analyzing-mempool
Monitor blockchain mempools for pending transactions, gas analysis, and MEV opportunities. Use when analyzing pending transactions, optimizing gas prices, or researching MEV. Trigger with phrases like "check mempool", "scan pending txs", "find MEV", "gas price analysis", or "pending swaps".
78
75%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Advisory
Suggest reviewing before use
Optimize this skill with Tessl
npx tessl skill review --optimize ./plugins/crypto/mempool-analyzer/skills/analyzing-mempool/SKILL.mdQuality
Discovery
100%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
This is a strong skill description that clearly defines its capabilities, provides explicit trigger guidance with natural user phrases, and occupies a distinct niche. It follows the recommended pattern of 'what it does' + 'Use when...' + trigger phrases, and uses third-person voice throughout. Minor improvement could include mentioning specific blockchain networks (e.g., Ethereum) for even more specificity.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: monitoring mempools, pending transaction analysis, gas analysis, and MEV opportunity detection. These are distinct, concrete capabilities. | 3 / 3 |
Completeness | Clearly answers both 'what' (monitor mempools, gas analysis, MEV opportunities) and 'when' (explicit 'Use when...' clause plus a 'Trigger with phrases like...' section providing concrete trigger terms). | 3 / 3 |
Trigger Term Quality | Excellent coverage of natural trigger terms users would say: 'check mempool', 'scan pending txs', 'find MEV', 'gas price analysis', 'pending swaps'. These are realistic phrases a user in this domain would naturally use. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive niche — blockchain mempool monitoring, MEV, and gas analysis are very specific domains unlikely to overlap with other skills. The trigger terms are domain-specific and precise. | 3 / 3 |
Total | 12 / 12 Passed |
Implementation
50%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The skill provides a reasonable structure for mempool analysis with clear CLI commands and good progressive disclosure references, but suffers from relying entirely on an external script that isn't included in the bundle. Actionability is limited since Claude can't verify or execute anything without the actual script, and workflow clarity lacks validation checkpoints for network-dependent operations that commonly fail.
Suggestions
Include the `mempool_analyzer.py` script in the bundle or provide inline executable Python code for core operations (e.g., fetching pending transactions via eth_getBlockByNumber with pending flag)
Add a validation step before running commands, such as checking RPC connectivity: `python mempool_analyzer.py --check-connection` or a simple curl/requests snippet to verify the endpoint
Include the referenced files (errors.md, examples.md, implementation.md) in the bundle so progressive disclosure actually works
Trim the Overview section and MEV Warnings to reduce redundancy—Claude already understands these concepts from the skill description and general knowledge
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Mostly efficient but includes some unnecessary content like the Overview section restating what the skill description already covers, and the 'MEV Warnings' section explaining things Claude would know. The prerequisites section explaining Python version requirements is borderline unnecessary. | 2 / 3 |
Actionability | Provides concrete CLI commands which is good, but all commands reference a `mempool_analyzer.py` script that isn't provided in the bundle. There's no executable Python code shown—everything depends on an external script whose implementation is unknown. The examples are concrete but shallow (just CLI invocations with brief comments). | 2 / 3 |
Workflow Clarity | Steps are clearly sequenced (navigate, choose command, interpret results), but there are no validation checkpoints. For operations involving RPC calls that can fail, there's no feedback loop—error handling is deferred entirely to a separate file. No verification step to confirm RPC connectivity before running commands. | 2 / 3 |
Progressive Disclosure | References to external files (errors.md, examples.md, implementation.md) are well-signaled and one level deep, which is good. However, no bundle files were provided, so these references may be broken. The main content includes some material that could be more concise while the referenced files that should contain the detail are absent. | 2 / 3 |
Total | 8 / 12 Passed |
Validation
81%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 9 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
allowed_tools_field | 'allowed-tools' contains unusual tool name(s) | Warning |
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 9 / 11 Passed | |
- Commit
3a2d27d
- Reviewed
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