Loop/Prompt Library / Running AI agents well
🔁 Agent workspace health check
Reads a project's notes and state, without changing anything, and grades whether a new agent could safely pick up the work.
Use it when: You are about to restart long-running agent work and are not sure what state it is in.
🛑 Stops when: A green, yellow, or red grade with evidence and one safe next step.
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Do a read-only health check on [repo or workspace]. Do not edit anything. Check: where the source of truth is, the last accepted state, branch safety, how fresh the handoff notes are, stale files, mismatches between preview and live, the health of the agent instruction files, and open items. Grade it green, yellow, or red with evidence. Do one pass only. Finish with the grade, evidence, stale items, risks, and one safe next action.
Review every change the agent makes before you keep it. Set a budget or round limit — the prompt includes one.
Idea from Forward Future's Loop Library · by Shinichi Nagata (@DecisionOS). Prompt rewritten in plain English by FixKit AI.
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Stop and check before continuing
After an agent finishes a task, it reports what is done and whether the next step is safe, then waits for you.
Clean handoff note
Before a session ends, writes a note so the next person or agent can continue without guessing.
Predict, act, check
Before every meaningful action, the agent writes what it expects to happen, then checks if that is what really happened.
Lessons that stick
Keeps a playbook of lessons from repeated runs, tests one lesson at a time, and only keeps lessons that keep working.
Fair-test experiments
Improves a prompt or piece of code through saved, fairly compared experiments that can pick up again later.
Champion vs challenger
Keeps the current best prompt as champion, and a new version only replaces it if it wins on fresh test cases it never saw.