loop-readiness
Skill1 starsChanged 5 months agoMITView on GitHub
Decision gate run BEFORE building any recurring loop, automation, or scheduled agent. Scores the task against the 4-condition test and 5-point checklist, returns a verdict — build it, keep it manual, or fix a precondition first. Use when asked "should this be a loop?" or before authoring any /loop, /schedule, or routine.
In this repository13 other files it gives its agents.
- adversarial-verifySkill
- closed-loopSkill
- cluster-feedbackSkill
- doubt-gateSkill
- fleet-loopSkill
- hill-climbSkill
- keep-greenSkill
- loop-auditSkill
- loop-stateSkill
- prod-watchSkill
- scaffold-planningSkill
- ship-preflightSkill
- source-groundedSkill
The file
We split this skill into the rules it gives an agent
2 rules. About 0 are common, 1 is distinctive, and 1 is very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈1
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 11
All four must hold:
- Very specific: line 40
Add a state file (see /loop-state).
≈ “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
Loop Readiness
Decide whether a task should become a loop before building one. A loop that misses a condition costs more than it returns — the honest default is "keep it manual."
The 4-condition test (strategic)
All four must hold:
| # | Condition | Fails when |
| 1 | The task repeats — at least weekly | One-time job. A good prompt is faster and cheaper; a loop run once is just a script. |
| 2 | Verification is automated | No test, typecheck, build, or linter can reject bad output. You're back in the chair reading every diff — the job the loop was supposed to remove. |
| 3 | Token budget absorbs the waste | Loops re-read context, retry, explore. On a metered plan the bill arrives before the productivity gain does. |
| 4 | Agent has senior-engineer tools | No logs, no repro environment, can't run the code it writes — the loop iterates blind. |
Miss one → verdict: keep it manual.
The 5-point checklist (tactical, per task)
- Happens at least weekly.
- An objective gate (test, typecheck, build, lint) rejects bad output — a second agent asked to "review" is just a second optimist.
- The agent can run the code it changes.
- A hard stop exists: token budget, iteration count, or time limit. Without one, the loop runs until someone notices the bill.
- A human reviews before merge, deploy, or dependency changes.
Good first loops vs bad
Good: CI failure triage, dependency bump PRs, lint-and-fix passes, flaky test reproduction, issue→PR drafts on well-tested code. (Test: could a junior do it from a checklist, with a test suite catching their mistakes?)
Bad — human stays in the chair: architecture rewrites, auth/payments code, production deploys, vague product work, anything where "done" is a judgment call.
Build order (if verdict is "build")
- Get one manual run reliable.
- Turn it into a skill (SKILL.md).
- Add a state file (see
/loop-state). - Wrap it in a loop with the gate and hard stop.
- Then schedule it.
Skipping ahead is how loops fail in production.
Verdict format
Task: <one line>
4-condition test: <pass | FAIL on #n — reason>
Checklist: <5/5 | which boxes missed>
Verdict: BUILD | KEEP MANUAL | FIX FIRST (<precondition>)
If BUILD — gate: <command> | hard stop: <limit> | cadence: <interval>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.

