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requesthunt

Generate user demand research reports from real user feedback. Scrape and analyze feature requests, complaints, and questions from Reddit, X, GitHub, YouTube, LinkedIn, and Amazon. Use when user wants to do demand research, find feature requests, analyze user demand, or run RequestHunt queries.

67

Quality

80%

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

68%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.

The body is highly actionable with complete CLI examples and a useful report template, but it is held back by redundant platform-selection guidance (stated three ways) and a missing scrape-completion validation loop in the research workflow. Splitting the platform guide into a reference file would improve both conciseness and progressive disclosure.

Suggestions

Collapse Platform Strengths, Recommended Platforms by Category, and Quick Selection Rules into a single table — the same guidance is repeated three times and costs significant context.

Add an explicit validation step in the research workflow: poll "requesthunt scrape status <job_id>" until complete and verify collected counts (e.g., "requesthunt list --topic ...") before generating the report.

Move the Platform Selection Guide and/or the report template into a references/ file (e.g., PLATFORMS.md, REPORT-TEMPLATE.md) to keep SKILL.md a lean overview.

DimensionReasoningScore

Conciseness

Platform selection guidance is stated three times (Platform Strengths table, Recommended Platforms by Category table, and Quick Selection Rules), and the Step 2 examples restate the same strategies, which is noticeable tightening opportunity; the rest is mostly dense and useful. Fits the 3 anchor (mostly efficient but some unnecessary content) rather than the 4 anchor because the redundancy is substantial, not minor.

3 / 5

Actionability

Every section provides copy-paste-ready CLI commands with flags (auth, search, list, scrape, config verification with expected output), plus a complete Markdown report template. This matches the 5 anchor (fully executable, covers the common cases); not 4 because there are no gaps in executable guidance.

5 / 5

Workflow Clarity

The Define Scope -> Collect Data -> Generate Report sequence is clear and auth has a validation checkpoint ("Verify with: requesthunt config show" with expected output), but the credit-consuming batch scrape operation has no validation loop — "requesthunt scrape status" is documented as a command yet the workflow never instructs polling it or confirming data landed before report generation. Per the guideline capping batch operations without validation at 3.

3 / 5

Progressive Disclosure

No bundle files exist, and the single-file body is well-sectioned with clear headers and only one-level external links (docs, setup.md) — good structure matching the 4 anchor. Not 5 because the ~40-line Platform Selection Guide and report template are inlined where separate reference files would slim the overview; not 3 because organization and navigation are solid, not merely "some structure".

4 / 5

Total

15

/

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 strong: concrete actions, explicit 'Use when' triggers, named platforms, and a distinct niche. The only gap is a few missing natural synonyms (e.g., user feedback analysis, market research).

Suggestions

Add common user phrasings such as "user feedback analysis", "market research", or "product research" to the trigger clause to broaden natural-term coverage.

DimensionReasoningScore

Specificity

"Scrape and analyze feature requests, complaints, and questions from Reddit, X, GitHub, YouTube, LinkedIn, and Amazon" plus "Generate user demand research reports" lists multiple concrete actions (collect, analyze, report) with comprehensive coverage, matching the 5 anchor; coverage is complete rather than having minor gaps.

5 / 5

Completeness

It explicitly answers both what ("Generate user demand research reports... Scrape and analyze feature requests, complaints, and questions") and when ("Use when user wants to do demand research, find feature requests, analyze user demand, or run RequestHunt queries") with concrete trigger phrases, matching the 5 anchor exactly.

5 / 5

Trigger Term Quality

Natural phrases like "demand research", "find feature requests", "analyze user demand", and "RequestHunt queries" are present and would be said by users, but common variations such as "user feedback analysis", "market research", or "product research" are missing, fitting the 4 anchor (good coverage, a few natural terms missing) rather than the 5 anchor.

4 / 5

Distinctiveness Conflict Risk

The niche (user demand research scraped from six named platforms, with the RequestHunt tool named) is clearly distinct with trigger phrases unlikely to fire for unrelated skills, matching the 5 anchor; it is not merely "mostly distinct" as in the 4 anchor.

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
ReScienceLab/opc-skills
Reviewed

Table of Contents

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