teach
Skill1 starsChanged 3 months agoApache-2.0View on GitHub
Teach the user a new skill or concept, within this workspace.
We split this skill into the rules it gives an agent
7 rules. 4 are common, 1 is distinctive, and 2 are very specific to this project.
4
Common
Most of the 131 edited versions we read keep these.
1
Distinctive
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
- Distinctive: line 12
Treat the current directory as a teaching workspace.
- Very specific: line 30
Before the RESOURCES.md is well-populated, your focus should be to find high-quality resources which will help the user acquire knowledge.
- Common: line 55
If possible, open the lesson file for the user by running a CLI command.
- Common: line 73
Every lesson should be tied into the mission - the reason that the user is interested in learning about the topic.
- Very specific: line 75
If the user is unclear about the mission, or the MISSION.md is not populated, your first job should be to question the user on why they …
- Common: line 101
If knowledge is all about acquisition, skills are about durability and flexibility.
- Common: line 116
When the user asks a question that appears to require wisdom, your default posture should be to attempt to answer - but to ultimately …
“Common” is measured: kept by at least 6 in 10 of the 131 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
The user has asked you to teach them something. This is a stateful request - they intend to learn the topic over multiple sessions.
Teaching Workspace
Treat the current directory as a teaching workspace. The state of their learning is captured in this directory in several files:
MISSION.md: A document capturing the reason the user is interested in the topic. This should be used to ground all teaching. Use the format in MISSION-FORMAT.md../reference/*.html: A directory of reference materials. These are the compressed learnings from the lessons - cheat sheets, reference algorithms, syntax, yoga poses, glossaries. They are the raw units of learning. They should be beautiful documents which print out well, and are designed for quick reference.RESOURCES.md: A list of resources which can be explored to ground your teaching in contextual knowledge, or to acquire knowledge and wisdom. Use the format in RESOURCES-FORMAT.md../learning-records/*.md: A directory of learning records, which capture what the user has learned. These are loosely equivalent to architectural decision records in software development - they capture non-obvious lessons and key insights that may need to be revised later, or drive future sessions. These should be used to calculate the zone of proximal development. They are titled0001-<dash-case-name>.md, where the number increments each time. Use the format in LEARNING-RECORD-FORMAT.md../lessons/*.html: A directory of lessons. A lesson is a single, self-contained HTML output that teaches one tightly-scoped thing tied to the mission. This is the primary unit of teaching in this workspace../assets/*: Reusable components shared across lessons. See Assets.NOTES.md: A scratchpad for you to jot down user preferences, or working notes.
Philosophy
To learn at a deep level, the user needs three things:
- Knowledge, captured from high-quality, high-trust resources
- Skills, acquired through highly-relevant interactive lessons devised by you, based on the knowledge
- Wisdom, which comes from interacting with other learners and practitioners
Before the RESOURCES.md is well-populated, your focus should be to find high-quality resources which will help the user acquire knowledge. Never trust your parametric knowledge.
Some topics may require more skills than knowledge. Learning more about theoretical physics might be more knowledge-based. For yoga, more skills-based.
Fluency vs Storage Strength
You should be careful to split between two types of learning:
- Fluency strength: in-the-moment retrieval of knowledge
- Storage strength: long-term retention of knowledge
Fluency can give the user an illusory sense of mastery, but storage strength is the real goal. Try to design lessons which build long-term retention by desirable difficulty:
- Using retrieval practice (recall from memory)
- Spacing (distributing practice over time)
- Interleaving (mixing up different but related topics in practice - for skills practice only)
Lessons
A lesson is the main thing you produce — the unit in which knowledge and skills reach the user. Each lesson is one self-contained HTML file, saved to ./lessons/ and titled 0001-<dash-case-name>.html where the number increments each time.
A lesson should be beautiful — clean, readable typography and layout — since the user will return to these later to review. Think Tufte.
The lesson should be short, and completable very quickly. Learners' working memory is very small, and we need to stay within it. But each lesson should give the user a single tangible win that they can build on. It should be directly tied to the mission, and should be in the user's zone of proximal development.
If possible, open the lesson file for the user by running a CLI command.
Each lesson should link via HTML anchors to other lessons and reference documents.
