embedded-docs

request_document

Request that a document be ADDED to the corpus - use this when search_docs returns 'no confident match' for material it should cover (a standard, protocol spec, SCPI or instrument manual, MCU / hardware datasheet, or library reference). This does NOT search; use search_docs for that. Pass ONE string with as much as you know: the document title or standard number, a URL if you have one, the edition / version, and what you were looking for. Requests are reviewed and the document is typically added within 24 hours.

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": {
      "request": "<request>"
    },
    "name": "request_document"
  }
}

Input Schema

Name	Required	Description	Default
`effort`	No
`request`	Yes

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedJun 19, 2026

TDQS

A4.4/5.0

Behavior4/5

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

With no annotations, the description carries the full burden of behavioral transparency. It discloses that requests are human-reviewed and typically fulfilled within 24 hours, and clarifies the tool does not perform searches. Although it doesn't describe side effects or idempotency, the given context (review process, timeline) is valuable and above the bare minimum.

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?

The description is compact and efficiently structured. The first sentence states the purpose, the second gives the usage condition, the third provides parameter content, and the fourth describes the outcome. Every sentence earns its place with no redundancy.

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, the description covers the core aspects: what it does, when to use it, what to provide, and what happens after. The main gap is the undocumented `effort` parameter, which the agent would not know about, and potential error cases are not mentioned. However, the tool is simple and the output schema may clarify return values.

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 0%, so the description must compensate. It thoroughly explains the `request` parameter ('Pass ONE string with as much as you know...'), but entirely omits the `effort` parameter. The phrase 'Pass ONE string' may misleadingly imply there is only one parameter, leaving the agent uninformed about `effort`.

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 states the action ('Request that a document be ADDED to the corpus') and explicitly contrasts with search_docs ('This does NOT search; use search_docs for that'), making it distinct from the sibling tool. It also lists concrete document types it covers, leaving no ambiguity about its purpose.

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

Usage Guidelines5/5

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

Usage is precisely defined: 'use this when search_docs returns no confident match' and explicitly excludes the search use case. It provides a list of acceptable document categories and instructs on what to include in the request, giving strong guidance on when and how to use the tool.

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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