Professor Sausages — Trust & Verification

Request missing data

request_data

The suggestion box: ask for data we don't have (a pre-2015 filing, an uncovered ticker, an unsupported chain, a whole dataset). Requests feed the nightly ingestion queue — filings are usually available within ~24h. Include contact if you want to hear back. Free.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "description": "<description>"
    },
    "name": "request_data"
  }
}

Input Schema

Name	Required	Description
`contact`	No	Optional: URL/email/handle for follow-up
`use_case`	No	Optional: what you're building
`description`	Yes	What data you need, in your own words

Schema Changelog

Changes observed during successful MCP inspections.

First observedAug 17, 2026

TDQS

A4.2/5.0

Behavior4/5

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

With no annotations, the description carries full responsibility. It discloses the nightly ingestion queue, ~24h turnaround, the need for optional contact, and that the service is free. It does not mention potential limitations or success criteria, but the behavior is reasonably transparent for a request tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, front-loaded with the core purpose, followed by concrete examples and behavioral notes. Every clause earns its place; no fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

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 covers the workflow, timing, and cost. It could mention how to track request status or what happens if a request is rejected, but it is largely complete given the tool's simplicity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

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 context around the 'description' parameter (examples of what to ask for) and 'contact' (optional follow-up), but it does not substantially extend what the schema already provides. It reinforces rather than enriches.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies the tool as a request mechanism for missing data, with specific examples (pre-2015 filing, uncovered ticker, unsupported chain) that distinguish it from sibling retrieval tools. The verb 'ask for' and resource 'data we don't have' make the purpose unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description conveys when to use it (when data is missing from existing coverage) and gives concrete examples, but it doesn't explicitly reference sibling tools or state 'use this if find_data/coverage fails.' The implied guidance is strong but not fully explicit.

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

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