottleneck. Action follows.
- HOLD — could fit in a future state, but no current bottleneck. Capture the trigger condition.
- REJECT — wrong category, wrong scale, or violates a load-bearing constraint. Capture the reasoning.
- MONITOR — interesting but no clear path. Re-evaluate next quarter.
Step 4 — Capture reconsideration triggers (for HOLD only)
What specific change in circumstances would flip the decision?
- "When the framework starts spawning >10 parallel agents, reconsider isolation tools."
- "When a downstream user can't sandbox safely, reconsider authority gates."
- "When the principal hits the 10K-note vault size, reconsider semantic search alternatives."
The trigger has to be observable. "When we have more time" isn't a trigger. "When DECISION_OUTCOMES.md shows 5+ failed Authority Level 1 actions in a quarter" is.
Step 5 — Write the note
File: vault/concepts/learning/<subject-slug>.md
Format:
---
title: {Subject}
tags:
- learning
- {category}
status: ADOPT | HOLD | REJECT | MONITOR
stack-layer: {layer or N/A}
created: YYYY-MM-DD
last-reviewed: YYYY-MM-DD
source: {URL or reference}
---
# {Subject}
## What it is
{2-5 sentences from the input}
## Stack location
{One paragraph on where it sits in the modern AI stack and what category it competes in}
## Verdict
**{ADOPT | HOLD | REJECT | MONITOR}**
{1-3 sentences on the reasoning}
## Reconsider when
{Trigger condition, only for HOLD; for REJECT, "Never (fundamental rejection)"; for ADOPT, this becomes "Adopted on YYYY-MM-DD; re-evaluate annually"; for MONITOR, "Re-evaluate next quarter"}
## Connects to
{Wikilinks to related vault notes — other tools in the same category, doctrine that applies, relevant projects}Step 6 — Update the index
Append a one-line entry to vault/concepts/learning/INDEX.md:
- [[{subject-slug}]] — {category} — {ADOPT|HOLD|REJECT|MONITOR} — {YYYY-MM-DD}The INDEX.md is the principal's external memory of considered tools. When they hit a real problem and need to remember "did I look at X?", the index answers in one read.
Anti-patterns this prevents
- Learning sweeps that produce no captured artifact, then are forgotten
- Re-evaluating the same tool from scratch six months later
- Not knowing whether a tool was rejected or just unread
- Reconsider triggers that exist in the principal's head but aren't written down (so they never fire)
- Adopting a tool because it's "cool" without locating it on the stack or assessing fit
Connects to
- [[Modern AI Infrastructure Stack]] — the layer map used for placement
- [[What I Am Not Building]] — REJECT entries from
/learngraduate here when worth permanent doctrine - [[Bio-hacking Posture]] —
/learnis the supplements-and-restriction-evaluation skill vault/concepts/learning/INDEX.md— the running index this skill maintains
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
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- It worked
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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.

