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ghost_stats

Retrieve cache and grounding telemetry to diagnose slow or unreliable flows. Identify winning tier, VLM escalation rate, cache hit/miss counts, and UIA-mirror stats.

Instructions

Grounding + cache telemetry for debugging flow speed/reliability: which tier is winning (cache/UIA/OCR/VLM), VLM escalation rate, cache hit/miss counts, UIA-mirror stats. Call when a flow is slow or a find is unreliable.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

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

  1. First observedv0.23.4

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations, the description carries the full burden of explaining behavior. It does so by describing that this is telemetry for debugging, listing the metrics returned, and implying a non-mutating read-only role. It stops short of explicitly stating 'no state changes' or describing the output format, but those are not hidden given the tool's zero-parameter stats nature.

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?

Two sentences carry all the needed information: what the tool reports, which metrics are included, and when to call it. The description is front-loaded with the core purpose and contains no filler or repeated schema content.

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 read-only telemetry tool, the description is nearly complete: it names the resource, metrics, and call triggers. There is no output schema, so a sentence about the return shape would fully close the last gap, but the description's explicit metric list leaves little ambiguity for correct selection and invocation.

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 empty input schema already exhaustively describes the parameter surface. The description adds no parameter detail, but none is needed; with 0 params this is the baseline 4 case.

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 identifies a concrete diagnostic resource — grounding and cache telemetry — and enumerates the specific metrics it exposes (which tier is winning, VLM escalation rate, cache hit/miss counts, UIA-mirror stats). This clearly distinguishes ghost_stats from the action-oriented sibling tools (ghost_tab_click, ghost_act, etc.), so an agent can tell what it is for without opening schemas.

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?

It gives explicit trigger conditions: 'Call when a flow is slow or a find is unreliable.' This is strong usage guidance for a diagnostic tool. It does not mention alternatives or exclusions, but among the siblings there is no other stats/telemetry tool, so the context is sufficient.

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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