ceo-feedback-iteration
Skill0 starsChanged 2 months agoMITView on GitHub
Use when an Agent is asked to classify and improve open repository feedback through the managed feedback-iteration capability. The Skill owns the bounded diagnosis and decision protocol; the service owns capability state, persistence, and lifecycle transitions.
In this repository42 other files it gives its agents.
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The file
We split this skill into the rules it gives an agent
7 rules. About 0 are common, 3 are distinctive, and 4 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈3
Distinctive · estimate
This author's own choices. Worth a look.
4
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 11
Use only the local Console API at http://127.0.0.1:8765/api/console/feedback.
- Very specific: line 12
Read the batch and every selected detail before changing a Skill, configuration, or code.
- Distinctive: line 22
Use brainstorming only if a material product or policy uncertainty remains.
- Distinctive: line 23
Ask one focused user question at a time, offering alternatives and a recommendation.
- Very specific: line 25
Before any change, persist one typed decision through POST /api/console/feedback/batches/{batch_id}/decisions.
- Very specific: line 29
Use exactly one scope: skill_only when policy/procedure is deficient but data, tool, and route exist.
- Distinctive: line 38
Read back the decision and batch history.
≈ “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
CEO Feedback Iteration
Use only the local Console API at http://127.0.0.1:8765/api/console/feedback.
Read the batch and every selected detail before changing a Skill, configuration,
or code. Treat feedback_key as the stable identity. The supplied persisted
summary, detail references, runtime configuration, loaded revision numbers, and
SHA values are factual context; do not ask a model to regenerate a summary or
invent IDs. Direct SQLite writes are forbidden.
Bounded discussion profile
- Establish the observed behavior and loaded capability facts, then identify the likely root-cause class.
- Use brainstorming only if a material product or policy uncertainty remains. Ask one focused user question at a time, offering alternatives and a recommendation. Do not require discussion when the facts establish the path.
- Before any change, persist one typed decision through
POST /api/console/feedback/batches/{batch_id}/decisions. Include the currentfeedback_keyvalues, persisted references, root cause, acceptance scenario, expected behavior, and verification. - Use exactly one scope:
skill_onlywhen policy/procedure is deficient but data, tool, and route exist;runtime_configwhen a valid capability is incorrectly bound or disabled;codewhen a required capability is missing or defective;mixedonly when both are needed;needs_humanfor missing reusable policy, authorization, or indispensable business facts. - Execute only the persisted path.
needs_humannever resolves feedback.
Verification boundary
Read back the decision and batch history. Record path-specific evidence through
the feedback API; a later resolution must prove the selected path, including
the active runtime/load receipt for Skill or configuration work, or commit and
tests for code work. Never claim a new batch while feedback iteration is
disabled, and never change generic brainstorming to encode this protocol.
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.