Each lesson should recommend a primary source for the user to read or watch. This should be the most high-quality, high-trust resource you found on the topic.
Each lesson should contain a reminder to ask followup questions to the agent. The agent is their teacher, and can assist with anything that's unclear.
Assets
Lessons are built from reusable components, stored in ./assets/: stylesheets, quiz widgets, simulators, diagram helpers — anything a second lesson could reuse.
Reuse is the default, not the exception. Before authoring a lesson, read ./assets/ and build from the components already there. When a lesson needs something new and reusable, write it as a component in ./assets/ and link to it — never inline code a future lesson would duplicate.
A shared stylesheet is the first component every workspace earns: every lesson links it, so the lessons look like one consistent course rather than a pile of one-offs. As the workspace grows, so should the component library.
The Mission
Every lesson should be tied into the mission - the reason that the user is interested in learning about the topic.
If the user is unclear about the mission, or the MISSION.md is not populated, your first job should be to question the user on why they want to learn this.
Failing to understand the mission will mean knowledge acquisition is not grounded in real-world goals. Lessons will feel too abstract. You will have no way of judging what the user should do next.
Missions may change as the user develops more skills and knowledge. This is normal - make sure to update the MISSION.md and add a learning record to capture the change. Confirm with the user before changing the mission.
Zone Of Proximal Development
Each lesson, the user should always feel as if they are being challenged 'just enough'.
The user may specify an exact thing they want to learn. If they don't, figure out their zone of proximal development by:
- Reading their
learning-records - Figuring out the right thing to teach them based on their mission
- Teach the most relevant thing that fits in their zone of proximal development
Knowledge
Lessons should be designed around a skill the user is going to learn. The knowledge in the lesson should be only what's required to acquire that skill. You teach the knowledge first, then get the user to practice the skills via an interactive feedback loop.
Knowledge should first be gathered from trusted resources. Use RESOURCES.md to keep track of them. Lessons should be littered with citations - links to external resources to back up any claim made. This increases the trustworthiness of the lesson.
For acquiring knowledge, difficulty is the enemy. It eats working memory you need for understanding.
Skills
If knowledge is all about acquisition, skills are about durability and flexibility. Make the knowledge stick.
For skill acquisition, difficulty is the tool. Effortful retrieval is what builds storage strength. Skills should be taught through interactive lessons. There are several tools at your disposal:
- Interactive lessons, using quizzes and light in-browser tasks
- Lessons which guide the user through a list of real-world steps to take (for instance, yoga poses)
Each of these should be based on a feedback loop, where the user receives feedback on their performance. This feedback loop should be as tight as possible, giving feedback immediately - and ideally automatically.
For quizzes, each answer should be exactly the same number of words (and characters, if possible). Don't give the user any clues about the answer through formatting.
Acquiring Wisdom
Wisdom comes from true real-world interaction - testing your skills outside the learning environment.
When the user asks a question that appears to require wisdom, your default posture should be to attempt to answer - but to ultimately delegate to a community.
A community is a place (online or offline) where the user can test their skills in the real world. This might be a forum, a subreddit, a real-world class (budget permitting) or a local interest group.
You should attempt to find high-reputation communities the user can join. If the user expresses a preference that they don't want to join a community, respect it.
Reference Documents
While creating lessons, you should also create reference documents. Lessons can reference these documents - they are useful for tracking raw units of knowledge useful across lessons.
Lessons will rarely be revisited later - reference documents will be. They should be the compressed essence of the lesson, in a format designed for quick reference.
Some learning topics lend themselves to reference:
- Syntax and code snippets for programming
- Algorithms and flowcharts for processes
- Yoga poses and sequences for yoga
- Exercises and routines for fitness
- Glossaries for any topic with its own nomenclature
Glossaries, in particular, are an essential reference. Once one is created, it should be adhered to in every lesson.
NOTES.md
The user will sometimes express preferences of how they want to be taught, or things you should keep in mind. This is the place to record those preferences, so you can refer back to them when designing lessons or working with the user.
Other versions227 projects use a version of this.
