Content
83%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 concise, highly actionable skill body with executable commands and concrete examples throughout. The main gap is the lack of an explicit query-workflow sequence with validation/feedback checkpoints, which the rubric caps at 3 for database operations.
Suggestions
Add a short "Query workflow" sequence with a validation checkpoint, e.g. run query → if it errors (blocked keyword / invalid table) → read the error → adjust and retry, to lift workflow_clarity above the database-operations cap of 3.
Note that the script rejects multi-statement and write keywords and how to interpret those errors, so Claude can recover from rejected queries without trial and error.
Clarify that er-diagram output should be rendered/verified (e.g. in a Mermaid viewer) as a lightweight validation step for the diagram workflow.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Lean and efficient — feature table, security bullets, executable commands, and concrete output examples with no padding or explanations of concepts Claude already knows. | 5 / 5 |
Actionability | Fully executable copy-paste commands for every subcommand, plus parameters and subcommands tables and concrete JSON/Mermaid output examples covering the common cases. | 5 / 5 |
Workflow Clarity | Per-subcommand commands are clear, but the body documents no sequenced workflow with validation/feedback loops for query operations (database ops); per the rubric cap, the absence of documented validation caps this dimension at 3. | 3 / 5 |
Progressive Disclosure | Well-organized sections with the single bundle file scripts/db_explorer.py referenced one level deep via real, executable paths; minor organization gaps keep it just below the top anchor. | 4 / 5 |
Total | 17 / 20 Passed |