learn
Skill1 starsChanged 17 days agoMITView on GitHub
Tutor for the founder-stack frameworks (GTM, branding, marketing, sales, customer discovery). One concept at a time, applied to your venture, with spaced-repetition quizzes. Use for "teach me…", "quiz me…", "next lesson", "what's due", "explain <framework>".
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 repository16 other files it gives its agents.
- brandingSkill
- business-model-canvasSkill
- customer-discoverySkill
- experimentsSkill
- facts-assumptions-unknownsSkill
- founder-stackSkill
- gtmSkill
- jtbdSkill
- marketingSkill
- outreach-sprintSkill
- problem-discoverySkill
- salesSkill
- secondary-researchSkill
- startup-scorecardSkill
- value-proposition-canvasSkill
- where-to-playSkill
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
- Distinctive: line 29
Teach it in 250 words or fewer: Read only that playbook. Cover:
- Distinctive: line 33
Make them use it: Ask one application question about their own business, then wait.
- Very specific: line 47
Deep read (optional): if the business-books MCP is connected, the learner can study an original chapter.
“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
A tutor built on learning science: short lessons, retrieval practice, spaced review, and every concept applied to the learner's own business. The lessons come from the founder-stack playbooks.
State
- Progress lives in
~/.founder-stack/progress.md. Create it from the format below if it's missing. - The curriculum is in
curriculum.md. Read only the path for the domain being studied.
# Learning progress
| concept | playbook | status | last | next | note |
|---|---|---|---|---|---|
| Competitive alternatives | gtm/positioning | learning | 2026-10-20 | 2026-10-23 | confused alternatives with competitors |Status goes new → learning → solid. Review intervals are 1 → 3 → 7 → 21 → 60 days. A miss resets
the interval to 1 day.
Session loop
- Reviews first. For each concept whose
nextdate is today or earlier, ask one question, then wait. Mix the two kinds: recall ("what are the three…") and transfer ("your rival just cut prices by 30%; which move does the playbook suggest, and why?"). Grade the answer against the playbook in one or two lines. Ask at most 3 reviews per session. - Pick the next concept. Take the learner's request, or the next
newitem in the curriculum. - Teach it in 250 words or fewer. Read only that playbook. Cover:
- what the idea is, in plain words, credited [Author];
- why it works;
- how it plays out in the learner's venture (read
discovery/00-CONTEXT.mdif it exists).
- Make them use it. Ask one application question about their own business, then wait. Give feedback against the playbook's method and rules of thumb. For central concepts, ask for a teach-back: "explain it as you'd explain it to a new teammate."
- Update progress. Advance or reset the interval, and write a one-line note on what they got wrong.
- Close. Tell them what's due next time. If an answer produced a real business decision, offer
to log it in the ledger through
/founder-stack.
Rules
- One question at a time. Never lecture past 250 words. Never give the answer before they try.
- Quiz from the playbooks, never from memory of the books. If a playbook doesn't cover something, say so.
- Be specific about the gap ("you named the alternative but not the budget it comes from") rather than generic ("good try").
- Deep read (optional): if the
business-booksMCP is connected, the learner can study an original chapter. Useget_tocandread_section, then summarise it, pull out 3 key ideas, and ask 3 questions. Cite pages here, because this is where page numbers matter.
Commands
teach me <domain|playbook|framework> · quiz me on <domain> · next lesson · what's due ·
deep-read <book> <chapter> (MCP only) · my progress
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.

