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by io.chatcut
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read_billing

Read-onlyIdempotent

Read the signed-in account's current membership, included features and available credits. Optionally read its posted credit history with linked model/token usage; paginate using nextCursor. Positive amounts add credits; negative amounts remove credits. Missing transactions or usage do not establish zero cost. Returns conversation billing information when the runtime knows it; external subscription/API costs are not visible. Reading this tool has no separate fee or side effect, but model inference to make the call and answer may still cost credits. Use estimate_generation for a proposed operation, and track_progress for per-job charges. Generation quotes exclude other calls and future conversation. Never infer charges from balance differences.

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": "read_billing"
  }
}

Input Schema

NameRequiredDescriptionDefault
historyNoOmit for account overview only; pass {} for recent posted transactions and related usage.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
  2. First observed

TDQS

A4.5/5.0
Behavior5/5

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

Goes well beyond the readOnly/idempotent annotations by disclosing that the read itself is free but inference to make the call may cost credits, that external subscription/API costs are invisible, that missing transactions or usage do not establish zero cost, and that sign conventions are positive=add / negative=remove. These are non-obvious semantics an agent could easily get wrong.

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?

Front-loads the primary payload (membership, features, credits) before optional history and caveats; each later sentence carries a distinct caution. It is dense but not padded, though the string of caveats could be tightened slightly.

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?

With no output schema, the description takes on the burden of explaining returns and does so for the main payload (membership, features, credits, history with linked model/token usage, conversation billing when known). It stops short of describing the response shape or where nextCursor appears, leaving a small gap.

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 100%, including the omit-vs-pass-{} semantics for history and the before/createdAt/id cursor fields, so the baseline is 3. The description adds only the mention of nextCursor for pagination, which is mostly restating what the schema already explains.

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?

Opens with a precise verb+resource+scope: reads the signed-in account's membership, included features and available credits, and optionally its posted credit history. That is clearly distinct from cost-related siblings like estimate_generation and track_progress, which the description also names.

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?

Explicitly routes the agent: use estimate_generation for a proposed operation and track_progress for per-job charges, plus a caution against inferring charges from balance differences. The distinction between this read and those estimation tools is spelled out rather than implied.

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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