Content
65%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
A highly actionable, well-sequenced skill body with concrete commands and exact thresholds, but it is verbose with duplicated FINVIZ-mode content, lacks explicit validation feedback loops for its batch scan, and carries a few inaccurate script-path references alongside a large inline JSON block.
Suggestions
Deduplicate the FINVIZ Elite-vs-public comparison — keep it in one place (e.g., the Important Notes table) and reference it elsewhere instead of restating timing/mode details in Prerequisites and Workflow Step 2.
Add an explicit validation checkpoint after the script run (e.g., confirm the JSON was written and is non-empty, and check the data_quality block) before proceeding to narrative confirmation, to give the batch workflow a real feedback loop.
Fix script-path references: remove or correct the missing finviz_industry_scanner.py entry and point theme_classifier.py to its actual scripts/calculators/ location, and consider moving the large inline JSON output example into a reference file.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Mostly efficient and domain-specific (no basic-concept padding Claude already knows), but it is padded with repetition — FINVIZ Elite vs public appears in Prerequisites, Workflow Step 2 timing, and the Important Notes table — and the 10-bullet 'Key Features' restates the Overview, so it could be tightened rather than earning the lean top anchor. | 2 / 3 |
Actionability | Provides fully executable, copy-paste-ready commands (pip install, the uv fallback, the script invocation with many flag examples) plus exact scan-rule thresholds (return_5d >= 20, volume >= 9,000,000, etc.) and explicit input contracts for --scan-hits and --narrative-scores. | 3 / 3 |
Workflow Clarity | Six steps are clearly sequenced and Step 1 verifies the environment, but for a batch operation (scanning ~145 industries) there is no explicit error-recovery feedback loop or validation checkpoint on the script output before proceeding, so per the batch-operation cap it stays at 2 rather than 3. | 2 / 3 |
Progressive Disclosure | Structure and reference signaling are decent (four reference docs listed in Step 5 and Resources, one level deep, all present on disk), but the body inlines a ~70-line JSON output example that could be split out, and script references are inaccurate — finviz_industry_scanner.py is missing and theme_classifier.py is in calculators/ not the scripts/ root the 'Scripts Directory' section implies. | 2 / 3 |
Total | 9 / 12 Passed |