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market-research

Use when doing upstream market-research methodology — sizing a market as TAM/SAM/SOM computed BOTH top-down and bottoms-up (never a single unsourced number), planning a survey sample size with finite-population correction and per-segment minimums, or scoring candidate market segments against Kotler's measurable/substantial/accessible/differentiable/actionable criteria. Outputs always show the method and the assumptions. For market-research analysts and product-marketing at the sizing/survey/segmentation moment. Distinct from marketing-skill (campaign analytics, attribution, demand-gen) — this is the evidence-building methodology, not live-campaign optimization.

71

Quality

89%

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SKILL.md
Quality
Evals
Security

Quality

Content

82%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 strong, highly actionable skill body: every step names a concrete command, scripts are tabulated with profiles, and methodology discipline (triangulate, power per segment, gate segments) is enforced at each step. The main costs are mild redundancy between the forcing-question library, the 'Distinct from' table, and the references, plus a thin error-recovery path for failed triangulation.

Suggestions

Move the forcing-question library's per-question 'Recommended' and 'Canon' lines into a new reference file (e.g. references/grill_questions.md), keeping only the five question stems inline to cut duplication with the References section.

Add one concrete recovery step to the Workflow for failed triangulation (e.g. 'if tam_divergence exceeds X, revisit the serviceable-fraction assumptions in market.json before quoting') so the main path has a fix-and-revalidate loop, not just the opt-in autoresearch bridge.

Trim the 'Distinct from' table's overlap with the frontmatter description and the 'Do NOT use' bullets — the campaign-analytics and demand-acquisition rows restate the same boundary twice.

DimensionReasoningScore

Conciseness

The body is dense and operational, assuming domain knowledge (Kotler criteria, FPC, AAPOR) rather than explaining basics, but the 5-question forcing-question library with per-question Recommended/Canon lines and the 'Distinct from' table partially duplicate the references section and the frontmatter description. Efficient with minor instances that could be trimmed, matching the 4 anchor rather than the 5 ('every token earns its place') or the 3 (noticeable padding).

4 / 5

Actionability

Fully executable, copy-paste-ready commands with real flags throughout: 'market_sizer.py --input market.json --method both --profile {b2b-saas|consumer|enterprise|marketplace|hardware|services}', 'sample_size_planner.py --population 62000 --confidence 0.95 --moe 0.05', onboarding and autoresearch invocations, plus a scripts table documenting '--help', '--sample', '--output {human,json}'. Specific examples cover the common cases, matching the 5 anchor.

5 / 5

Workflow Clarity

A clear 5-step workflow (brief → size → plan → score → assemble) with explicit validation checkpoints ('Reconcile the top-down/bottoms-up delta before quoting anything', 'Drop segments failing the substantiality/accessibility gate', 'Lock 1-2 before opening 3-5'). It falls short of the 5 anchor because recovery from a failed triangulation is only implicitly handled — the body says to reconcile the delta and offers the opt-in autoresearch loop, but gives no direct fix-and-revalidate loop in the main workflow.

4 / 5

Progressive Disclosure

The References section clearly signals three one-level-deep files with one-line scope descriptions, all verified to exist, and the scripts table maps each tool to its purpose. It does not reach 5 because the 25-line forcing-question library with canon citations is inline content that belongs in a reference file, keeping the overview slightly heavier than a clean split.

4 / 5

Total

17

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20

Passed

Description

92%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.

An excellent description: it names three concrete methodology capabilities, opens with an explicit 'Use when...' trigger clause, states the output contract and audience, and explicitly disambiguates against the closest sibling skills. The only gap is a handful of missing natural synonyms ('addressable market', 'market analysis', 'competitive intelligence') in the trigger-term coverage.

DimensionReasoningScore

Specificity

Three concrete, comprehensive capabilities are named: 'sizing a market as TAM/SAM/SOM computed BOTH top-down and bottoms-up (never a single unsourced number)', 'planning a survey sample size with finite-population correction and per-segment minimums', and 'scoring candidate market segments against Kotler's measurable/substantial/accessible/differentiable/actionable criteria'. This lists multiple specific concrete actions with comprehensive coverage, matching the 5 anchor; the 4 anchor's 'minor gaps in coverage' does not apply.

5 / 5

Completeness

It explicitly answers both what and when: 'Use when doing upstream market-research methodology — sizing a market... planning a survey sample size... or scoring candidate market segments' gives concrete trigger activities, and 'Outputs always show the method and the assumptions' plus 'For market-research analysts and product-marketing at the sizing/survey/segmentation moment' add the output contract and audience. Clearly matches the 5 anchor.

5 / 5

Trigger Term Quality

Good keyword coverage of natural terms users would say — 'market-research', 'TAM/SAM/SOM', 'sizing', 'survey', 'sample size', 'segmentation', 'market segments'. A few natural synonyms are missing (e.g. 'addressable market', 'market analysis', 'market opportunity', 'competitive intelligence' — the last appears only in the body), so it fits the 4 anchor ('a few natural terms missing') rather than the 5's comprehensive synonym coverage.

4 / 5

Distinctiveness Conflict Risk

'Distinct from marketing-skill (campaign analytics, attribution, demand-gen) — this is the evidence-building methodology, not live-campaign optimization' draws an explicit boundary against the nearest neighbor, and the upstream framing separates it from positioning/pricing skills. Clear niche with distinct triggers and minimal conflict risk, matching the 5 anchor.

5 / 5

Total

19

/

20

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.

Validation — 15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

metadata_field

'metadata' should map string keys to string values

Warning

Total

15

/

16

Passed

Repository

alirezarezvani/claude-skills

Path

research-ops/skills/market-research/SKILL.md

Reviewed

Table of Contents

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