| name | skill-feedback |
| description | Capture ad-hoc feedback about any skill for the decision trace system. |
| disable-model-invocation | true |
| allowed-tools | Read, Write, Bash |
| argument-hint | <skill-name> "<feedback text>" |
Skill Feedback — Ad-Hoc Trace Capture
Purpose
Record feedback about any skill's behavior as a decision trace. This feeds the short loop (skill reads its own traces on future runs) and the long loop (/skill-improve analyzes accumulated traces to propose skill mutations).
Use this when you have feedback that doesn't correspond to a specific gate interaction — general impressions, workflow complaints, meta-observations, or suggestions.
Template paths are resolved from ${AGENTS_SKILLS_ROOT}/skill-feedback/.
Follow the Harnessy policy in .jarvis/context/docs/standards/skill-feedback-protocol.md when deciding whether feedback must be captured and which skill should receive the trace. The short rule is: capture reusable skill lessons, not empty retrospectives.
Inputs
skill-name — the skill to attach feedback to
feedback text — free-text description of the issue, suggestion, or observation
Steps
- Parse arguments: extract skill name and feedback text from
$ARGUMENTS.
- Validate skill exists: check that
${AGENTS_SKILLS_ROOT}/<skill-name>/ or ~/.agents/skills/<skill-name>/ exists. If not, report the error and list similar skill names.
- Attach the trace to the skill that should change. Do not attach routine feedback to
skill-feedback unless the recorder itself failed.
- Capture the trace:
python3 "${AGENTS_SKILLS_ROOT}/_shared/trace_capture.py" capture \
--skill "<skill-name>" \
--gate "ad_hoc" \
--gate-type "retrospective" \
--outcome "approved" \
--feedback "<feedback text>"
- Confirm: report that the feedback was recorded and the trace file location.
- Suggest: if the skill has 5+ traces with refinement loops, suggest running
/skill-improve <skill-name>.
Output
- Confirmation message with trace ID
- Trace file path
- Optional improvement suggestion