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token_cost_estimate

Read-onlyIdempotent

Estimate wall-clock time and dollar cost for any LLM token usage. Combines token counts with model-specific pricing to output cost breakdowns and time estimates.

Instructions

Estimate wall-clock time AND dollar cost for LLM token usage.

Combines token-to-time mapping with model-specific pricing data. Returns cost breakdown (input/output/overhead) alongside the time estimate.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tokensYesTotal number of tokens in the LLM request (prompt + completion).
modelYesLLM model identifier. Unknown models fall back to generic estimates.
tool_callsNoNumber of tool calls expected in the agentic loop.
reasoning_depthNoExpected depth of chain-of-thought reasoning.moderate
task_typeNoOptional task type for feedback matching.
Behavior4/5

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

Annotations already declare readOnlyHint, destructiveHint, and idempotentHint. The description adds value by explaining the estimation approach (combines token-to-time mapping with pricing) and the output structure (cost breakdown and time estimate). No contradictions.

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 two sentences with no wasted words. The first sentence states the purpose clearly, the second explains the mechanics and output. It is front-loaded and efficient.

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?

Given the tool has 5 parameters and no output schema, the description adequately covers the output and basic behavior. Missing details like handling of unknown models or edge cases, but overall sufficient for a straightforward estimation tool.

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%, so baseline is 3. The description does not add parameter-level meaning beyond the schema; it mainly focuses on output. No extra semantics for tokens, model, or other fields.

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 explicitly states the tool estimates 'wall-clock time AND dollar cost' for LLM token usage, with a specific verb and resource. It distinguishes itself from sibling tools like cocomo_estimate (software cost) and token_time_bridge (likely just time) by clearly targeting LLM token scenarios.

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 LLM token cost/time estimation but provides no explicit guidance on when to use this tool versus alternatives like token_time_bridge or cocomo_estimate. No when-not-to-use or exclusion criteria are mentioned.

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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