mono
Skill5 starsChanged 6 days agoMITView on GitHub
Entry router: match a task to one of thirteen playbooks (feature, bug-fix, refactoring, perf, research, ship, ...) and run its skill steps as a todo list. Use when the route is unclear.
3 other projects use a version of this.
Adopted by
Most recently taken up by
- hemal08ce094/DesignSkillsSwiftUItheir own version, first seen Nov 8, 2026
- lachinovedhem/standards-mcptheir own version, first seen Oct 11, 2026
- bergside/awesome-design-skillstheir own version, first seen Apr 24, 2026
Other versions3 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 3
- bergside/awesome-design-skills★ 2.9ksame name
- hemal08ce094/DesignSkillsSwiftUI★ 0same name
- lachinovedhem/standards-mcp★ 0same name
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.
The file
We split this skill into the rules it gives an agent
2 rules. 0 are common, 0 are distinctive, and 2 are very specific to this project.
0
Common
Most of the 3 edited versions we read keep these.
0
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
- Very specific: line 11
Ask the user only through the agent's question tool (Claude Code AskUserQuestion, Codex request_user_input, Pi ask_user_question, Gemini …
- Very specific: line 29
Read the matched playbook.
“Common” is measured: kept by at least 6 in 10 of the 3 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
Name the matched playbook first.
Ask the user only through the agent's question tool (Claude Code AskUserQuestion, Codex request_user_input, Pi ask_user_question, Gemini CLI ask_user, omp ask): ≤4 per call, recommended option first and labelled (Recommended); plain text only without one.
| Task | Playbook |
| Build or change behavior | playbooks/feature.md |
| Error, crash, failing test, regression | playbooks/bug-fix.md |
| Restructure code without changing behavior | playbooks/refactoring.md |
| Slow, latency, memory, throughput regression | playbooks/perf.md |
| Decide a design by building throwaway variants | playbooks/prototype.md |
| Question, review, diagnosis; nothing to change | playbooks/investigation.md |
| Web research, read sources, deep dive into a topic | playbooks/research.md |
| "Be ambitious", make a task deeper, "what would an expert do" | playbooks/ambition.md |
| Get PRs green, address review comments, "check on PR X" | playbooks/babysit.md |
| Land PRs, release, tag, publish, deploy, "is this worth a release" | playbooks/ship.md |
| Resume, "where was I", an active plan exists | playbooks/session-pickup.md |
| Learn from recent sessions, retrospective | playbooks/retro.md |
| Run several sub-agents in parallel, swarm, orchestrate | playbooks/fanout.md |
Read the matched playbook. Open a todo list whose first items are its steps copied verbatim, in order. A step you choose not to do stays in the list as skip: <reason>; never drop it silently. No playbook fits → say so and ask which one applies.
Each step names a skill; that skill owns the procedure. Resolve it through the host's skill metadata. If a required skill is unavailable, report the missing dependency and stop.
Gated skill — retro — runs only from a playbook step here or when the user names it.
Defer to: the skill each playbook step names; git only on the owner's explicit request.
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.