search_positions

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

Annotations already indicate readOnlyHint=true, so the description doesn't need to restate safety. It adds value by explaining the data origin (LLM-extracted) and return granularity (one row per filing, argument), which are behavioral traits beyond the annotation.

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?

Three sentences: first sets function and scope, second lists filter options, third gives concrete examples and return format. No redundancy, front-loaded with key purpose.

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?

No output schema, but the description explains the return structure (one row per filing, argument). It covers filter categories and provides examples. Missing details on pagination or ordering, but limit parameter covers result count.

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 description lists filter categories but does not add detail beyond what the schema already provides for each parameter.

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 searches LLM-extracted policy arguments across COMMENT/REPLY/PETITION filings with specific filters. It distinguishes from sibling tools like search_filings (filings-level) and search_semantic (semantic search) by focusing on structured arguments and providing concrete example questions.

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 includes example questions ('who opposed X?', 'which filings support modular satellite licensing?'), which imply appropriate use cases. However, it does not explicitly state when not to use this tool or mention alternatives like search_filings for raw filings.

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