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glimind

by io.github.shawndei

check_tool_reliability

Call this BEFORE invoking any external MCP tool or API to check if it is working RIGHT NOW. Returns a verdict (healthy | degraded | down | unknown) plus the live success rate from real agent usage in the last hour, typical p50/p95 latency, top current error signatures, the tool's actual connection endpoint (MCP endpoint URL or package to launch — so you can call it without a registry lookup), whether it is FREE or PAID with the exact price and precisely how to pay (x402/USDC = auto-payable per call, no signup), and any active breakage. Use it to decide whether to call a tool, choose a fallback, or tune timeouts and retries — it prevents wasted calls and dead-ends on broken tools. Cheap and fast; safe to call routinely before tool use.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toolIdYesIdentifier of the tool to check: a server id (e.g. 'mcp-registry/acme') or 'server/tool_name' for a specific tool.

Schema Changelog

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

  1. First observed

TDQS

A4.6/5.0
Behavior5/5

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

With no annotations provided, the description carries the full burden. It discloses the tool's output (verdict, live success rate, latency, error signatures, endpoint, pricing, breakages), its non-destructive nature, and that it is cheap and fast. No contradictions.

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 relatively long but every sentence adds value. It is front-loaded with the main purpose and includes implementation details. Slightly verbose but still effective.

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?

For a tool with one parameter and no output schema, the description is very complete. It covers purpose, usage, return values, pricing, and even how to call the endpoint. No gaps left.

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 coverage for the single parameter is 100%, so the schema already documents the parameter well. The description does not add new information about the parameter beyond what the schema provides, hence baseline 3.

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 tool checks if an external MCP tool or API is working right now, with a specific verdict and live metrics. It uses a specific verb ('check') and resource ('tool reliability'), and distinguishes itself from sibling tools by being a pre-call reliability check.

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 explicitly says to call this before invoking any external MCP tool or API, and provides guidance on using it to decide whether to call a tool, choose a fallback, or tune timeouts. It also notes it is cheap and safe to call routinely.

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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TDQS

A4.3/5.0
Disambiguation5/5

Each tool has a distinct, well-defined purpose: checking reliability, discovering tools, finding alternatives, getting recipes, routing tasks, etc. No two tools overlap in function.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern with underscores (e.g., check_tool_reliability, route_task, watch_tool). The only minor deviation is 'how_to_use_glimind', which still follows a clear verb phrase convention.

Tool Count5/5

With 15 tools, the set is well-scoped for a comprehensive meta-layer covering discovery, reliability checking, preparation, batch routing, reporting, and notifications. Each tool earns its place.

Completeness4/5

The surface covers the full workflow of discovering, checking, preparing, calling, and reporting on tools. A minor gap is the lack of a direct 'list all tools' catalog, but the discovery tools effectively fill this need.

Resources