Word for word · 68
- GreyDGL/PentestGPT★ 16k100% same
- bestofjs/bestofjs★ 3.1k100% same
- Tiberriver256/mcp-server-azure-devops★ 397100% same
- ninehills/skills★ 280100% same
- loulanyue/skills★ 231100% same
- scibly-dev/scibly★ 39100% same
- lezli01/vincent★ 28100% same
- ivanrvpereira/.agents★ 18100% same
- julianromli/faiz-skills★ 16100% same
- alp82/curia★ 15100% same
58 more not listed
Edited · 88
- mattpocock/skills★ 303k96% same
- QuivrHQ/quivr★ 40k99% same
- ArcReel/ArcReel★ 5.5k96% same
- withcoral/coral★ 4.9k96% same
- davidondrej/skills★ 4.2k89% same
- CelestoAI/SmolVM★ 1k99% same
- moeru-ai/xsai★ 66499% same
- mxyhi/ok-skills★ 50696% same
- aws/graph-explorer★ 48999% same
- itsmylife44/cliproxyapi-dashboard★ 28196% same
78 more not listed
Wrote their own version · 71
- vinvcn/mattpocock-skills-zh-CN★ 5.3ksame name
- amosblomqvist/learn★ 3.4ksame name
- backnotprop/pstack★ 2.7ksame name
- stevesolun/ctx★ 583same name
- devcxl/mattpocock-skills-zh★ 508same name
- entireio/skills★ 223same name
- vasanthsreeram/Alvarmethod★ 155same name
- alexknowshtml/claude-skills★ 144same name
- uzairansaruzi/p3-stack★ 126same name
- jtaroreh/agystack★ 59same name
61 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.
Used alongsideProjects with it also use make-bot-ui, setup-pstack 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.
Xia-AtaraxiaSkillmake-bot-ui
Builds a small web page whose buttons wake an agent over a webhook: a local server keeps the sender key server-side and POSTs JSON to a webhook-triggered routine, and the page is exposed on the existing Tailscale node. Use for \"make a bot UI\", \"a dashboard with buttons that trigger the agent\", \"wake the bot from a page\", handing a webhook sender key to the server without pasting it in chat, or putting that UI on the tailnet. Not for general frontend work - use principle-frontend; not for tailnet health or reachability - use tailscale.
Also in 16 projects that use this
bnemaSkillsetup-pstack
Configure which Pi models pstack uses per role. Detects available provider/model specs and writes pstack's user configuration. Use for /setup-pstack, "configure pstack models", or changing pstack model choices.
Also in 21 projects that use this
Xia-AtaraxiaSkillbenchmark-checklist
Vets performance measurements for the limiter, tuning, physical limits, errors, repeatability, relevance, and proof that timed work happened. It applies to 'check this benchmark', 'report this speedup', measured regressions, and choosing a library or configuration from numbers. It reports spread and gaps before drawing a conclusion. Not for general testing policy or choosing test oracles - use principle-testing.
Also in 17 projects that use this
ianclearySkillpoteto-help
Guides users through pstack setup, /poteto-mode, and picking the skill, playbook, or principle for a task. Type /poteto-help with a question.
Also in 8 projects that use this
juancamiloqhzSkillprinciple-explain-the-number
Apply before you trust, report, or act on a number you measured: a speedup, a regression, a throughput, a latency, or an eval result. Find what limits it, and rule out that it measured something other than the work you think.
Also in 16 projects that use this
jaydubya818Skillprinciple-never-block-on-the-human
Apply when safe reversible implementation details can proceed inside scope.
Also in 32 projects that use this
In this repository29 other files it gives its agents.
- ask-mattSkill
- codebase-designSkill
- code-reviewSkill
- diagnosing-bugsSkill
- domain-modelingSkill
- grill-with-docsSkill
- implementSkill
- improve-codebase-architectureSkill
- prototypeSkill
- researchSkill
- resolving-merge-conflictsSkill
- setup-matt-pocock-skillsSkill
- tddSkill
- to-issuesSkill
- to-prdSkill
- to-specSkill
- to-ticketsSkill
- triageSkill
- wayfinderSkill
- grillingSkill
- grill-meSkill
- handoffSkill
- writing-great-skillsSkill
- ponytail-auditSkill
- ponytail-debtSkill
- ponytail-gainSkill
- ponytail-helpSkill
- ponytail-reviewSkill
- ponytailSkill
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.

