japanese_research

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

With no annotations, the description carries the full burden. It adds value by disclosing the cost ($0.02 USDC per request) but fails to mention whether the tool is read-only, data freshness, pagination, or any side effects. The behavioral disclosure is minimal.

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 a single sentence with a clear list of topics and cost, which is efficient. It front-loads the core purpose. However, it could be slightly more structured (e.g., separating content from cost) to improve readability.

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?

Given two simple parameters and no output schema, the description provides enough context to understand the tool's focus but lacks details about output format, result limits, or how to interpret data. It is adequate but not thorough for an AI agent to fully anticipate 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%, so the baseline is 3. The tool description does not add any additional semantics beyond the schema's parameter descriptions (e.g., 'Days to look back (1-7)' and focus enum). No extra context is provided.

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 explicitly lists specific content types ('Nikkei news, corporate earnings surprises, BOJ policy signals, and sector rotation analysis'), which are distinct from sibling tools that cover broader Asian markets or specific topics like currency or real estate. The verb 'research' is implied, making the tool's purpose clear.

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?

No guidance is provided on when to use this tool versus siblings like 'asia_news_api' or 'cs_jp_currency_api'. There is no mention of when not to use it or prerequisites, leaving the agent to infer from the content list.

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