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/ce-riffrec-feedback-analysis

Analyze recorded product feedback into evidence for bugs and requirements. Use when a Riffrec capture or other screen, voice, or notes artifact needs interpretation. Use for Riffrec setup, capture, or sharing help when no recording exists yet.

From plugin
compound-engineering
25k35 skills1 command
Install
$ npx -y skills add everyinc/compound-engineering-plugin --skill ce-riffrec-feedback-analysis --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/ce-riffrec-feedback-analysis

Context preview

The summary Claude sees to decide when to auto-load this skill.

Analyze recorded product feedback into evidence for bugs and requirements. Use when a Riffrec capture or other screen, voice, or notes artifact needs interpretation. Use for Riffrec setup, capture, or sharing help when no recording exists yet.

SKILL.md

ce-riffrec-feedback-analysis.SKILL.md
name: ce-riffrec-feedback-analysis
description: "Analyze recorded product feedback into evidence for bugs and requirements. Use when a Riffrec capture or other screen, voice, or notes artifact needs interpretation. Use for Riffrec setup, capture, or sharing help when no recording exists yet."

Riffrec Feedback Analysis

Turn raw product feedback into structured evidence for downstream agents. This skill is the consumption side of [Riffrec](https://github.com/kieranklaassen/riffrec), a capture tool that records synchronized screen + voice + event sessions and emits a `riffrec-*.zip` bundle.

**Done:**

  • Setup ends with a current capture/share path.
  • Quick analysis ends with one evidence-backed bug report and no durable artifact unless requested.
  • Extensive analysis ends with the complete evidence set and a `ce-brainstorm` handoff unless the user asked for extraction only.
  • A missing input, analyzer failure, or unresolved route ends with an actionable blocker rather than a partial success claim.

Choose the path

Route from the input. Read only the references named for that route; do not load the other path references.

  • **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/analyzer.md`, then `references/quick-bug-report.md`.
  • **Extensive analysis** — input is longer, contains multiple issues, requirements, or a workflow walkthrough, or the user wants requirements material. Read `references/analyzer.md`, then `references/extensive-analysis.md`. Continue into `ce-brainstorm` unless the user explicitly asked only to extract or analyze artifacts.

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/` or `frames/` 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.

The Compound Engineering output format used by the extensive path is documented in `references/compound-engineering-feedback-format.md`.

Read more
Ships withcompound-engineering

AI skills that make each unit of engineering work easier than the last. Compound Engineering is a plugin of 35 skills for AI coding agents.

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Repo: everyinc/compound-engineering-plugin

Other skills on compound-engineering.