Skip to main content
Glama

Ask a model

ask

Send a question or task to Leanfare and receive the answer plus its cost; Auto selects the cheapest suitable model by default, or name a model to use one.

Instructions

Ask a question through Leanfare and get the answer with its cost. By default Leanfare's Auto picks the cheapest model the user ticked that rates well for the task; name a model to use that one. The cost counts toward the user's budget.

Input Schema

NameRequiredDescriptionDefault
modelNoauto (the default), auto-save, auto-balanced, auto-best, or a model id from the models tool, such as google/gemini-3.8-flash.
promptYesThe question or task, with everything the model needs to answer it.
systemNoInstructions for the model (a system prompt).
max_tokensNoThe longest answer to allow, in tokens.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.15.1

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already disclose openWorldHint=true, non-idempotent, non-destructive, and not read-only, so the mutation/cost framing is consistent. The description adds real context beyond those annotations: the response includes cost and the cost counts toward the user's budget, which is a meaningful side effect an agent should know before calling. It does not cover rate limits or failure modes, so not a 5.

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?

Three tight sentences: what it does, how model selection works, and the billing consequence, with the core action front-loaded. Every sentence carries information and none is filler.

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 four-parameter tool with no output schema, the description covers the action, the model-selection default, and the cost side effect, which is what an agent needs to invoke it correctly. Minor gaps remain around what the returned payload looks like beyond 'the answer with its cost', but overall it is sufficient.

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%, so every parameter is already documented, including the 'auto' default and the valid auto variants. The description only restates the Auto-vs-named-model behavior already present in the 'model' parameter description, adding little new meaning beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource ('Ask a question through Leanfare and get the answer with its cost'), so an agent knows this is a model-invocation tool that also returns billing information. It does not explicitly distinguish itself from siblings like 'delegate', 'estimate', or 'plan', which a 5 would require.

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?

It gives useful conditional guidance for model selection: the default Auto picks the cheapest ticked model that rates well for the task, and naming a model overrides that. However, there is no explicit guidance on when to use this tool rather than siblings such as 'estimate', 'trial', or 'delegate', leaving that to inference.

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