Riffrec Feedback Analysis
SkillMediaAnalyze Riffrec feedback captures from bundles or standalone recordings. Always load for `riffrec-*.zip`, `session.json` + `events.json` + `recording.webm` + `voice.webm` bundles, `.mp4`/`.mov`/`.webm` videos, `.m4a`/`.mp3`/`.wav` audio, or capture/share requests.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Riffrec Feedback Analysis skill
What this skill tells your AI
The instructions your AI receives, as published by nota-america/forgecat-agent-profiles in profiles/everyinc/compound-engineering-plugin/for-forgecat/skills/ce-riffrec-feedback-analysis/SKILL.md and read by ahel’s review.
Turn raw product feedback into structured evidence for downstream agents. This skill is the consumption side of Riffrec, a capture tool that records synchronized screen + voice + event sessions and emits a riffrec-*.zip bundle.
Choose the path
Route to the matching reference based on the input. Read only that reference; do not load the others.
- Setup — user has no recording yet and asks how to install Riffrec, capture a session, or share feedback. Read
references/install-riffrec.md. - Quick bug report — input is a short recording (under ~60 seconds), the user describes a single specific issue, or asks for "quick", "small", or "just transcribe". Read
references/quick-bug-report.md. Emit one concise bug report; skip the full artifact set and brainstorm handoff. - Extensive analysis — input is a longer recording, contains multiple issues / requirements / workflow walkthroughs, or the user wants requirements or brainstorm material. Read
references/extensive-analysis.md. Always continue into thece-brainstormskill.
When the input is ambiguous (e.g., a zip arrived without context), inspect the recording length and event count before choosing. If still unclear, ask the user which path applies before running anything heavy.
Common rules
- Keep raw recordings, audio chunks, zip contents, session dumps, and extracted screenshots local-only by default. Do not commit
raw/orframes/directories unless the user explicitly asks and privacy is acceptable. - Text/metadata artifacts (requirements kickoff material, analysis summaries, problem analyses, source manifests) may be committed when they are needed for traceability and contain no sensitive data.
- Use repo-relative screenshot paths in any committed doc so later agents can open the evidence without absolute local paths.
Analyzer entrypoint
All non-setup paths share the same analyzer, which ships in this skill's scripts/ directory. The Bash tool's working directory is the user's project, not the skill directory, so a bare scripts/<name> path will not resolve. Invoke it by the skill's own absolute path: set SKILL_DIR to the directory you loaded this ce-riffrec-feedback-analysis SKILL.md from, in the same command (shell state does not persist between Bash calls):
SKILL_DIR="<absolute path of the directory containing this SKILL.md>"
python "$SKILL_DIR/scripts/analyze_riffrec_zip.py" /path/to/input
Accepted inputs: a Riffrec .zip, an .mp4 / .mov / .webm video, an .m4a / .mp3 / .wav audio file, or a meeting-notes .md. Use --output-dir <dir> to control where artifacts land. In repos with docs/brainstorms/, the default remains docs/brainstorms/riffrec-feedback/ as a documented evidence/kickoff-artifact exception; it is not the durable ce-brainstorm output convention. The quick path overrides the output dir to a temp location so nothing pollutes the repo.
The Compound Engineering output format used by the extensive path is documented in references/compound-engineering-feedback-format.md.
Signals
- GitHub stars
- 67
- Forks
- 4
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Gateway key
ce-riffrec-feedback-analysis-nota-america- Source
- github.com/nota-america/forgecat-agent-profiles