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Glama

health_check

Verify backend health, identify the active embedding provider, and retrieve per-sector memory counts and average salience.

Instructions

Backend health, embedding provider in use, and per-sector counts/average salience.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A3.5/5.0
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 usefully discloses what the report surfaces (backend status, embedding provider, sector counts/salience), but never states that it is a side-effect-free read, whether it requires auth, or whether it is expensive/rate-limited. A health check is conventionally safe to call, so this is a moderate rather than severe gap.

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?

A single front-loaded sentence that enumerates exactly the three things returned, with no filler or redundancy. Every clause 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?

With no parameters and an output schema present, the description need not explain return values, and it correctly orients the agent to a read-only diagnostic. The only shortfall is the absence of any usage context, which is minor for a zero-argument health probe.

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 is the baseline-4 case. Nothing about arguments needs explaining, and 100% schema coverage leaves no ambiguity.

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 names a specific resource (backend health) and enumerates the report's contents: embedding provider and per-sector counts/average salience. That clearly separates it from the CRUD/search siblings, though it reads as a noun-phrase output list rather than an explicit verb+resource statement.

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

Usage Guidelines2/5

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

There is no when-to-use guidance, no mention of when a diagnostic check is appropriate (e.g. troubleshooting, startup validation), and no reference to alternatives. Usage is only implied by the tool name.

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