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

With no annotations, the description carries the full burden. It states the tool returns a monthly series for a single item, which is a read operation. However, it does not disclose the response format, historical depth, or any error conditions. The basic behavioral fact (returning data) is present, but richer context like pagination or rate limits is absent.

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?

The description is two sentences, front-loaded with the main purpose and immediately useful examples. There is no wasted wording; every clause contributes to understanding what the tool does and how to use it.

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 tool with a single parameter and no output schema, the description covers purpose, parameter examples, and the sibling tool for list retrieval. It does not describe the output structure, but given the simplicity and the pointer to super_pos, the essential context for calling the tool correctly is present.

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 0%, so the description must compensate. It does so by listing valid slug examples (eggs, milk, bread, etc.) and directing the user to super_pos for the full list. This gives the agent concrete guidance on parameter values beyond the bare string type, fully addressing the parameter semantics.

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 returns a monthly series for one item of the supermarket price index, with a specific resource (Consumer Affairs Agency POS). It also gives concrete slug examples (eggs, milk, etc.) and distinguishes itself from super_pos, which provides the list of items. This is a specific verb+resource with clear sibling differentiation.

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 the alternative: '一覧は super_pos で' (the list is in super_pos), telling the agent to use super_pos for the list and this tool for a specific item. It provides clear context for when to use this tool versus its sibling, though it doesn't enumerate other exclusions or prerequisites.

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