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request_approval

Ask for one of the two fine-tuning approvals. training_spend names the job and the cap being approved (it must equal the job's own cap); production_switch needs a job with a passing protected gate verdict and a servable model, and takes jobId only when more than one candidate qualifies. Executes nothing and decides nothing: the request waits for decide_approval. Scope: write.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
noteNoContext for whoever decides (max 500 characters)
jobIdNoRequired for training_spend; optional for production_switch
scopeYes
capUsdNoRequired for training_spend: the cap being approved, in USD
projectIdYesFine-tuning project ID from list_fine_tuning_projects
customerIdNo(Converra superadmin only) Target customer ID

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.7/5.0
Behavior5/5

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

Annotations only say readOnlyHint=false/destructiveHint=false. The description adds substantive behavior: it 'Executes nothing and decides nothing' and the request waits for decide_approval, clarifying it is a non-side-effecting write-pending action, plus prerequisite gates for each scope. This is real value beyond the annotations, with no contradiction.

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?

Three dense sentences, front-loaded with the core purpose and then per-scope rules and the downstream handoff. No wasted prose, though the packed phrasing requires careful reading.

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 6-parameter write tool with no output schema, the description covers prerequisites, the two scopes, and the follow-up flow well. Minor gaps remain on the note and superadmin-only customerId semantics, but nothing critical is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is high (83%), so baseline is 3, but the description adds constraints the schema lacks: capUsd must equal the job's own cap, and jobId for production_switch is conditional on more than one qualifying candidate. That meaningfully supplements the schema without fully documenting note/customerId.

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?

States a specific verb+resource ('Ask for one of the two fine-tuning approvals') and enumerates the two scopes (training_spend, production_switch). It explicitly names the downstream decision tool decide_approval, so an agent can distinguish it from siblings without opening the schema.

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?

Gives explicit per-scope conditions: training_spend requires jobId and a cap equal to the job's own cap; production_switch needs a passing protected gate verdict and a servable model, with jobId only when multiple candidates qualify. It also routes the agent to decide_approval for the actual decision.

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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