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Approve a training proposal

approve_training_proposal
Destructive

Approve a pending proposal, optionally with edited guidance text, so it joins the context document the AI agent reads before every answer. Owners, admins and support agents with Review agent training.

Input Schema

NameRequiredDescriptionDefault
proposedNoEdited guidance to approve instead of the proposed text.
proposalIdYesThe id from list_training_proposals.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

Annotations already declare destructiveHint=true and idempotentHint=false; the description adds genuine context by explaining the consequence — the approved text becomes part of the persistent context document used for every future answer, which signals permanence and scope of impact. It stops short of saying whether re-approval fails or overwrites, or where the proposal goes afterward.

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?

Two tight clauses with the action and its effect front-loaded, then permissions. No filler and nothing repeated from the title.

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 two-parameter mutation with annotations and no output schema, it covers what the tool does, the authorization needed, and the downstream effect on the agent's context. Missing only post-approval state of the proposal and any irreversibility note, which keeps it just under complete.

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 both parameters are already documented; the description only echoes that `proposed` is an optional edited replacement for the proposed text. No added syntax, format, or constraints beyond the schema. Baseline 3 applies.

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 (approve) and resource (a pending training proposal), plus the outcome — the guidance joins the context document the agent reads before every answer. That distinguishes it from dismiss_training_proposal and list_training_proposals without opening any schema.

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?

Gives real preconditions: the proposal must be pending and the caller must be an owner, admin, or support agent with Review agent training. It also conveys that the edit is optional. It does not name the alternative (dismiss_training_proposal) or state when not to approve, so routing is implied rather than explicit.

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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