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

With no annotations, the description carries the transparency burden. It discloses that requests feed a nightly queue, turnout time, optional contact, and that it's free. It doesn't mention rate limits or authentication, but for a request submission tool, this is adequate and adds context beyond raw schema.

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 short sentences, front-loaded with the purpose via the 'suggestion box' analogy. Every word adds value, with no filler or redundant information.

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 tool with no output schema and three parameters, the description covers when to use it, what to include, and the expected turnaround. It could mention how to track a request or what response to expect, but given the tool's simplicity and the schema's coverage, it is sufficiently complete.

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 schema itself documents all parameters. The description adds a bit of context for the 'contact' parameter ('if you want to hear back') and provides real-world examples, but it doesn't introduce meaning beyond what the schema already explains.

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 is for requesting missing data, using examples like pre-2015 filings and uncovered tickers, and the 'suggestion box' metaphor makes the purpose obvious. It does not explicitly name the sibling find_data tool to differentiate, so it's clear but not fully distinct.

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 provides clear context on when to use it: when data is missing, and it sets expectations with the nightly ingestion queue and ~24h availability. However, it does not explicitly state when not to use it or recommend alternatives like find_data, so it lacks explicit exclusions.

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