Install
$ agentstack add skill-tanishg98-claude-teach-skill-claude-teach-skill ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
The user has asked you to teach them something. This is a stateful request - they intend to learn the topic over multiple sessions.
Session Loop
Every session follows the same loop. Do not skip steps.
On session start:
- Read
MISSION.md,NOTES.md, and scan./learning-records/to load state. - Recall warm-up: if learning records exist, open with 2-3 quick retrieval questions drawn from past records. Pick records in this priority order: records last marked
forgotten, then records never tested, then the longest-untested ones (see the retention tracking section of LEARNING-RECORD-FORMAT.md). Spaced retrieval is the single highest-leverage act in learning; teaching without it produces exposure, not retention. - Based on warm-up performance: if something was forgotten, re-teach it briefly before anything new (and mark the relevant record superseded if the understanding was lost). If recall is solid, proceed to the next lesson in the zone of proximal development.
- Stamp the results: update the frontmatter of every record you tested with today's date, the result, and the streak (format in LEARNING-RECORD-FORMAT.md). This is what makes the next session's warm-up selection computable instead of guesswork.
On session end:
- Write learning records for anything that qualifies (see LEARNING-RECORD-FORMAT.md).
- Promote newly-mastered terms to
GLOSSARY.md. - Jot the next-best lesson candidate in
NOTES.mdunder a## Next upheading, so the following session starts with intent instead of deliberation.
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](./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](./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-.md, where the number increments each time. Use the format in [LEARNING-RECORD-FORMAT.md](./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.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.
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-.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. Default to a light theme, self-contained HTML (no external dependencies), printable.
The lesson should teach ONE THING only. It should be completable very quickly - but give the user a 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.
Every lesson ends with a Recall section: 2-4 retrieval questions covering the lesson's core idea, with answers hidden behind `` elements. These double as the question bank for future session warm-ups.
Make opening a lesson as easy as possible — ideally a single CLI command the user can run to open the HTML file in their browser.
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.
Zone Of Proximal Development
Each lesson, the learner 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
A user may tell you that they already know about that topic. If so, record it in their learning-records.
Acquiring Knowledge & Skills
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, and gives the user a path to acquire more knowledge if they want to go deeper.
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.
Skills
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)
- In-agent quizzes, where you ask the user scenario-based questions about what they've learned
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.
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. Use the format in [GLOSSARY-FORMAT.md](./GLOSSARY-FORMAT.md).
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.
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: tanishg98
- Source: tanishg98/claude-teach-skill
- License: MIT
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.