Content
68%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 delivers actionable, executable CLI guidance with a clear structure and reasonable token efficiency, but its workflow lacks the explicit validation checkpoints expected for destructive graph mutations. Progressive disclosure is solid, with external references cleanly signaled.
Suggestions
Add an explicit validation step after create/remove/move operations (e.g., run `get-stats` or `detect-cycles` and confirm the expected entity exists before proceeding).
Trim framing sentences that restate the value proposition ('This is enough for an agent to navigate...') to tighten token efficiency.
Consider bundling a local reference doc (e.g., a command cheatsheet) so detailed material is available without an external network fetch.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is efficient and assumes competence, with only minor instances of over-explanation (e.g., framing sentences like 'This is enough for an agent to navigate...') that could be trimmed. | 4 / 5 |
Actionability | It provides concrete, executable `python dsp-cli.py` commands across setup, navigation, and impact-analysis examples that are mostly copy-paste ready, with only minor gaps. | 4 / 5 |
Workflow Clarity | Sequences are clearly laid out ('When to Use', 'Workflow Rules', 'When to Update DSP'), but create/remove/move operations are potentially destructive/batch and lack explicit validation checkpoints, capping this at 3. | 3 / 5 |
Progressive Disclosure | Content is well-organized into clearly signaled sections with one-level-deep external references (GitHub links) and no nested file chains, though detailed reference docs live off-site rather than in a bundled file. | 4 / 5 |
Total | 15 / 20 Passed |