Content
64%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-structured, highly actionable skill with excellent concrete examples and a useful report template. Its main weaknesses are verbosity in the platform selection guide and prerequisites sections, and the lack of validation checkpoints in the workflow (e.g., verifying scrape job completion, handling empty results, iterating when data is insufficient). The content would benefit from splitting reference material into separate bundle files.
Suggestions
Add validation checkpoints to the workflow: check `requesthunt scrape status` before generating reports, handle empty/low-yield results with guidance to expand platforms or adjust queries.
Move the Platform Selection Guide tables and the Commands reference section into separate bundle files (e.g., PLATFORMS.md, COMMANDS.md) and reference them from SKILL.md to reduce token footprint.
Trim the Prerequisites section — remove the SHA256 verification detail, cargo install alternative, and headless environment setup into a referenced setup file or collapse into a brief note.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The platform selection guide tables are useful but quite extensive — the two large tables (Platform Strengths + Recommended Platforms by Category) plus the Quick Selection Rules section add significant token weight. The prerequisites section also over-explains installation details (SHA256 verification, cargo install alternative, headless environments) that could be trimmed. However, the command examples and report template are reasonably efficient. | 2 / 3 |
Actionability | The skill provides fully executable CLI commands for every step (install, auth, scrape, search, list), concrete platform-specific examples with rationale, a complete report template in Markdown, and specific configuration/verification commands. Everything is copy-paste ready. | 3 / 3 |
Workflow Clarity | The 3-step workflow (Define Scope → Collect Data → Generate Report) is clearly sequenced, but there are no validation checkpoints between steps. There's no guidance on verifying scrape completion before generating reports (e.g., checking scrape status before proceeding), no error handling for failed scrapes or empty results, and no feedback loop for iterating on insufficient data. | 2 / 3 |
Progressive Disclosure | The content is well-structured with clear headers and sections, but it's monolithic — the extensive platform selection guide, full command reference, and API info could be split into separate referenced files. Links to external docs exist (requesthunt.com/docs, setup.md) but the inline content is heavy for a single SKILL.md with no bundle files. | 2 / 3 |
Total | 9 / 12 Passed |