issue-control-loop
Skill0 starsChanged 4 months agoMITView on GitHub
Turn a GitHub Issue into a clean human-agent control loop with canonical issue state, deterministic PRD intake, explicit machine markers, and clear handoff points. Use when GitHub should be the durable control surface instead of chat alone.
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The file
We split this skill into the rules it gives an agent
3 rules. About 0 are common, 2 are distinctive, and 1 is very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈2
Distinctive · estimate
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 10
Do not use when: the task is tiny local work that would become slower with issue overhead.
- Very specific: line 19
Use the narrower CLI primitives when needed after that, such as issue-control-loop prd --markdown-file /absolute/path/to/prd.md --format …
- Distinctive: line 20
Keep the issue body human-readable and machine state explicit in marker comments or other deterministic structure.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Issue Control Loop
Metadata
- Trigger when: the work deserves an issue-centric control loop, PRD intake, or explicit human-agent handoff state.
- Do not use when: the task is tiny local work that would become slower with issue overhead.
Skill Purpose
Make the issue the durable task surface so humans and agents can coordinate from explicit state instead of reconstructing intent from chat.
Instructions
- Decide first whether the work is substantial enough for an issue-centric loop. If not, keep it lighter and stop there.
- Use
issue-control-loop sequencefirst when the real question is "what should happen after what." Feed it either a PRD markdown file or raw task text so it can pick the right execution surface and ordered workflow. Use--emit artifactswhen you want ready-to-use plan/status/test-plan and issue markdown skeletons in the same output. Use--write-artifactswhen you want those scaffolds written into the workspace immediately. - Use the narrower CLI primitives when needed after that, such as
issue-control-loop prd --markdown-file /absolute/path/to/prd.md --format markdownorissue-control-loop shape --text "Task description here" --format markdown. - Keep the issue body human-readable and machine state explicit in marker comments or other deterministic structure. Treat Projects as the workflow lens, not as the only source of truth. If another skill should take over next, name it explicitly with a one-line reason.
Non-Negotiable Acceptance Criteria
- One canonical issue beats scattered state across chat and boards.
- Machine-readable state must be explicit, not implied.
- Tiny work stays light; this skill does not exist to add ceremony.
- The final issue state names the next handoff point clearly enough for another human or agent run to continue.
Output
- Ordered execution sequence when the lane or next artifact is still unclear.
- Issue-first execution surface for substantial work when GitHub is available.
- Issue-ready markdown or updated issue state with explicit machine markers.
- The command or workflow used to generate that state.
- A short note on the next human or agent handoff step.
Next skill options(only if needed):$work-shaping— decide how much process the issue deserves;$spec-bundle— add contracts/schema/test artifacts when the issue is too soft;$justdoit— turn the issue into live plan/status/test-plan files.
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
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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.

