Content
92%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 operational, well-structured skill body: fully executable commands and configs, a ten-step workflow with validation checkpoints and feedback loops, and a clean one-level-deep reference split. The only weakness is redundancy — key rules (low-cardinality handling, SimilaritySearch sourcing, index selection) are stated in both Step 5 and the Tool Configuration section, and the Checklist repeats them a third time.
Suggestions
State the CypherTemplate low-cardinality/valid-values rule and the SimilaritySearch provider/model/dimension sourcing rules once — either in Step 5 or in the Tool Configuration section — and cross-reference the other location instead of repeating them verbatim.
Trim the closing Checklist to items not already verifiable in the step sequence (e.g. drop restatements of schema.json sourcing rules), or fold it into the steps as final checkboxes.
Collapse the duplicated Linux/Windows `uv run` command pairs (Steps 3 and 4) into one line with a note that Windows uses backslashes, saving several lines without losing either platform.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is dense and fluff-free — commands, error paths, and data-sourcing rules with no concept padding — but there is structural duplication beyond 'every token earns its place': the CypherTemplate low-cardinality rule and the SimilaritySearch provider/model/dimension/index guidance each appear in both Step 5 and the "Tool Configuration" section, and the closing Checklist restates step-level rules. This is trimming work rather than the unnecessary explanation of anchor 3, so it sits at anchor 4. | 4 / 5 |
Actionability | Everything is copy-paste executable: real curl commands with correct headers and bodies, `uv run` invocations for all four bundled scripts (all of which exist), complete JSON config templates whose placeholders are explicitly sourced (e.g. `"<name from schema.json metadata.vector_index[state=ONLINE].name>"`), per-script parameter tables, and an error→cause→fix table. Matches anchor 5's 'fully executable, covers the common cases'. | 5 / 5 |
Workflow Clarity | Ten clearly sequenced steps with validation checkpoints throughout: token verification, explicit "Stop and report" on every failure path, a data gate in fetch_schema, user confirmation before create, explicit confirmation for the irreversible delete, and a validation script gate for the eval dataset. Feedback loops exist (401 → re-run Step 1; error table maps causes to fixes) and a closing checklist covers the complex process — the anchor-5 pattern. | 5 / 5 |
Progressive Disclosure | Scored against the actual bundle (3 reference files, 4 scripts, all verified to exist): each reference is linked at its point of need with read-first directives (authoring-guide.md before Step 5, evaluation-dataset-guide.md before Step 10, REFERENCE.md for embedding models and external access), scripts are documented in a table, and references are one level deep with bulky API detail correctly kept out of the main file. No organization gaps that would drop it to anchor 4. | 5 / 5 |
Total | 19 / 20 Passed |