Skip to main content
Glama

rush_complexity

Measure Python and JS/TS code complexity at a path using radon or jscpd. Returns 'skipped' status when engines are missing.

Instructions

Measure Python and JS/TS complexity at . Uses radon or jscpd; missing engines return status='skipped'.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
rawNo
toolNo
engineNo
statusNo
metricsNo
summaryNo
findingsNo
metadataNo
artifactsNo
duration_msNo
review_kindNo
engine_versionNo
review_providerNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.2.2
    • changedOutput schema / properties / metrics / anyOf
      Previous value: -[
      -  {
      -    "additionalProperties": {
      -      "anyOf": [
      -        {
      -          "type": "integer"
      -        },
      -        {
      -          "type": "number"
      -        },
      -        {
      -          "type": "string"
      -        }
      -      ]
      -    },
      -    "type": "object"
      -  },
      -  {
      -    "type": "null"
      -  }
      -]New value: +[
      +  {
      +    "additionalProperties": {
      +      "anyOf": [
      +        {
      +          "type": "integer"
      +        },
      +        {
      +          "type": "number"
      +        },
      +        {
      +          "type": "string"
      +        },
      +        {
      +          "type": "null"
      +        }
      +      ]
      +    },
      +    "type": "object"
      +  },
      +  {
      +    "type": "null"
      +  }
      +]
  2. First observedv0.3.0

TDQS

A4/5.0
Behavior4/5

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

With no annotations provided, the description must disclose behavior itself. It does so by naming the engines (radon or jscpd) and the skip fallback when engines are missing. Although it does not explicitly state that the operation is read-only, 'measure' plus the 'status='skipped'' behavior imply a non-mutating analysis.

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 tight sentences front-load the core action and then add only essential engine and fallback detail. No wasted words or redundant schema repetition.

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 single-parameter measurement tool, the description covers purpose, engines, and failure behavior. An output schema exists, so return-value documentation is not required from the description. The only missing piece is explicit usage guidance, which is already captured in the usage_guidelines dimension.

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 description coverage is 0%, so the description must clarify the path parameter. It does so minimally by identifying <path> as the target of complexity measurement and implying Python/JS/TS code, but it does not specify whether path should be a file or directory or give any path-formatting rules. The single generic path parameter leaves little ambiguity, but the description could add more value.

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 first clause names a specific action ('Measure'), a resource type ('Python and JS/TS complexity'), and a target ('at <path>'). Among the many rush_* siblings, this is the only one concerned with complexity measurement, so it is clearly differentiated.

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

Usage Guidelines3/5

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

The description implies use when complexity measurement is needed, but it gives no explicit when-to-use or when-not-to-use guidance and does not name alternatives such as rush_review or rush_lint. The engine and fallback sentence is behavioral, not usage direction.

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