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

With no annotations, the description carries the burden and does it well: it reveals that requests feed a nightly ingestion queue, filings usually appear within ~24 hours, contact is optional for follow-up, and the service is free. This goes beyond a basic mutation request and sets expectations about asynchronous processing.

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 punchy sentences: the first explains what the tool is and gives examples, the second covers queue timing, contact, and cost. Every word earns its place, with no fluff or repetition.

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 request tool with no output schema and one required parameter, this description is well-rounded. It covers the purpose, process, timing, contact, and pricing. It does not explain the full request lifecycle (e.g., whether requests are public) but given the simplicity, this is not a major gap.

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 coverage is 100%, so the baseline is 3. The description adds a little context around the contact parameter ('include contact if you want to hear back') but does not explain the description or use_case parameters beyond what the schema already provides. It neither improves nor worsens schema clarity.

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 identifies the tool as a 'suggestion box' for requesting missing data, with concrete examples (pre-2015 filing, uncovered ticker, unsupported chain, whole dataset). This specific verb+resource framing distinguishes it from the sibling data-retrieval tools like find_data and coverage.

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 data is not already available ('ask for data we don't have') and gives examples that reflect gaps. It does not explicitly name sibling tools as alternatives, but the context of 'missing data' and the queue behavior make the intended use clear. Slightly stronger if it said 'instead of find_data, use this'.

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