Content
80%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 lean, well-organized overview with genuinely concrete data sources, thresholds, and config format, but the operational workflow is underspecified: the run sequence, state persistence for "since the last run" diffing, and detection mechanics for MEV and first-time interactions are left implicit. Tightening those would make the skill reliably executable end-to-end.
Suggestions
Add a short numbered run sequence (load watchlist → fetch logs per chain → classify → diff against last-run state → format output) and specify where last-run state is persisted, since 'surfaces only what's changed since the last run' and 'pattern recognition vs prior weeks' both depend on it.
Specify how MEV bot interactions are detected (e.g., which MEV-known addresses or tx-pattern heuristics) and how first-time-interaction pairs are tracked, so the two most novel alert types are reproducible.
State the USD enrichment method concretely (which CoinGecko/DefiLlama endpoint or parameter) to match the specificity already present in the Sources section's RPC methods.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Every section earns its place: a compact watchlist YAML with inline comments, a tight trigger table, one sentence of concrete data sources ("eth_getLogs for ERC-20 Transfer + Approval topics"), and behavior rules — with no explanation of concepts Claude already knows (no primer on what ERC-20 or an RPC is). It matches the 'lean and efficient; every token earns its place' anchor; score 4 would require some trimming, and none is evident. | 5 / 5 |
Actionability | Guidance is mostly concrete: exact RPC methods ("eth_getLogs", "eth_getTransactionByHash"), named price sources (CoinGecko / DefiLlama), explicit thresholds ($1,000, 0.05 ETH, $50,000), and a full watchlist config schema. It falls short of 5 because key mechanics are unspecified — how MEV sandwich/frontrun/backrun interactions are detected, how first-time-interaction state is tracked, and which endpoint serves the USD enrichment. Not 3 because what is present is executable guidance, not pseudocode or vague direction. | 4 / 5 |
Workflow Clarity | A rough sequence is implied (pull activity → classify → surface what changed → output), but there is no explicit step ordering and no validation checkpoints (e.g., handling RPC failures or unpriced events beyond "show without $"). Critically, "surfaces only what's changed since the last run" and "pattern recognition vs prior weeks" depend on persisted state, yet where last-run state is stored or restored is never specified. This is a genuine gap that keeps it at the anchor-3 level (sequence present but checkpoints/mechanics missing or implicit) rather than 4. | 3 / 5 |
Progressive Disclosure | The skill is under 50 lines with no external files needed, and the body is organized into clean, well-labeled sections (Watchlist, Alert triggers, Sources, Output, Rules) with no inlined content that belongs in a separate file — the rubric's simple-skill guideline allows a 5 on well-organized sections alone. There are no references to verify and no buried or nested navigation. | 5 / 5 |
Total | 17 / 20 Passed |