user-feedback-aggregation

Collecting and synthesizing user feedback across channels (support tickets, NPS, in-app feedback, sales calls, social mentions, customer councils) into a continuous signal that informs product decisions. The triage discipline that distinguishes loudest-voice (whoever complains most wins) from averaged-noise (every signal weighted equally) from triaged-synthesis (signal weighted by source quality, frequency, and decision relevance). Triggers on user feedback, customer feedback aggregation, NPS, support ticket analysis, customer councils, feedback synthesis, voice of customer, feedback triage, in-app feedback. Also triggers when feedback channels overflow with volume that does not produce decisions, when the loudest-voice problem is steering roadmap, or when continuous feedback streams need synthesis discipline.

Quality

81%

Does it follow best practices?

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Securityby

Low

Low-risk findings worth noting

Quality

Content

71%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-structured senior-PM playbook with strong progressive disclosure (real, one-level reference files) and concrete frameworks (weighting worked example, frequency-intensity matrix, cadences, failure diagnoses). Its main weakness is redundancy: the framework, closing, and scope sections restate earlier content, lowering token efficiency.

Suggestions

Collapse the '12 considerations' framework section or the closing section — both largely restate the preceding topical sections; keeping one consolidation point would cut significant tokens without losing signal.

Merge 'What this skill is for' with the intro/disambiguation already present in the opening, since the skill distinctions (discovery-research-synthesis, beta-program-management, ux-research) are repeated across both.

Tighten the failure-mode list by cross-referencing the diagonal it maps onto (loudest-voice / averaged-noise / triaged-synthesis) once instead of re-explaining each anti-pattern inline.

Dimension	Reasoning	Score
Conciseness	Mostly efficient domain framing with concrete sections, but the 12-consideration framework, the closing section, and 'What this skill is for' substantially restate points already made earlier, padding the body without adding new signal.	3 / 5
Actionability	Provides concrete, applicable guidance — the channel-source weighting worked example (enterprise admin feature), the frequency-intensity four-quadrant matrix, explicit daily/weekly/monthly/quarterly cadences, and 11 failure-mode diagnoses — though as a conceptual playbook it stops short of fully copy-ready procedures.	4 / 5
Workflow Clarity	The 'From feedback to product decision' loop and cadence ladder give a clear sequenced process, and the litmus test ('can the team explain why specific feedback signals weighted...') acts as an explicit checkpoint; minor gaps in validation formality, but no destructive/batch operation triggers the cap.	4 / 5
Progressive Disclosure	Each topical section closes with a clearly signaled one-level-deep 'Detail in [references/...]' link, all nine referenced files exist, and a consolidated Reference files list aids navigation — an exemplary overview-to-detail split.	5 / 5
	Total	16 / 20 Passed

Description

91%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 strong, explicit description that clearly states both capability and trigger conditions with rich natural-language keywords and a well-defined niche. Slightly conceptual in its action framing rather than enumerating discrete operations, which keeps specificity just short of maximum.

Dimension	Reasoning	Score
Specificity	Names concrete actions ('Collecting and synthesizing user feedback across channels', 'signal weighted by source quality, frequency, and decision relevance') and enumerates six channels, but the actions are domain-discipline framing rather than discrete tool operations, leaving minor coverage gaps versus a fully comprehensive action list.	4 / 5
Completeness	Explicitly answers both what ('Collecting and synthesizing user feedback across channels into a continuous signal that informs product decisions') and when ('Triggers on...', 'Also triggers when feedback channels overflow...') with concrete trigger phrases.	5 / 5
Trigger Term Quality	Comprehensive natural-term coverage including synonyms and variations — 'user feedback, customer feedback aggregation, NPS, support ticket analysis, customer councils, feedback synthesis, voice of customer, feedback triage, in-app feedback' — plus situational triggers a user would naturally voice.	5 / 5
Distinctiveness Conflict Risk	Clear niche (continuous cross-channel feedback aggregation / triage) with distinct trigger vocabulary; minor overlap risk with adjacent research skills whose disambiguation lives in the body rather than the description.	4 / 5
	Total	18 / 20 Passed

Validation

93%

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 — 15 / 16 Passed

Validation for skill structure

Criteria	Description	Result
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	15 / 16 Passed

Repository: rampstackco/claude-skills
Path: skills/user-feedback-aggregation/SKILL.md
Commit: 0479242

Reviewed: 6 days ago

Table of Contents

Discovery Implementation Validation

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