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

With no annotations, the description carries the transparency burden well. It discloses that requests feed a nightly ingestion queue and are usually available within ~24h, and mentions optional contact for follow-up. It doesn't detail response behavior, but for a request tool this is adequate.

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 compact: a purpose phrase, examples, a time-frame, and a note on contact. Every sentence adds value; 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, the description is complete enough: it explains the request process, expected timing, and optional contact. It doesn't mention what the immediate response looks like, but that's not critical for this type of tool.

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% with descriptions and examples for all three parameters, so the baseline is 3. The description adds only general context (e.g., 'Include contact if you want to hear back') which is redundant with the schema, and does not add new syntax or nuances.

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 opens with 'The suggestion box: ask for data we don't have' – a specific verb and resource. It clearly distinguishes itself from siblings like find_data by focusing on missing data, with concrete examples (pre-2015 filing, uncovered ticker).

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?

It clearly states when to use this tool: when data is not available (pre-2015 filing, unsupported chain, whole dataset). However, it does not explicitly name alternatives or provide when-not-to-use guidance, so it's more implied than fully explicit.

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