feedback

name	feedback
description	Use this skill when reviewing how the plugin behaved across recent runs, after a release to confirm reliability, before filing a plugin bug report, or when planning the next plugin improvement cycle — to collect and analyze past Claude Code session logs for the ai-skills plugin and surface agent, subagent, skill, command, and hook errors, timeouts, unexpected exits, and other anomalies that point at plugin defects. Defaults to the last 7 days of sessions for the current project. Produces an extended Markdown report on disk plus a brief on-screen summary.
context	fork
argument-hint	[--days N] [--project PATH] [--plugin NAME] [--out PATH] [--severity all|warn|error]

/feedback — Plugin Session Feedback Analyzer

Mine Claude Code session JSONL transcripts for evidence of how the ai-skills plugin behaved across recent sessions. Produces:

1. An extended report saved to disk at a deterministic path.
2. A brief on-screen report following the same template skeleton so users can scan it in the terminal.
3. The on-disk path is the last line of the brief so the user can jump to the full document.

Both reports share section headings (Executive Summary → Findings → Evidence → Recommendations). The brief truncates each section; the file holds the full evidence with timestamps, session IDs, and verbatim excerpts.

When to use

• Post-release reliability check ("did the new hooks misbehave on real sessions?")
• Triage before filing a plugin bug ("show me every place subagent-depth-guard exit-2 fired this week")
• Skill quality review ("which user-invocable skills failed silently in the last 7 days?")
• Planning next improvement cycle ("which 3 problems hit me most often?")
• Auditing a specific subagent or hook by name

Not for:

• Live tail of an active session (use the Claude Code transcript pane)
• Project-code bugs unrelated to the plugin (use /bugfix)
• Test-suite analysis (use /qa / /eval)

Invocation

/feedback                                   # last 7 days, current project, plugin = ai-skills
/feedback --days 14                         # last 14 days
/feedback --project /path/to/other/repo     # analyze a different project's sessions
/feedback --plugin ai-skills                # restrict findings to one plugin (default: ai-skills)
/feedback --severity error                  # only blocking/error-level findings
/feedback --out reports/feedback-2026-05.md # custom output path

Arguments

Flag	Default	Effect
--days N	7	Window of recent sessions to scan (mtime-based). 0 means "all sessions".
--project PATH	current $PWD	Project whose session logs to read. Resolved to ~/.claude/projects/<sanitized-path>/.
--plugin NAME	ai-skills	Filter findings to events that mention this plugin name in hook paths, skill paths, or system events. all disables the filter.
--severity LEVEL	warn	One of all, warn, error. warn is the default — includes errors plus non-blocking warnings.
--out PATH	.ai-skills-memory/feedback/feedback-<YYYY-MM-DD>-<HHMM>.md	Override the on-disk report path. Parent dir is created if missing.
--max-sessions N	100	Cap on number of session files parsed (oldest first; newest always included).

Behavior

1. Resolve the session log directory

Translate --project (or $PWD) to the Claude Code log path:

~/.claude/projects/<sanitized-cwd>/<session-id>.jsonl

<sanitized-cwd> is the absolute project path with / replaced by - and a leading -. Example: /home/u/repo/ai-skills → -home-u-repo-ai-skills. If the directory does not exist, fail with a clear message and suggest --project.

2. Filter session files by recency

List *.jsonl files; keep those with mtime >= now - days (or all if --days 0). Sort newest first; truncate to --max-sessions. Record the resolved window and file count in the report header.

3–6. Parse · attribute · group · render

Steps 3 (stream-parse + event classifier), 4 (per-finding attribution fields), 5 (3-level grouping + signature collapse), 6 (render extended + brief), and 6a (paired canonical JSON parity contract) carry the precise classification rules, attribution schema, and the MD↔JSON parity invariant. Read report-pipeline.md and apply steps 3–6a verbatim before parsing — those rules are mandatory. In short: stream-parse each .jsonl line and classify into hook/tool/assistant/subagent/permission/plugin events; attribute each with session/source/severity/excerpt; group by source-kind → identity → normalized failure signature; render the extended (file) + brief (stdout) reports from templates/extended-template.md; and write a schema-conformant paired .json (full parity, atomic write) next to every .md per output-schema.json — the JSON is the canonical contract for /plugin-author fix-feedback.

Classifier v2 (see report-pipeline.md §3a–3c) additionally: matches task-notifications across queue-operation/attachment events (not just user) and adds the killed status; scans team-envelopes/ for silent-idle subagents and interrupted G7 writes — the dominant /develop failure that the transcripts cannot show; and softens the verdict so a single transient upstream-API error (e.g. HTTP 529 overloaded) does not force RED on its own.

