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josephkamau32

ERP-lite MCP Server

approve_pending_requisition

Approve a pending purchase requisition by specifying the requisition ID and approving user. Requires human confirmation to authorize the purchase.

Instructions

Approve a pending purchase requisition. This MUST be triggered by a human.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
approved_byYes
requisition_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
statusYes
quantityYes
created_atYes
approved_atNo
material_idYes
requested_byYes
requisition_idYes
Behavior2/5

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

With no annotations provided, the description carries the full burden for transparency. It only discloses the human-trigger requirement, but does not mention side effects, irreversibility, permission requirements, or what the approval action entails. This is a significant gap for a mutation tool.

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 extremely concise with two sentences. The first states the purpose clearly, and the second emphasizes a critical human-in-the-loop constraint. Every word earns its place.

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?

This is an approval action with side effects, yet the description provides minimal context. It lacks prerequisites, postconditions, and any explanation of the approval workflow. The existence of an output schema may cover return values, but the overall description is insufficient for an AI agent to safely and correctly invoke the tool in a given context.

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 description coverage is 0%, and the description provides no explanations for 'requisition_id' or 'approved_by'. The parameter names are somewhat self-explanatory, but the tool does not compensate for the lack of schema documentation, leaving meaning entirely to inference.

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 a pending purchase requisition') with a specific verb and resource. It distinguishes itself from siblings like create_requisition and get_open_orders, and the extra note about human triggering adds clarity.

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 provides a clear usage constraint: it MUST be triggered by a human, implying it should not be used in automated flows. However, it does not explicitly name alternatives or conditions under which this tool is preferred over others.

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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