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estimate_job

Estimate the cost of a fine-tuning job before submitting it. Returns estimated cost, cost range, current balance, and balance sufficiency. Always run this before creating a job to avoid insufficient funds.

Instructions

Get a cost estimate for a fine-tuning job before submitting it. Returns estimated cost, cost range, current balance, and whether balance is sufficient. Always estimate before creating a job.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
base_modelNoHuggingFace model ID (e.g. 'Qwen/Qwen2.5-Coder-7B-Instruct'). Required unless base_user_model_id is provided.
base_user_model_idNoID of a previously trained model. The base model is resolved automatically.
num_epochsNoTraining epochs
max_examplesNoMaximum examples
repo_size_mbNoApproximate repository size in MB (helps refine the estimate)
use_caseNoAgent to use for the estimate (e.g. 'code_repo' for Cody, 'sera_code_repo' for SIERA). Defaults to code_repo.
Behavior4/5

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

No annotations are present, so the description fully bears responsibility. It discloses return information (estimated cost, cost range, current balance, sufficiency). It does not mention side effects (likely none) or authorization, but the read-only nature is implied.

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 consists of two concise sentences with no redundant information. It front-loads the core purpose and includes a directive.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With 6 parameters and no output schema, the description could be more complete by specifying the return format or units. It lists return items but lacks detail like how errors are handled.

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 the baseline is 3. The description adds no additional parameter meaning beyond what the schema already provides (e.g., 'HuggingFace model ID').

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 action ('Get a cost estimate'), the resource ('a fine-tuning job'), and the purpose ('before submitting it'). It distinguishes from sibling tools like estimate_evaluation by specifying the job type.

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 explicitly advises 'Always estimate before creating a job,' providing clear when-to-use guidance. It does not specify when not to use, but the context implies it's a prerequisite step.

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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