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jacksonnnzzz

leam-opt-mcp

by jacksonnnzzz

approve_antenna_engineering_assumption

Approve the exact hash-frozen engineering assumption post-review, finalizing the candidate for antenna modeling.

Instructions

Approve the exact hash-frozen engineering assumption candidate after user review.

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?

No annotations are provided, so the description bears full responsibility for disclosing behavioral traits. It indicates the action and a constraint (hash-frozen), but does not explain side effects (e.g., state changes, downstream triggers), permissions required, reversibility, or whether the approval is idempotent. This is a significant gap for an approval action.

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, well-structured sentence with no redundant words. It front-loads the verb and object, making it immediately understandable.

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 a simple signature (2 string params) and an output schema, the description lacks sufficient context about prerequisites (e.g., prior propose step), how this approval integrates with sibling tools, and what constitutes a valid approval hash. The 'after user review' hint is the only contextual anchor, which is insufficient for a mutating workflow step.

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

Parameters2/5

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

The schema descriptions are empty (0% coverage), so the description must compensate. It hints at a hash ('exact hash-frozen') for approval_hash but does not explain the role of job_id or the format/relationship between the two parameters. An agent would be unclear what values to supply.

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 clearly states the action ('Approve') and the specific object ('exact hash-frozen engineering assumption candidate'), which distinguishes it from sibling tools like 'approve_antenna_source' or 'propose_antenna_engineering_assumption'. The qualifiers 'exact hash-frozen' and 'after user review' add precision, though it doesn't explicitly list alternative tools.

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?

The phrase 'after user review' implies a specific point in the workflow, providing some context for when to use the tool. However, there is no explicit guidance on when not to use it or what alternatives (e.g., approve_antenna_source, compile_reviewed_antenna_model) might be more appropriate.

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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