Content
100%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The SKILL.md body is a lean, highly actionable pipeline guide with executable commands, explicit validation checkpoints, and well-organized one-level-deep references. It exemplifies progressive disclosure, having been deliberately trimmed from ~650 to ~250 lines by offloading detail to reference files.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is dense and operational, conveying only non-obvious hard-won knowledge (buffer-flush race conditions, CRM-field causality traps) with no padding about concepts Claude already knows; occasional real-run anecdotes earn their place as concrete failure evidence. | 3 / 3 |
Actionability | Provides fully executable bash and Python snippets with real flags and JSON payloads (deepline enrich invocations, analyze_signals.py and dedupe_utils.py calls), which are copy-paste ready rather than pseudocode. | 3 / 3 |
Workflow Clarity | A clearly numbered multi-step pipeline (Steps 0 through 7) with explicit validation checkpoints (Step 3 row-count match, Step 3.5 red-flag review) and feedback loops (fix-and-regenerate configs, re-validate, demote uncited signals), appropriate for batch and paid operations. | 3 / 3 |
Progressive Disclosure | Serves as an overview pointing to nine one-level-deep reference files and three scripts, each clearly signaled with its contents and all verified to exist on disk, with a References section mapping every file to its purpose. | 3 / 3 |
Total | 12 / 12 Passed |