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.
The body is highly actionable with concrete CLI examples and clear update rules, but workflow clarity is capped by the absence of explicit validation feedback loops around destructive and batch DSP operations.
Suggestions
Add an explicit validation checkpoint after destructive/batch DSP changes — e.g. run `get-stats`/`detect-cycles`/`get-orphans` to verify consistency, and re-run on failure before proceeding.
Move the full storage-format tree and command table into a local reference file to keep SKILL.md a lean overview.
Trim conceptual framing (graph basics, the "NOT an AST dump" disclaimers) that Claude can infer.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Mostly efficient and focused on DSP-specific concepts and CLI commands, with only minor over-explanation (e.g. the "NOT documentation / NOT an AST dump" framing and basic graph model recap) that could be trimmed. | 4 / 5 |
Actionability | Fully executable guidance: concrete `python dsp-cli.py` commands, a full command table, and three copy-paste-ready bash examples with expected outputs covering setup, navigation, and impact analysis. | 5 / 5 |
Workflow Clarity | Bootstrap and update rules are well sequenced, but destructive/batch operations (remove-entity with cascade cleanup, whole-repo bootstrap) lack explicit validation-retry checkpoints, which caps workflow clarity at 3 per the guideline. | 3 / 5 |
Progressive Disclosure | Well-organized into clear sections with a References block pointing one level deep to external docs; with no bundle files the inline spec is justified, though the full storage-format and command tables could plausibly live in a separate reference file. | 4 / 5 |
Total | 16 / 20 Passed |