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Verify credentials and upstream reachability

gemini_healthcheck
Read-onlyIdempotent

Diagnoses why a Gemini API tool failed: resolves credentials, calls generativelanguage.googleapis.com, and reports whether the credential was accepted, latency, and a plain-English cause.

Instructions

Resolves the credential the way real tools do, then makes one authenticated request to generativelanguage.googleapis.com. Reports which source supplied the credential, whether generativelanguage.googleapis.com accepted it, the round-trip time, and a plain-English hint distinguishing 'no credential' from 'credential rejected' from 'a generativelanguage.googleapis.com-side problem'. Call this when a real tool fails and you want to know which hop broke. Read-only; never returns the credential itself.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Addedv1.12.0

TDQS

A4.6/5.0
Behavior5/5

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

Beyond the readOnlyHint and idempotentHint annotations, the description discloses valuable behavioral details: it resolves the credential the way real tools do, performs exactly one authenticated request, reports credential source and acceptance, measures round-trip time, and explicitly states it never returns the credential itself.

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 well-structured, starting with what the tool does, then what it reports, then when to call it, and ending with safety. It is somewhat dense but every sentence contributes useful information; no filler or repetition.

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?

With no output schema, the description carries the full burden of explaining return semantics, and it does: it enumerates the reported items (credential source, acceptance, round-trip time, plain-English hint) and the three failure categories. Combined with zero parameters and strong annotations, nothing essential is missing.

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 has zero parameters, so the baseline is 4. The description adds useful context by explaining that it resolves the credential the way real tools do, which gives the agent a mental model without needing any parameter documentation.

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 states a specific verb and resource: it 'makes one authenticated request to generativelanguage.googleapis.com' and reports health information. It clearly distinguishes itself from sibling tools by its diagnostic purpose, describing it as a healthcheck that determines which hop broke when a real tool fails.

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 gives an explicit usage condition: 'Call this when a real tool fails and you want to know which hop broke.' This is clear guidance for when to use the tool, though it does not explicitly name alternatives or provide when-not-to-use conditions.

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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