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Reports which credential source nanobanana-mcp uses—Gemini API key, Vertex AI Express Mode, or ADC—without exposing secrets, and shows basic runtime details to debug setup.

Instructions

Reports which credential source nanobanana-mcp is using (Gemini API key, Vertex AI Express Mode API key, or Vertex AI / Gemini Enterprise Agent Platform ADC) without revealing secrets, plus basic runtime info. Useful for debugging setup.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.6/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses an important behavioral trait – that it does not reveal secrets – and describes return content (credential source + runtime info). It does not state read-only safety explicitly, but the read-only nature is strongly implied by 'Reports ... without revealing secrets.'

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?

Two sentences, front-loaded with what is reported and the key constraint (no secrets revealed). Slightly wordy in enumerating credential source names, but each sentence earns its place.

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 zero-parameter, no-output-schema status tool, the description covers what it returns (credential source and runtime info) and a debug use case. It is largely complete, though it could note whether it requires auth or always succeeds.

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 tool takes zero parameters, which per rubric yields a baseline of 4. No parameter documentation is needed, and the description correctly implies a no-argument call.

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?

States a specific verb ('Reports') and resource ('credential source ... plus basic runtime info'), and enumerates the three possible credential sources, which is concrete. It doesn't explicitly distinguish itself from siblings, but none of the siblings (generate_image, edit_image, list_models, etc.) overlap in purpose, so misidentification is unlikely.

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?

Ends with 'Useful for debugging setup,' which implies the when-to-use context. However, it doesn't state when NOT to use it or name alternatives, and the guidance is vague rather than an explicit trigger condition.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.