lookup_word

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

With no annotations, the description carries the full burden. It discloses what the tool returns (grammatical parsing, collation, Strong's number, gloss), which is sufficient for a read-only lookup. It does not mention potential errors or side effects, but none are expected for this simple operation.

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 concise, with two sentences that front-load the purpose and then list the expected output. Every word adds value, and it is easy to scan.

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 lookup tool, the description covers the essential context: what it does, what input it expects, and what it returns. There is no output schema, but the description explicitly lists the returns, making it complete for an agent to decide when to use it.

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?

The schema only provides the parameter name, type, and title. The description enriches it by explaining that word_id is a specific original word link token and giving concrete format examples (e.g., 'JHNc1v1w5'). This fully clarifies the parameter meaning.

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's purpose: to drill down into a specific original word link token and return detailed information. The verb 'drill down' and the focus on a specific token distinguish it from sibling tools like search_text or search_lemma.

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 implies usage when you have a specific token ID (with examples), but it does not explicitly contrast with alternatives or mention when not to use it. The examples help, but there is no direct guidance on choosing between this and sibling tools.

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