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usage_breakdown

Analyzes token allocation across task categories, MCP server calls, and core tools to identify usage patterns.

Instructions

Show where Claude Code tokens go: task category breakdown (coding, debugging, feature, refactoring, testing, exploration, planning, delegation, git, build_deploy, conversation, brainstorming), MCP server call counts, and core tool usage. Inspired by Codeburn. No API key required.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "usage_breakdown"
  }
}

Input Schema

Name	Required	Description	Default
`period`	No	Time period (default: all)

Schema Changelog

Changes observed during successful MCP inspections.

First observedv4.4.0Jun 8, 2026

TDQS

A4.1/5.0

Behavior4/5

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

With no annotations, the description carries the full burden. It clearly indicates a read-only operation (no side effects) requiring no authentication, and specifies the output content (task categories, MCP counts, tool usage). This is transparent enough for an agent to understand behavioral traits, though more detail on data freshness or potential rate limits could improve it.

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?

The description is a single sentence that immediately states the purpose and lists key output elements. It is front-loaded, concise, and contains no filler or redundant information.

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 simple informational tool with one optional parameter and no output schema, the description is complete. It explains what the tool returns, lists all relevant categories, and notes the lack of authentication requirements. No additional context is needed.

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?

The input schema has one optional parameter 'period' with enum values and a description. Schema coverage is 100%, so the description adds no additional meaning beyond what the schema provides. Baseline score of 3 is appropriate.

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 shows token usage breakdown by task category, MCP server calls, and core tool usage. It distinguishes from sibling tools like usage_stats and usage_dashboard by specifying the categorical breakdown and noting 'No API key required,' which differentiates it from other diagnostic tools.

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 usage for understanding token allocation but does not explicitly state when to use this tool versus alternatives (e.g., usage_stats, usage_dashboard). The mention of 'No API key required' offers a hint but no formal guidance on use cases or exclusions.

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