Content
76%Weight 40%Scale 1-5Reviews 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 with executable commands for all modes and genuine, well-organized reference files. Its main gap is the absence of any validation/verification or error-recovery step in a batch workflow that makes ~200 API calls, and secondarily the inline tuning tables that should live one level deeper.
Suggestions
Add an explicit verification checkpoint after Step 1 — e.g. 'Confirm the timestamped JSON/MD files exist in --output-dir; if the FMP API returned errors or the rate limit was hit, re-run with a smaller universe or wait for the daily quota' — so the batch screening workflow has a validate-and-retry loop instead of silently proceeding.
Move the Advanced Tuning parameter table and the historical-mode flag table into a reference file (e.g. references/tuning_parameters.md) and link to it, keeping SKILL.md to the default invocation plus one tuning example.
Trim the redundancy between the intro paragraph / historical-mode prose and the 'When to Use' bullets, which currently state the same purpose twice.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is dense and efficient — commands, parameter tables, and outcome guidance with almost no explanation of concepts Claude already knows. Not 5 because of minor redundancy: the intro paragraph restates the description, and the historical-mode prose re-explains purpose already covered in 'When to Use'. | 4 / 5 |
Actionability | Fully executable copy-paste commands for every mode — default, custom universe, full S&P 500, strict, historical (three variants), and advanced tuning — with defaults, ranges, and effects tabulated, plus a clear presentation template for results. Covers the common cases completely. | 5 / 5 |
Workflow Clarity | Steps 1-4 are clearly sequenced (execute screening → review results → present analysis → give guidance), but there is no validation or verification checkpoint: nothing confirms the reports were generated, handles API errors or rate-limit failures, or loops back on failure. The rubric's cap for batch operations without validation (~200 API calls across the 3-phase pipeline) applies; not 4 because that cap takes precedence over the otherwise good sequencing. | 3 / 5 |
Progressive Disclosure | Three real, one-level-deep reference files (vcp_methodology.md, scoring_system.md, fmp_api_endpoints.md — all verified present in references/) are well signaled in Step 2 and the Resources section, and the referenced script exists in the bundle. Not 5 because the two large inline parameter tables (~30 lines of tuning detail) belong in a reference file, leaving the overview heavier than an ideal quick-start. | 4 / 5 |
Total | 16 / 20 Passed |