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discovery-research-synthesis

Turning research artifacts into actionable PM insight. Customer interviews, user research notes, support ticket reviews, sales call transcripts, survey data, in-app feedback, all synthesized into the decisions they are meant to inform. The discipline of moving from raw discovery data to clear product direction without losing signal in the synthesis or fabricating insight that was not actually there. Triggers on research synthesis, customer interview synthesis, user research analysis, discovery readout, research insights, sales call analysis, support ticket analysis, qualitative data analysis. Also triggers when a team has done research but cannot turn it into decisions, when synthesis is producing pretty decks but no roadmap movement, or when an upcoming PM decision needs to be grounded in research already conducted.

74

Quality

Does it follow best practices?

Impact

No eval scenarios have been run

SecuritybySnyk

Passed

No known issues

SKILL.md
Quality
Evals
Security

Quality

Content

85%

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

A high-quality instruction skill body: actionable, clearly sequenced with validation feedback loops, and exemplary progressive disclosure with real, one-level-deep reference files. The only ding is mild verbosity in the closing/summary passages.

Suggestions

Trim the 'Closing' section and the repeated keystone framing, which restate points already established in earlier sections, to tighten token efficiency.

Consider folding the consolidated 'Reference files' list into the in-section 'Detail in' pointers to avoid listing the same nine files twice.

DimensionReasoningScore

Conciseness

The body is well-written and lean for an instruction skill, but it is lengthy (~250 lines) and the closing section plus some repeated framing restates points already made, adding tokens that a senior PM audience may not need.

2 / 3

Actionability

It provides concrete, specific guidance — a six-stage sequence with named stage outputs, falsifiable implication examples, pattern-name contrasts ('Onboarding configuration friction' vs 'users had trouble'), and a 12-consideration checklist — giving copy-paste-ready instruction for an instruction-only skill.

3 / 3

Workflow Clarity

The synthesis sequence is a clearly sequenced six-step process (transcribe → tag → cluster → name → imply → so-what) with an explicit review/validation loop section and validation checkpoints before publishing, matching the explicit-checkpoints anchor.

3 / 3

Progressive Disclosure

SKILL.md is an overview with nine well-signaled, one-level-deep references (each section ends with 'Detail in [references/...md]'), all of which are real files present in ./references/, and a consolidated reference-files list with descriptions — appropriate content split with easy navigation.

3 / 3

Total

11

/

12

Passed

Description

100%

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, specific description with concrete inputs, rich natural trigger terms, explicit when-guidance, and clear differentiation from sibling skills. It uses appropriate third-person voice throughout.

DimensionReasoningScore

Specificity

The description lists many concrete synthesis inputs (customer interviews, support ticket reviews, sales call transcripts, survey data, in-app feedback) and the concrete action of moving from raw discovery data to clear product direction. This matches the 'lists multiple specific concrete actions' anchor.

3 / 3

Completeness

It answers both 'what' (synthesizing research artifacts into actionable PM insight) and 'when' explicitly with a 'Triggers on...' clause and additional situational triggers ('Also triggers when...'), satisfying the explicit-triggers anchor.

3 / 3

Trigger Term Quality

It provides extensive natural trigger terms users would say ('research synthesis, customer interview synthesis, user research analysis, discovery readout, research insights, sales call analysis'), plus diagnostic situational triggers, giving good coverage of natural phrasings.

3 / 3

Distinctiveness Conflict Risk

It carves a clear niche (one-off discovery research synthesis) and explicitly distinguishes it from adjacent skills via 'Different from `user-feedback-aggregation`... different from `jtbd-framing`', making conflict unlikely.

3 / 3

Total

12

/

12

Passed

Validation

93%

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

Validation15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

15

/

16

Passed

Repository
rampstackco/claude-skills
Reviewed

Table of Contents

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