Content
92%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
A lean, highly actionable skill body with clear workflows and a validation checklist, held back only by monolithic structure — all platform references are inline rather than split into separate reference files.
Suggestions
Move each platform's template + mapping tables + syntax rules into dedicated bundle files (e.g. references/pine.md, references/tdx.md, references/mql5.md) and keep SKILL.md as an overview with clearly signaled one-level-deep links.
In SKILL.md, replace the inline per-platform reference sections with a short navigation table linking to those reference files so the overview stays compact.
Confirm any referenced bundle paths actually exist under references/ (currently no bundle directory is present), since progressive disclosure is scored against the real bundle structure.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is dense, table-driven reference material (Python→Pine/TDX/MQL5 mappings, syntax rules) that Claude does not reliably know, with no padding about basic concepts; nearly every token earns its place. | 3 / 3 |
Actionability | Each platform ships an executable template (Pine Script v6, TDX formula, MQL5 indicator) plus concrete copy-paste-ready mapping tables and explicit syntax rules, giving fully actionable guidance. | 3 / 3 |
Workflow Clarity | Two numbered workflows give a clear sequence, and the pre-output 'Quality Checklist' acts as an explicit validation gate with per-platform verification items for a complex multi-output process. | 3 / 3 |
Progressive Disclosure | Content is well-organized with clear sections, but ~300 lines of per-platform API reference live inline in a single 380-line SKILL.md with no bundle files or one-level-deep references to split them out. | 2 / 3 |
Total | 11 / 12 Passed |