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chimera_cost_estimate

Estimate token count and USD cost for text or messages without an API call. Supports Claude, GPT, and Gemini models for accurate cost projections.

Instructions

Estimate token count and USD cost for text or messages. No API call. Supports Claude, GPT, Gemini models.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textNoRaw text to estimate. Use instead of messages for single strings.
messagesNoMessage list [{role, content}] to estimate. Use instead of text.
modelNoModel name. Default: claude-sonnet-4-6. Supported: claude-opus-4-7, claude-sonnet-4-6, claude-haiku-4-5, claude-opus-4-5, claude-sonnet-4-5, claude-haiku-3-5, gpt-4o, gpt-4o-mini, gpt-4-turbo, gemini-1.5-pro, gemini-1.5-flashclaude-sonnet-4-6
output_tokensNoExpected output tokens (for total cost). Default 0 (input only).
Behavior3/5

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

No annotations exist, so the description carries full burden. It discloses the tool does not make API calls, which is good, but lacks details on accuracy, limits, or other behavioral traits.

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 exceptionally concise—two sentences covering purpose, key feature (no API call), and supported models. No filler or redundant information.

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 simple estimation tool, the description is largely complete. It covers what, how (no API call), and supported models. However, it does not mention that cost estimates are approximate or any caveats.

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 coverage is 100%, and the description does not add extra meaning beyond the schema. Baseline 3 is appropriate as the schema already documents all parameters.

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 estimates token count and USD cost for text or messages, specifies it makes no API call, and lists supported model families (Claude, GPT, Gemini). This distinguishes it from sibling tools like chimera_cost_track (actual cost tracking) and chimera_budget (budget management).

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?

The description provides clear context (estimates without API call, supports specific models) but does not explicitly state when not to use or mention alternatives. It implies usage for cost planning before actual API calls.

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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