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by io.crunchjunkie.app
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list_data_sources

Read-only

List connected data sources (Google Ads, GA4, Meta, Search Console, etc.) across the workspace, optionally filtered to one client.

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": "list_data_sources"
  }
}

Input Schema

NameRequiredDescriptionDefault
clientIdNoRestrict to a single client id.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
    • removedInput schema / additionalProperties
      Removed value: -false
  2. First observed

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare the tool as read-only, non-destructive, and closed-world, which covers the safety profile. The description adds that it lists only *connected* data sources, which is useful behavioral context. However, it does not disclose return format, pagination, or any auth/rate-limit details, so it adds only modest value beyond the annotations.

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 a single well-structured sentence with zero waste. It front-loads the verb and resource, includes representative examples, and ends with the optional filter, making it easy to parse and act on.

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?

Given the tool's simplicity (one optional parameter, no output schema), the description covers what the tool does and its scope. The safety profile is fully handled by annotations, so the description need not elaborate there. A minor gap is the absence of any hint about what the returned list contains (e.g., IDs, names, types), but for a straightforward list tool this is not critical.

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%, with the single optional parameter clientId fully documented in the schema. The description's phrase 'optionally filtered to one client' mirrors the schema and adds no new semantics (e.g., format, expected values, or behavior when omitted). Baseline 3 is appropriate when the schema carries the parameter documentation.

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 states a specific verb ('List') and resource ('connected data sources') with concrete examples (Google Ads, GA4, Meta, Search Console). It also specifies workspace scope and optional client filtering, making the tool's purpose immediately clear. No sibling tool lists data sources, so explicit differentiation is not needed, but the description could have named a related sibling like list_clients to reinforce boundaries.

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

Usage Guidelines3/5

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

The description implies when to use the tool (to see connected data sources, optionally scoped to a client) but offers no explicit when-to-use versus when-not-to-use guidance, no alternatives, and no prerequisites or conditions. The usage is inferable from the purpose but not articulated.

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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