Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already provide readOnlyHint=true, so the description's addition of 'Pure computation — no RPC call needed' gives extra behavioral context beyond annotations. It also explains the input provenance, but doesn't mention failure modes or edge cases, which is acceptable given the simplicity.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences with no filler. The first sentence states the core function, the second provides the key usage hint. Every word earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With 3 parameters, full schema coverage, and readOnly annotations, the description covers the essential context: purpose, input source, and the fact it's pure computation. It mentions 'named fields' as the output, which suffices given no output schema is present, though more detail on return format could have been added.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already fully documents topics, data, and abi. The description reinforces that topics and data come from a log entry but adds no new parameter-level meaning beyond the schema, earning the baseline score.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool decodes raw event logs (topics + data) into named fields using an ABI. It distinguishes from siblings by specifying 'event log' (vs calldata) and 'on Mezo' (vs eth/testnet variants), making the purpose unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly states 'Pure computation — no RPC call needed', which tells the agent this can be used offline, contrasting with RPC-dependent tools. It also advises passing topics/data from a transaction receipt log entry, giving clear input context, but does not explicitly mention alternative tools for calldata decoding.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.