Approve a production job awaiting review and move it to completed, confirming the art passes quality checks.
Approve a production job that is awaiting approval, moving it to completed.
| Name | Required | Description | Default |
|---|---|---|---|
| job_id | Yes | Production job ID |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries full behavioral disclosure. It states the primary effect (approving and moving to completed) but lacks any mention of side effects, failure conditions, reversibility, or authorization requirements. For a mutation tool, this is minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no redundant words. It front-loads the action and outcome, making it easy for an agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with no annotations and no output schema, the description is incomplete. It does not mention what the tool returns, what happens if the job is not in an 'awaiting approval' state, or potential errors. The agent may be left uncertain about the behavior in edge cases.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage for the single parameter job_id, which is described as 'Production job ID'. The tool description does not add any extra semantic detail about this parameter, so the baseline of 3 is appropriate since the schema already documents it.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'approve', the resource 'production job', and the outcome 'moving it to completed'. It is specific enough to distinguish from asset approval (art.asset.approve) by specifying 'production job'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is used when a production job is 'awaiting approval', which is a context cue. However, it does not explicitly mention alternatives like art.production.start or art.asset.approve, nor does it state when not to use this tool. Thus, usage is only implied, not fully guided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.