Signed

delete_document

DestructiveIdempotent

Remove a document from a company's or pitch's data room, for good: the file is purged from storage and there is no undo, so confirm with the user before calling this. Give the document's id from list_documents and the slug it belongs to. Two kinds of document are refused rather than guessed at: files that arrived on a founder update (they belong to the update, and the web app doesn't remove them from the data room either), and files a transaction was recorded from (the web app deletes those transactions along with the file, which is a change to do there, where the user can see what goes).

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": {
      "company": "<company>",
      "id": "<id>"
    },
    "name": "delete_document"
  }
}

Input Schema

Name	Required	Description	Default
`id`	Yes	The document's id, from list_documents.
`company`	Yes	Company or pitch the document belongs to, by slug.

Schema Changelog

Changes observed during successful MCP inspections.

AddedOct 8, 2026

TDQS

A4.6/5.0

Behavior5/5

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

Beyond the destructiveHint/openWorldHint annotations, the description discloses that the file is purged from storage with no undo, and documents two refusal conditions (founder-update files, files with recorded transactions) plus what the web app does in each case. This is exactly the extra context annotations cannot carry.

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?

Front-loads the action and the destructive warning before the procedural details, and every sentence carries information. It is somewhat long as a single dense paragraph, which slightly hurts scannability.

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

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers the mutation's irreversibility, the prerequisites (id from list_documents, slug), and the refusal edge cases. With no output schema, nothing an agent needs to call this correctly is missing.

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 both parameters are already documented, including that the id comes from list_documents and that company is a slug. The description restates this, adding no new syntax or format detail. Baseline 3 applies.

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 verb and resource with scope: removes a document from a company's or pitch's data room. It is clearly distinguishable from upload_document and list_documents, the siblings it could be confused with.

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?

Explicitly instructs to confirm with the user before calling, and names two categories of documents that will be refused rather than handled, routing the agent to the web app for those cases instead. This is genuine when/when-not guidance with alternatives.

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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