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market-research-reports

Builds evidence-traceable market research reports and assumption-driven market sizing or forecast scenarios. Use for market definition, industry and customer evidence, competitive landscapes, TAM/SAM/SOM reconciliation, forecast sensitivity, and auditable report scaffolds.

Quality

94%

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SecuritybySnyk

Passed

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SKILL.md
Quality
Evals
Security

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.

This is a well-engineered instruction skill: a clearly sequenced ten-step workflow with per-step validation CLIs, a release gate, and clean one-level-deep reference structure where every cited bundle file exists. Its only notable weakness is conciseness — a few inline lists (survey disclosure fields, ethics "Never" bullets, the citation appendix) duplicate material that belongs in the already-bundled references.

Suggestions

Move the section-7 survey/interview disclosure field lists into references/methods_and_ethics.md, keeping only the top-level rules inline, since that reference already covers the same ground.

Trim or relocate the closing "Citing Scientific Agent Skills" section to a short reference file, leaving a one-line citation reminder in SKILL.md.

Condense the section-1 research-contract bullet list into the few decisions that materially change the denominator, pointing to references/report_structure_guide.md for the full checklist.

DimensionReasoningScore

Conciseness

The body is dense, assumes domain competence (never explains what TAM/SAM/SOM or a survey is), and almost every list encodes non-obvious procedural knowledge (ledger fields, coverage guardrails, reconciliation rules). Minor trimming opportunities remain — e.g., the section-7 survey-disclosure field list and the "Never" bullets overlap with references/methods_and_ethics.md, and the long citation appendix could live in a reference — so it fits "efficient; minor instances that could be trimmed" rather than "every token earns its place".

4 / 5

Actionability

Guidance is fully executable: copy-paste commands with concrete paths for each validator/calculator (e.g., `python3 scripts/audit_claim_citations.py data/claims.csv data/source_ledger.csv`, `python3 scripts/generate_report_scaffold.py assets/report_manifest_template.json ./market-report-workspace`), exact sizing formulas, and explicit ledger schemas. The scaffold command's constraints (horizon derivation, empty-ledger caveat) are stated.

5 / 5

Workflow Clarity

A ten-step numbered workflow with explicit sequencing, per-step validation commands, a release-gate checklist, and explicit feedback-loop handling ("generated empty ledgers and analysis files must be populated before their validators can pass", re-checking API terms before retrieval). This matches the anchor of clear sequence with explicit validation steps and error-recovery guidance.

5 / 5

Progressive Disclosure

SKILL.md is a genuine overview: each step points to exactly one level of references (all seven referenced files in references/ exist on disk, as do all cited assets/ and scripts/ paths), and the Bundled resources section catalogs each file with a one-line description. Content is appropriately split with clear navigation and no nested-reference chains.

5 / 5

Total

19

/

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.

The description is specific, third-person, and clearly states both what the skill does and when to use it with concrete trigger terms. Its only weakness is a few missing natural synonyms a user might say (e.g., "market analysis", "industry research"), which keeps trigger coverage just short of comprehensive.

DimensionReasoningScore

Specificity

The description names the domain and multiple concrete capabilities: "Builds evidence-traceable market research reports and assumption-driven market sizing or forecast scenarios", plus "TAM/SAM/SOM reconciliation, forecast sensitivity, and auditable report scaffolds" — comprehensive coverage of the skill's actions.

5 / 5

Completeness

It explicitly answers both questions: "what" ("Builds evidence-traceable market research reports and assumption-driven market sizing or forecast scenarios") and "when" ("Use for market definition, industry and customer evidence, competitive landscapes, TAM/SAM/SOM reconciliation, forecast sensitivity, and auditable report scaffolds") with concrete trigger phrases.

5 / 5

Trigger Term Quality

Strong natural terms users would say: "market research", "market definition", "competitive landscapes", "TAM/SAM/SOM", "forecast sensitivity". A few common variations (e.g., "market analysis", "industry report", "competitor analysis") are missing, so it falls just short of the comprehensive-synonyms anchor.

4 / 5

Distinctiveness Conflict Risk

It occupies a clear niche (auditable market research and sizing) with distinct triggers like "TAM/SAM/SOM reconciliation" and "forecast sensitivity"; no meaningful overlap with generic research or writing skills.

5 / 5

Total

19

/

20

Passed

Validation

100%

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

K-Dense-AI/scientific-agent-skills

Path

skills/market-research-reports/SKILL.md

Reviewed

Table of Contents

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