Skip to main content
Glama

rush_context_gain_stats

Retrieve real-time token economy savings and cost metrics to monitor resource usage and optimize spending.

Instructions

Get real-time token economy savings and cost metrics

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

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

  1. First observedv0.3.0

TDQS

B3.2/5.0
Behavior2/5

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

With no annotations, the description carries the full burden of behavioral disclosure. 'Get' implies a read operation and 'real-time' indicates data freshness, but there is no mention of side effects, access requirements, rate limits, or what scope of data is covered, so behavioral transparency is minimal.

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 sentence with no filler; the key qualifier 'real-time' is front-loaded and every word contributes to identifying the metric. It is concise without being under-specified to the point of uselessness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool is simple with no parameters and an output schema exists, so invocation requirements are minimal. However, the description gives no sense of when this metric is relevant versus siblings like rush_token_outline, and the meaning of 'token economy savings' is left largely to inference.

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 and an empty input schema, so schema coverage is trivially complete. The description does not need to explain parameter behavior; for a no-parameter tool the baseline of 4 applies.

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 uses a specific verb ('Get') and names a concrete resource ('real-time token economy savings and cost metrics'), making the basic function clear. It does not explicitly distinguish itself from siblings like rush_token_outline or rush_context_retrieve, but the resource name is specific enough to identify the tool.

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 guidance about when to use this tool instead of a sibling such as rush_token_outline or rush_context_pack, nor any mention of context or conditions. The description provides no exclusionary information, so an agent receives no help with selection among the large family of rush_* tools.

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

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/jamesdsizemore/rush-cli'

If you have feedback or need assistance with the MCP directory API, please join our Discord server