Content
77%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a strong, highly actionable skill with excellent executable examples in both Cypher and Python, clear workflow sequencing with validation checkpoints, and good error handling guidance. Its main weakness is length — it straddles being an overview and a comprehensive reference, which makes it slightly verbose for a SKILL.md. The routing guidance between related skills is thorough but somewhat repetitive across formats.
Suggestions
Consider moving the detailed algorithm examples (Louvain, WCC, Betweenness, Node Similarity individual sections) to references/algorithms.md and keeping only the algorithm selection table and one representative example (e.g., PageRank) in the main SKILL.md to reduce length.
Consolidate the 'When to Use' / 'When NOT to Use' bullet lists and the routing table into a single format to eliminate redundancy.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is generally efficient and avoids explaining basic concepts, but includes some redundancy — the 'When to Use' / 'When NOT to Use' section with both bullet lists AND a table is duplicative, and some algorithm sections repeat patterns that could be condensed. The routing table and multiple cross-references to other skills, while useful, add bulk. | 2 / 3 |
Actionability | Excellent actionability throughout — every algorithm section includes both executable Cypher and Python code examples that are copy-paste ready. The FastRP → KNN pipeline is a complete end-to-end workflow with numbered steps. Connection setup, estimation, and cleanup all have concrete code. | 3 / 3 |
Workflow Clarity | The Full Workflow section provides a clear 7-step sequence with validation checkpoints (verify plugin, estimate memory, stream first before write). The FastRP → KNN pipeline demonstrates a concrete multi-step workflow with estimation and cleanup. The execution modes table with the 'stream → mutate → write' pattern provides explicit guidance, and the MCP Tool Mapping includes a confirmation step before writes. | 3 / 3 |
Progressive Disclosure | References to algorithms.md and graph-projection.md are well-signaled, but no bundle files were provided to verify they exist. The SKILL.md itself is quite long (~350 lines) and some content like the full algorithm selection table and detailed error table could potentially be moved to reference files. The structure is good with clear sections, but the document tries to be both overview and detailed reference. | 2 / 3 |
Total | 10 / 12 Passed |