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jacksonnnzzz

leam-opt-mcp

by jacksonnnzzz

approve_antenna_source

Approve a reviewed antenna source candidate to proceed with downstream HFSS model and code generation. Provide the job ID and approval hash to confirm.

Instructions

Approve the reviewed source candidate before downstream model/code generation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
job_idYes
approval_hashYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It indicates the approval is a step in a pipeline but does not mention side effects, whether the operation is idempotent, or any security requirements (e.g., the approval_hash). The phrase 'before downstream generation' gives a hint, but essential behavioral details are missing.

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?

The description is a single, front-loaded sentence with no filler. Every word contributes to the core purpose and timing, making it appropriately concise.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite having an output schema, the description is too thin for an approval action. It doesn't explain prerequisites (e.g., that the source must be analyzed, refined, and rechecked first), what it means to 'approve' beyond the step, or what the approval_hash validates. For a tool with sibling workflow steps, more context is needed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0% and the description provides no explanation of the two parameters (job_id and approval_hash). The approval_hash, in particular, is non-obvious and would benefit from a description of its role. The description does not compensate for the schema's lack of detail.

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?

The description clearly states the action ('Approve'), the resource ('reviewed source candidate'), and the context ('before downstream model/code generation'). It is specific enough to distinguish from sibling tools like approve_antenna_engineering_assumption, which targets a different artifact.

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?

The description conveys a clear temporal context: the approval happens after a source has been reviewed and before generation. However, it doesn't explicitly name alternatives or state when not to use the tool, which would push it to a 5.

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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