Disco

discovery_account

Read-only

Check your Disco account status to verify plan details, available credits, and payment method before running private data analysis.

Instructions

Check your Disco account status.

Returns current plan, available credits (subscription + purchased), and
payment method status. Use this to verify you have sufficient credits
before running a private analysis.

Args:
    api_key: Disco API key (disco_...). Optional if DISCOVERY_API_KEY env var is set.

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": "discovery_account"
  }
}

Input Schema

Name	Required	Description	Default
`api_key`	No

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Apr 13, 2026

TDQS

A4.7/5.0

Behavior4/5

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

The annotations already declare readOnlyHint=true, indicating a safe read operation. The description adds valuable context beyond this by specifying the return data (plan, credits, payment method status) and the practical use case for credit verification, which helps the agent understand the tool's behavioral output and purpose. No contradiction with annotations exists.

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 well-structured and front-loaded with the core purpose, followed by return details, usage guidance, and parameter explanation. Every sentence earns its place without redundancy, making it efficient and easy to parse.

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?

Given the tool's low complexity (1 optional parameter), the presence of annotations (readOnlyHint) and an output schema (which handles return values), the description is complete. It covers purpose, usage, parameter semantics, and behavioral context adequately without needing to explain return values.

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

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 1 parameter with 0% description coverage, but the description compensates by explaining the api_key parameter's purpose (Disco API key), format hint ('disco_...'), and optionality condition (can use env var instead). This adds meaningful semantics beyond the bare schema.

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 specific action ('Check your Disco account status') and resource ('Disco account'), and distinguishes it from siblings by focusing on account status verification rather than analysis, payment, or other operations. It explicitly mentions what information is returned (plan, credits, payment method status).

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?

The description provides explicit guidance on when to use this tool ('to verify you have sufficient credits before running a private analysis'), which clearly differentiates it from sibling tools like discovery_analyze (for analysis) or discovery_purchase_credits (for buying credits). It establishes a clear prerequisite context.

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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