learn
Skill1 starsChanged 2 months agoMITView on GitHub
Learn and understand a concept in depth. Args: <concept>
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 repository17 other files it gives its agents.
- check-drySkill
- check-testsSkill
- create-commit-messageSkill
- create-unit-testsSkill
- deslop-proseSkill
- deslopSkill
- fanout-reviewSkill
- fix-security-auditSkill
- framework-upgrade-guideSkill
- generate-adrSkill
- optimizeSkill
- pr-descriptionSkill
- resolve-merge-conflictsSkill
- security-checkSkill
- ship-itSkill
- takeawaysSkill
- update-claude-mdSkill
The file
We split this skill into the rules it gives an agent
3 rules. 0 are common, 2 are distinctive, and 1 is very specific to this project.
0
Common
Most of the 170 edited versions we read keep these.
2
Distinctive
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 26
If $ARGUMENTS is empty, missing, or whitespace, stop and output:
- Distinctive: line 82
Keep code examples minimal: focus strictly on illustrating the target concept.
- Distinctive: line 83
If the concept is ambiguous, explain the most common usage first and mention the alternative.
“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
<!-- Note: $ARGUMENTS is substituted by Claude commands only. In Copilot,
the user must include their argument inline in the prompt; the skill
body sees the literal text "$ARGUMENTS" unsubstituted. -->Arguments
<concept>
- Required. The concept, term, or technology you want explained in depth.
- Examples:
/learn user story,/learn Wilson score interval,/learn closure in JavaScript
Copilot CLI note:
$ARGUMENTSdoes not substitute in skills; include the argument inline in your prompt.
Explain Concept: $ARGUMENTS
Explain a software development concept, algorithm, tool, or architectural pattern clearly and thoroughly across multiple conceptual depths.
Step 1: Validate Input
If $ARGUMENTS is empty, missing, or whitespace, stop and output:
Usage:
/learn <concept>Please provide the concept, term, or technology you want explained.
Then stop.
Step 2: Adaptive Multi-Depth Explanation
Synthesize the concept across structured levels to ensure both rapid intuition and deep technical mastery:
- Simple Summary (ELI5): Explain the concept in plain, non-jargon language that any developer or stakeholder can grasp immediately.
- Technical Mechanics: Detail how it works under the hood: data flow, memory model, execution phases, or state transitions.
- Mental Model: Provide an intuitive analogy from daily life or foundational computer science.
- Code Example: Provide a concise, runnable, and idiomatic code snippet illustrating the concept in practice.
- Common Pitfalls: Highlight common mistakes, anti-patterns, and performance or security traps.
- Best Practices: State concrete production recommendations and guidelines for when and when not to use it.
- Related Concepts: Connect the topic to 2-3 adjacent concepts, tools, or design patterns.
Output Format
Output using this structured markdown template:
# Learn: <Concept>
## 1. Simple Summary (ELI5)
<Plain language explanation capturing core value>
## 2. Technical Mechanics
<Detailed explanation of underlying architecture, algorithms, and lifecycle>
## 3. Mental Model
<Concrete analogy explaining the concept intuitively>
## 4. Code Example
```<language>
// Minimal, self-contained, and runnable example5. Common Pitfalls
- <Pitfall 1>:
<Why developers make this mistake and how to prevent it> - <Pitfall 2>:
<Why developers make this mistake and how to prevent it>
6. Best Practices
- <Practice 1>:
<Concrete operational recommendation> - <Practice 2>:
<Concrete operational recommendation>
7. Related Concepts
<Concept A>:<How it relates or differs><Concept B>:<How it relates or differs>
## Rules
- Ground explanations in technical reality; avoid marketing buzzwords or hand-waving.
- Keep code examples minimal: focus strictly on illustrating the target concept.
- If the concept is ambiguous, explain the most common usage first and mention the alternative.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
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.

