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list_pending_approvals

Read-only

Fine-tuning approvals waiting on a decision, and which job each one is for. Training spend and the production switch are decided by a human on the project screen, or through decide_approval by a key that holds the approve scope — write, admin and superadmin keys cannot decide one. Answers: 'what is blocked on me?', 'why has training not started?'.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
customerIdNo(Converra superadmin only) Target customer ID

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description's added behavioral content (approve-scope requirement, that write/admin/superadmin keys cannot decide) pertains mostly to the sibling decide_approval rather than to this tool's own behavior, and it says nothing about result ordering, pagination, or volume.

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?

Purpose is front-loaded in the first clause, and the following sentences add authorization and intent context. Slightly wordy in its focus on the decision path, but no sentence is pure 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?

With no output schema, the description compensates by indicating what each row represents ('which job each one is for') and the questions it answers. It is complete enough for an agent to call and interpret a read-only list, though it omits pagination/ordering details.

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 single customerId parameter is fully documented as superadmin-only in the schema. The description adds no further meaning beyond what the schema already provides, so the 3 baseline is appropriate.

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 and resource (fine-tuning approvals waiting on a decision) plus a scope qualifier, and adds the return content ('which job each one is for'). This clearly separates it from siblings like decide_approval or list_fine_tuning_projects.

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?

Names the alternative tool (decide_approval) and explains who is permitted to act, giving the agent the routing context. It frames intent with 'what is blocked on me?'/'why has training not started?', though it stops short of an explicit when-not-to-use statement.

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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