Sections in both:

1. Executive Summary — verdict (GREEN/YELLOW/RED), window, sessions analyzed, total findings, top failure signature
2. Scope & Method — --days, project path, plugin filter, file count, classifier version
3. Findings — grouped table: source kind | source | signature | count | severity | first/last seen
4. Evidence — per-group evidence blocks with timestamps and excerpts
5. Sequence / Causal Chain — for the top failure: ordered timeline of related events across sessions to show the lead-up
6. Recommendations — table: finding ref | suggested action | owner (skill / hook / agent file) | estimated effort
7. Open Questions — anything the data alone cannot answer (needs a human follow-up)

7. Memory write

Append one JSON-line summary to .ai-skills-memory/feedback/feedback.log:

{"ts": "<iso>", "days": 7, "project": "<path>", "plugin": "ai-skills", "sessions_scanned": 14, "findings": 23, "verdict": "YELLOW", "report": ".ai-skills-memory/feedback/feedback-2026-05-13-0910.md"}

8. Print the brief

Last line of stdout is always Extended report: <absolute-path-to-on-disk-report>. This is the contract the caller relies on.

Worker script

scripts/collect_session_data.py is the deterministic parser; the skill body always passes --out-json and --report-md-path so the paired .json lands next to the .md. Its full invocation contract and the worker MUST-rules (stream-parse, malformed-line counter, secret-redaction regex, exact CLI form, --stdout canonical vs default aggregation shape) are in report-pipeline.md ("Worker script") — read and follow it verbatim when invoking the worker.

Templates

• templates/extended-template.md — extended on-disk skeleton (used for the saved Markdown document)
• templates/brief-template.md — brief on-screen skeleton (≤ 60 lines)

Both files include placeholders the skill substitutes at render time.

Hard rules

• Read-only — never modify session JSONL files
• Never echo secrets — apply the redaction regex above before printing or writing
• Deterministic output path — when --out is not given, use .ai-skills-memory/feedback/feedback-<YYYY-MM-DD>-<HHMM>.md so re-runs do not overwrite each other
• Paired JSON parity — every MD write MUST be paired with a JSON write at the same stem. If the JSON write fails, surface the error to the user; do not silently leave a MD-only report (downstream /plugin-author fix-feedback would fall back to degraded MD parsing)
• English-only per repo CLAUDE.md
• No absolute user-machine paths in templates — substitute at runtime only
• Last stdout line is the report path — never print anything after it
• Plugin scope only by default — when --plugin ai-skills, exclude events whose source is clearly user-code (e.g., bash commands, project test runs that are not invoked by plugin hooks)

Failure modes

• Session dir missing: report the resolved path, list nearby candidates, suggest --project
• Zero sessions in window: still write a report with verdict INSUFFICIENT_DATA; brief is one line + path
• Malformed JSONL line: count it, continue; surface counter in report header
• Permission denied on .ai-skills-memory/feedback/: fall back to /tmp/feedback-<ts>.md and warn the user that the canonical path was unreachable
• Worker crash: print the worker traceback, exit 1, do NOT print a fake report-path line

Memory writes

Layer	When	Shape
L4	End of every run	Append one JSON line to .ai-skills-memory/feedback/feedback.log — timestamp, window, sessions scanned, finding count, verdict, report path

Integration

• Reads: ~/.claude/projects/<sanitized-cwd>/*.jsonl; <project>/.ai-skills-memory/sessions/*/team-envelopes/*.json (classifier v2 — the team-gate-reconciliation envelopes that surface silent-idle subagents the transcripts cannot show); report-pipeline.md (steps 3–6a + worker contract)
• Writes: paired Markdown + canonical JSON reports at the same stem (e.g. feedback-2026-05-13-0910.{md,json}), plus a one-line summary append to .ai-skills-memory/feedback/feedback.log
• Downstream consumer: /plugin-author fix-feedback --from <report>.json ingests the canonical JSON and produces a fix-cycle (one WP per finding, DEV → REVIEW → QA pipeline) — see plugin/skills/plugin-author/feedback-parser.md for the consumed shape. Markdown reparse via --md is degraded fallback only.
• Companion: /plugin-doctor (live plugin diagnostic), /eval (rubric-based skill quality), /bugfix (file a fix once a finding is confirmed)
• Schema: plugin/skills/feedback/output-schema.json (JSON Schema 2020-12, schema_version: "1"). The worker validates against it implicitly by construction; downstream consumers SHOULD validate via jsonschema when available.
• Hooks: none required; /feedback is read-only and runs in the main thread