ask-matt
FreeAsk which skill or flow fits your situation. A router over the skills in this repo.
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Riffrec product-feedback workflow. ALWAYS load when the user posts a `riffrec-*.zip`, a bundle with `session.json` + `events.json` + `recording.webm` + `voice.webm`, a video/audio recording for product feedback, or asks how to capture and share Riffrec sessions. Routes between setup, quick bug report, and extensive analysis.
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See how to installReview the instructions the agent will receive before you install.
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.
Route to the matching reference based on the input. Read only that reference; do not load the others.
references/install-riffrec.md.references/quick-bug-report.md. Emit one concise bug report; skip the full artifact set and brainstorm handoff.references/extensive-analysis.md. Always continue into the ce-brainstorm skill.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.
raw/ or frames/ directories unless the user explicitly asks and privacy is acceptable.All non-setup paths share the same analyzer:
python 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 is docs/brainstorms/riffrec-feedback/. 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.
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Ask which skill or flow fits your situation. A router over the skills in this repo.
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Build applications where agents are first-class citizens. Use this skill when designing autonomous agents, creating MCP tools, implementing self-modifying systems, or building apps where features are outcomes achieved by agents operating in a loop.
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Run comprehensive agent-native architecture review with scored principles
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Explore requirements and approaches through collaborative dialogue before writing a right-sized requirements document and planning implementation. Use for feature ideas, problem framing, when the user says 'let's brainstorm', or when they want to think through options before deciding what to build. Also use when a user describes a vague or ambitious feature request, asks 'what should we build', 'help me think through X', presents a problem with multiple valid solutions, or seems unsure about scope or direction — even if they don't explicitly ask to brainstorm.
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Clean up local branches whose remote tracking branch is gone. Use when the user says "clean up branches", "delete gone branches", "prune local branches", "clean gone", or wants to remove stale local branches that no longer exist on the remote. Also handles removing associated worktrees for branches that have them.
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Structured code review using tiered persona agents, confidence-gated findings, and a merge/dedup pipeline. Use when reviewing code changes before creating a PR.
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