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Agent Request Desk

Request data you could not find

request_data

Call this when you need specific data for a task and cannot get it: the site returned 403 or 429, showed a CAPTCHA or Cloudflare challenge, sits behind a login wall, has no API, renders only with JavaScript, publishes only as PDF, or the data is spread across many sites or not found at all. Returns pointers to existing sources (official APIs, open datasets, MCP servers) that may already serve the need, plus a log id. Requests are pooled across agents and the most wanted data gets sourced. Free, no key. Do not include personal data about private individuals.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
formatNoShape you wanted it in, e.g. JSON list, CSV, single value
targetNoSite, organisation or source you tried, if any (domain or name)
privateNoSet true to have your description, purpose and error text used for matching but not stored
purposeNoWhat task the data was for, in a few words
freshnessNoHow fresh it must be, e.g. real-time, daily, monthly
agent_nameNoName of your agent or product, optional
descriptionYesWhat data you needed, as specifically as possible
max_price_usdNoMost you (or your operator) would pay per request in USD if this existed, e.g. 0.01

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it discloses that requests are pooled across agents, that the most-wanted data gets sourced, that the call is free with no key, that it returns pointers plus a log id, and it sets a privacy constraint on inputs. It omits latency, whether the call is synchronous, and any rate limits, keeping it from a 5.

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

Conciseness4/5

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

The trigger is front-loaded in the first clause and the return/behavioral facts follow, so an agent gets the routing signal immediately. The first sentence is a long run-on enumeration, but each item is a distinct condition that earns its place, so the verbosity is functional rather than filler.

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?

There is no output schema, and the description compensates by explaining the return payload (pointers to sources plus a log id). For an 8-parameter submission tool it covers purpose, cost, privacy, and pooling behavior adequately; the main gap is that it never explains the interplay of private/max_price_usd/freshness, which the schema carries alone.

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 description coverage is 100%, so every one of the 8 parameters is already documented in the schema and the baseline is 3. The description adds no per-parameter semantics beyond the schema, aside from a general warning not to include personal data of private individuals.

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?

States a specific trigger-and-action contract: call this when data is unobtainable (403/429, CAPTCHA, login wall, no API, JS-only, PDF-only, not found) and it returns pointers to existing sources plus a log id. It is clearly distinguishable from the siblings report_failure and request_action, which are about reporting and acting rather than sourcing data.

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 when-to-use condition is exhaustively enumerated with concrete failure modes, which is unusually good routing guidance. However, it never names the sibling alternatives (report_failure, request_action) or states when this tool is the wrong choice, so it stops short of full when/when-not/alternative coverage.

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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