Content
86%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 well-structured, highly actionable skill body: exact commands that match the bundled script's CLI, clear step sequencing, and appropriate use of one-level-deep reference files. Only minor trims to audience/advisory lines and an optional connection-check step would improve it further.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is lean and command-focused with no explanation of concepts Claude already knows, but contains minor padding that could be trimmed, such as 'Useful for traders, MEV researchers, and protocol developers' and the advisory MEV warnings lines. | 4 / 5 |
Actionability | Fully executable, copy-paste-ready commands (e.g., 'python mempool_analyzer.py pending --limit 100', 'python mempool_analyzer.py --chain polygon gas') that were verified against the actual CLI in mempool_analyzer.py; all subcommands and flags exist and examples cover the common cases. | 5 / 5 |
Workflow Clarity | A clear three-step sequence (navigate, choose command, interpret results) with result interpretation guidance and error recovery delegated to references/errors.md; no explicit checkpoint such as verifying RPC connectivity before running, though the read-only nature of the tool limits the need for validation. | 4 / 5 |
Progressive Disclosure | A concise overview with well-signaled, verified, one-level-deep references (errors.md, examples.md, implementation.md) covering error handling, advanced details, and extra examples, plus a contents navigation line; the split is appropriate for the bundle. | 5 / 5 |
Total | 18 / 20 Passed |