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agentlabbusiness

raposa-mcp

Official

get_approval

Look up an approval by ID to see if a human approved it. Verify the decision status before continuing with a high-stakes action.

Instructions

Read an approval by id. Look at approved — it is true only when a human approved.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
approval_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.1

TDQS

A4.1/5.0
Behavior4/5

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

No annotations are provided, so the description carries the disclosure burden. It correctly indicates a read operation and adds useful field-level behavior: 'approved' is true only when a human approved. This goes beyond a generic 'get by id' and clarifies an important semantic detail.

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 two tight sentences with no filler. The core operation is front-loaded, and the second sentence adds a valuable semantic nuance about the 'approved' field.

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?

For a single-parameter read tool with an output schema available, the description is mostly complete. It states the purpose, the lookup key, and the key field semantics. The only small gap is not explicitly documenting the approval_id parameter beyond 'by id,' but the input schema already makes that required parameter visible.

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?

Schema description coverage is 0%, and the description only implicitly references the parameter through 'by id.' It does not directly explain that approval_id is the approval's unique identifier or provide any format expectations, leaving the agent to infer the mapping.

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 uses a specific verb and object: 'Read an approval by id.' This clearly identifies the operation and resource, and it is easy to distinguish from the sibling tools create_approval and request_human_approval, which are write/request operations rather than reads.

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 gives clear context: use this tool when you need to read an approval by its id. It does not explicitly name alternatives or state when not to use them, but the read-versus-create/request distinction is clear enough from the sibling names.

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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