Content
75%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, well-structured instruction body: concrete parameter/output tables, domain-specific interpretation thresholds that add real value, executable code, and clearly signaled cross-references. The main improvements are an example factor_analysis invocation with a sample CSV format, and trimming the Zoo metadata description.
Suggestions
Add a short example showing the factor_analysis tool being invoked (command or function call) with a small sample factor/return CSV layout to make the core step fully executable.
Trim the AlphaMeta validation-pipeline detail in 'Calling Zoo Factors' to the one sentence a caller needs, moving schema detail to the alpha-zoo skill it already references.
Consider splitting 'Factor Combination Methods' and 'Common Pitfalls' into a reference file if the skill grows, to keep SKILL.md a lean overview.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is dense and efficient — tabulated IC/IR thresholds, parameter tables, and formulas that encode domain knowledge Claude cannot reliably recall. Minor over-explanation exists (e.g. the detailed AlphaMeta validation pipeline description in 'Calling Zoo Factors' and 'The simplest method: standardize each factor and sum'). Not 5 because a few sentences could be trimmed; not 3 because there is no padded conceptual filler. | 4 / 5 |
Actionability | Provides a concrete tool parameter table, expected output files with contents, an executable Registry code snippet, a pip install command, and explicit combination formulas. Minor gaps: no example invocation of the factor_analysis tool itself and no sample CSV layout showing the required (date x code) structure. Not 5 because the core tool call is described but never shown; not 3 because most guidance is executable. | 4 / 5 |
Workflow Clarity | A clear five-step sequenced workflow with a highlighted 'Key point' on CSV alignment and forward returns, plus interpretation criteria that function as validity checkpoints (e.g. 'IC mean > 0.10 ... check for look-ahead bias'). Not 5 because there is no explicit verify-inputs-before-running step or feedback loop (interpret-fail-revise) spelled out; not 3 because checkpoints are largely present via the interpretation standards and warning signs. | 4 / 5 |
Progressive Disclosure | No bundle files exist (references/, scripts/, assets/ are absent), so all content is appropriately inline under well-organized headers, and cross-skill pointers ('multi-factor', 'alpha-zoo') are clearly signaled and one level deep. Not 5 because some sections (Factor Combination Methods, Common Pitfalls) are long enough that a references split would improve navigability if a bundle were introduced; not 3 because organization and signaling are solid. | 4 / 5 |
Total | 16 / 20 Passed |