Content
88%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 highly actionable, well-sequenced skill body that earns its length with Alethia-specific knowledge and concrete examples. The main improvement is trimming time-sensitive version detail and considering splitting a couple of the longer example sections out of the main file.
Suggestions
Move the version-specific 'bridge 0.6.1' / 'Server transport closed unexpectedly' troubleshooting into an 'Old patterns' or 'Deprecated' section, or generalize it, so time-sensitive content does not bloat the main flow.
Consider extracting the four-example 'Dev feedback loop' eval block into a reference file, keeping one representative example inline, to tighten the main SKILL.md.
The 'NLP patterns that work well' and 'NLP patterns that trip the resolver' sections overlap with 'How to drive Alethia in NLP'; merging or cross-linking them would reduce redundancy.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Mostly lean and focused on Alethia-specific concepts Claude does not already know, but a few sections could be trimmed — notably the version-specific 'bridge 0.6.1' troubleshooting, which is time-sensitive information not placed in a deprecated/old-patterns section. | 4 / 5 |
Actionability | Provides fully executable, copy-paste-ready guidance across the common cases — NLP step examples, tool calls with concrete parameters, bash install/cache-clear commands, and JavaScript eval snippets. | 5 / 5 |
Workflow Clarity | Multi-step flows are clearly sequenced with explicit validation ('confirm it's actually available' before use) and a feedback loop (read nearMatches/suggestedFix then retry); destructive and batch operations are validated via the 'expect block:' primitive and assert_safety regression check. | 5 / 5 |
Progressive Disclosure | Well-organized single-file skill with clearly headed sections and no nested references; organization is good, though some detail (e.g., the four eval examples, expanded NLP patterns) could arguably be split out, keeping it just below the top anchor. | 4 / 5 |
Total | 18 / 20 Passed |