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.

Quality

84%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide

Securityby

Low

Low-risk findings worth noting

Quality

Content

92%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A well-architected skill body: concise routing overview, explicit completion criteria, validation and escalation feedback loops, and clean progressive disclosure into real reference files. The only minor gap is that executable specifics are delegated to references rather than shown inline.

Dimension	Reasoning	Score
Conciseness	Lean body with no over-explanation of concepts Claude already knows; every section (Done, routing, common rules) earns its place and assumes Claude's competence.	5 / 5
Actionability	Provides concrete routing rules, named reference files per path, and explicit outcomes, with executable detail delegated to references; minor executable specifics live one level down rather than inline.	4 / 5
Workflow Clarity	Clear multi-step routing sequence, explicit 'Done' completion criteria per path, and validation/blocker handling plus an escalation feedback loop (quick path escalating to extensive) match the top anchor.	5 / 5
Progressive Disclosure	Overview routes to one-level-deep references that all exist as real bundle files (analyzer.md, quick-bug-report.md, extensive-analysis.md, install-riffrec.md, compound-engineering-feedback-format.md), each clearly signaled per path.	5 / 5
	Total	19 / 20 Passed

Description

76%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A focused, well-structured description that answers both what it does and when to use it with explicit trigger clauses. It could enumerate more distinct concrete actions to lift specificity, but trigger coverage and distinctiveness are strong.

Suggestions

List a few more concrete actions (e.g., transcribe, extract screenshots, map issues to source) to raise specificity beyond a single analyze-into-evidence verb.

Add common user-facing synonyms like 'review', 'transcribe', or 'walkthrough' to broaden natural trigger coverage.

Dimension	Reasoning	Score
Specificity	Names the domain and one concrete action ('Analyze recorded product feedback into evidence for bugs and requirements') but does not enumerate multiple distinct actions, matching the 'domain plus 1-2 concrete actions, not comprehensive' anchor.	3 / 5
Completeness	Clearly states what it does ('Analyze recorded product feedback into evidence for bugs and requirements') and gives two explicit 'Use when/Use for' clauses with concrete triggers, matching the top anchor.	5 / 5
Trigger Term Quality	Covers natural terms like 'Riffrec capture', 'screen, voice, or notes artifact', 'recording', and 'setup, capture, or sharing', with a few common synonyms missing, fitting the 'good keyword coverage' anchor.	4 / 5
Distinctiveness Conflict Risk	Centered on a distinct niche (Riffrec captures) with specific artifact types, making overlap with other skills minimal and conflict risk low.	5 / 5
	Total	17 / 20 Passed

Validation

100%

Warnings & errors only

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository: EveryInc/compound-engineering-plugin
Path: skills/ce-riffrec-feedback-analysis/SKILL.md
Commit: 26bf5b1

Reviewed: 4 days ago

Table of Contents

Discovery Implementation Validation

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.