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Prosyo

by com.prosyo.app
OverviewDiscussionsAdmin

approve_review

Prepare approving people waiting in the review queue (run ids from list_review_queue). Approval researches them for credits; you still see the message before it is sent. Runs only after confirm_action.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "run_ids": "<run_ids>"
    },
    "name": "approve_review"
  }
}

Input Schema

NameRequiredDescriptionDefault
run_idsYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations indicate it is not read-only, not destructive, and not idempotent. The description adds that approval researches people for credits, you see the message before sending, and it only runs after confirm_action. This is good extra context, though it doesn't detail rate limits or errors.

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 short sentences packed with essential information: purpose, source of ids, side effects, visibility, and ordering. No wasted words.

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?

Given one required parameter, no output schema, and annotations covering safety, the description covers purpose, usage, and key side effects. It could be slightly more explicit about what the tool returns or whether approval is immediate versus queued.

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 0%, so the description must compensate. It names the parameter source (run ids from list_review_queue) and implies they are required and refer to review queue items. It doesn't fully describe the array format, but gives enough semantic meaning.

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 action: preparing approval for people waiting in the review queue, and clarifies that run_ids come from list_review_queue. This distinguishes it from siblings like list_review_queue or confirm_action, though it could more explicitly frame the overall workflow.

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?

It explicitly ties the tool to the review queue and list_review_queue, and states that it runs only after confirm_action. This gives a clear precondition and workflow 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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