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Dataconto: who buys company records and code

What a business tool's terms say about customer data

get_tool_terms
Read-onlyIdempotent

For business tools companies keep records in (chat, email, tickets, docs, CRM, call recordings, code hosts): who owns the customer's data, whether the vendor trains AI on it (generative and other models, by plan), whether it keeps aggregated use, what can be exported on which plan and by whom, how much history the plan keeps, and how long data stays after cancellation. Each answer is quoted word for word from the vendor's own terms, AI page, data processing addendum or help article, with the date read. "The terms don't say" means every contract was read and none answers; "Not read yet" means a document is still unread. Answers marked inferred are a reading of the text, not its words. Without a tool id it returns a short index (each tool's headline answers and its Dataconto page); name a tool for the quoted facts. Not legal advice.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_tool_terms"
  }
}

Input Schema

NameRequiredDescriptionDefault
planNoA plan name as the vendor spells it, e.g. "Free", "Enterprise".
toolNoTool id, e.g. "slack", "microsoft-365", "google-workspace", "salesforce", "notion". Omit for a short index of every tool's headline answers.
factsNofalse = headline answers only, no quoted facts. Default true when a tool is named, false otherwise.
fieldNoOne question: ownership, ai_training, aggregate_use, export, retention or after_cancel.
limitNoTools to return, default 20.
answerNoKeep tools whose headline answer has this token, e.g. opt_out with field=ai_training.
record_typeNoKind of record: slack-and-teams, email, support-tickets, jira-and-linear, crm, call-recordings, documents-and-sops.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • changedInput schema / properties / facts / description
      Previous value: -"false = headline answers only, no quoted facts. Default true."New value: +"false = headline answers only, no quoted facts. Default true when a tool is named, false otherwise."
    • changedInput schema / properties / tool / description
      Previous value: -"Tool id, e.g. \"slack\", \"microsoft-365\", \"google-workspace\", \"salesforce\", \"notion\". Omit to list every tool."New value: +"Tool id, e.g. \"slack\", \"microsoft-365\", \"google-workspace\", \"salesforce\", \"notion\". Omit for a short index of every tool's headline answers."
  2. Added

TDQS

A4.1/5.0
Behavior5/5

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

Beyond the annotations, the description provides substantial behavioral context: answers are quoted word for word, each includes the date read, inferred answers are marked as interpretation rather than quotation, and 'The terms don't say' versus 'Not read yet' have distinct meanings. It also discloses that this is not legal advice, which is important operational context for how results should be treated.

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 description is dense but mostly front-loaded with the domain and questions it answers. The first sentence is very long and could be easier to scan, but the remaining sentences each carry useful qualification or output-mode information.

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?

For a seven-parameter tool without an output schema, the description is complete enough: it explains the index versus quoted-facts modes, provenance and dating of quotes, inferred versus verbatim answers, and the meaning of gaps in coverage. It also sets appropriate expectations with the not-legal-advice caveat.

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 the input schema already documents the parameters and enum meanings thoroughly. The description adds mode-level context about omitting the tool id and naming a tool, but it does not add much parameter-specific meaning beyond what the schema already provides.

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

Purpose4/5

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

The description clearly states that this tool returns vendor terms facts about customer data ownership, AI training, aggregate use, export, retention, and post-cancellation retention, with quoted evidence. It is specific about the resource and questions, but it does not explicitly distinguish itself from siblings such as deletion_clock or rights_check, which may overlap with retention and ownership/export topics.

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 explains two usage modes: omitting a tool id returns a short index, while naming a tool returns quoted facts. That is clear invocation guidance, but it does not explicitly say when to prefer this tool over related siblings or when not to use it.

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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