Skill Manager

Skill Manager

Preserve confirmed agent lessons as concise, durable skill guidance. Follow the active repository and host instructions; this skill does not replace them.

Modes

• log-skill-discovery: inspect execution evidence for repeated behavior, prompt boilerplate, missing guidance, and reusable workflow lessons.
• existing-skill-optimization: inspect a current skill for unnecessary prose, duplicated mechanics, misplaced resources, and context-heavy read paths. Read refactor-placement.md before changing placement.
• new-skill-final-check: after a new skill is drafted and mechanically valid, verify its behavior and side effects before reporting it complete.

Stop at a proposal when the finding belongs to product architecture, backlog shaping, runtime implementation, or another system owner.

Stage contract

• DISCOVERY: inspect and report evidence-backed findings; stop without a gate or edit when no exact candidate is requested.
• CANDIDATE: define one exact bundle and separate mechanical validation, semantic/behavioral gate, and human approval. Gate success is not approval.
• APPLY: edit only after unambiguous approval for that exact bundle.
• FINAL-CHECK: run mechanical checks, then semantic/behavioral validation, then any repository-local governance checks.

Workflow

1. Read the target skill, its direct references, applicable repository instructions, and the evidence that exposed the problem. State missing sources rather than filling them with assumptions.
2. Group findings into a small set of reusable themes. Separate skill guidance from scripts, runtime changes, product work, and one-off local corrections.
3. Prepare one exact candidate bundle with affected paths, evidence, expected impact, risk, and validation.
4. For existing-skill-optimization, run $instruction-validity-gate on the exact candidate before approval or application. Mechanical validation does not replace semantic/behavioral validation or human approval.
5. Propose only an APPLY bundle. Obtain text approval that unambiguously refers to it before editing, unless the current user request already grants that exact authority.
6. Apply only the approved skill changes. Do not create a parallel approval store or silently expand the bundle.
7. For new-skill-final-check, run the system quick_validate.py on the draft, then run $instruction-validity-gate before finalization. After a gate-driven rewrite, rerun both in that order.
8. Rerun the gate when applied text differs materially from the passing candidate. Material changes may alter trigger, scope, authority, workflow, success or stop conditions, dependencies, or observed behavior; formatting and spelling alone are not material.
9. Treat HOLD as unfinished and report missing evidence. For REJECT, make a bounded rewrite within the gate's retry limit or discard the candidate. If the gate cannot be loaded, stop at HOLD; do not copy its protocol here.
10. Run focused validation and every applicable repository governance check. Commit only when the user and repository workflow authorize it.

Placement

Read refactor-placement.md for placement decisions. Keep repository-specific commands, paths, role routing, and service policy in repository instructions or references, not in this global skill.

Validation

Use system skill-creator guidance for skill changes. Validate every changed folder containing SKILL.md with:

cmd /c py -3 -X utf8 C:\Users\sedho\.codex\skills\.system\skill-creator\scripts\quick_validate.py <skill-folder>

quick_validate.py is mechanical validation only; keep semantic/behavioral validation, human approval, and repository-local governance checks separate. For shared references, validate each consuming skill. For executable helpers, run the smallest direct syntax or behavior check. Read agent-guidance-test-policy.md before adding or changing agent-guidance tests.