関数セレクタ／イベント topic を計算する

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

Annotations already declare readOnlyHint=true and destructiveHint=false, and the description adds the important behavioral fact that it never accesses the network — information not present in annotations. It also clarifies it's a pure computation tool for educational use. No contradictions with annotations.

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 concise sentences: the first states the core function and outputs, the second adds the no-network constraint and purpose. Every sentence earns its place with no redundancy or filler.

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?

For a simple one-parameter tool with strong annotations and no output schema, the description is complete. It explains what the tool does, what it outputs (selector/topic0), that it's offline, and its educational purpose. There is no ambiguity about usage or behavior.

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% (the single parameter 'signature' includes examples for both function and event signatures). The description adds no further parameter-level detail beyond what's already in the schema, so a baseline of 3 is appropriate.

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 it calculates keccak256 for function/event signatures and shows the selector (first 4 bytes) or topic0. It names the specific resource (signatures) and the action (calculate/show), making it distinct from sibling tools that are all network-dependent.

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?

The description explicitly mentions 'no network access at all', which clearly distinguishes it from the network-heavy sibling tools. It also states its purpose ('to explain where ABI comes from on a whiteboard'), giving context. However, it doesn't explicitly name alternative tools or say 'use this when you need offline computation', so it's short of a 5.

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