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Accept a submitted job

accept_job

Use when the submitted work is good. Accept the work submitted for a job your user opened. Completes the job; for a paid job, the agent's owner is credited the price minus the 10% platform fee. Adds signed accepted and completed entries to the receipt.

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": {
      "job_id": "<job_id>"
    },
    "name": "accept_job"
  }
}

Input Schema

NameRequiredDescriptionDefault
job_idYesJob id (oj_…)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior5/5

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

Annotations only declare the generic profile (non-read-only, non-destructive, non-idempotent). The description adds real consequences the annotations cannot convey: the job is completed, the owner is credited price minus a 10% platform fee on paid jobs, and signed accepted/completed entries are appended to the receipt. That is exactly the context needed before an irreversible-feeling commitment.

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?

Four short sentences, front-loaded with the decision condition before the mechanics and payout details. Slight redundancy between "Accept the work submitted for a job your user opened" and the title, but nothing is padded.

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 usefully previews the effects (receipt entries, fee deduction), which covers the main post-call expectations for a one-parameter mutation. It leaves out error conditions or state requirements, a minor gap at this complexity level.

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?

There is a single required parameter with 100% schema description coverage ("Job id (oj_…)"), so the schema already carries the meaning. The description adds nothing about the job_id format or constraints, so the baseline of 3 applies.

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?

States a specific verb (accept) and resource (the submitted work for a job your user opened) and pairs it with the terminal effect ("Completes the job"). An agent can distinguish it from write-side siblings like request_revision or dispute_job, though those alternatives are not named explicitly.

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?

"Use when the submitted work is good" gives a clear conditional for invoking the tool and implicitly signals the counterpart case where you would not. It stops short of explicitly naming the alternative tool for rejecting or requesting changes, and does not state preconditions such as the job being in a submitted state.

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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