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procurement_po_approval_workflow

Destructive

Run the purchase order approval workflow by sending a message objective and optional structured inputs, routed under your JWT, tenant, and company scope.

Instructions

Run the procurement domain agent action po_approval_workflow.

Routes through the platform's domain-agent dispatcher under your JWT, tenant, and company scope.

Args: message: Free-text objective for the action. inputs: Optional JSON string of structured inputs for the action.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
inputsNo{}
messageNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.4/5.0
Behavior2/5

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

The description adds the useful detail that the action routes through the domain-agent dispatcher under the caller's JWT, tenant, and company scope, but it discloses nothing about the workflow's side effects. Given annotations already declare `destructiveHint: true` and `idempotentHint: false`, the description should explain what may be changed, approved, or modified; it does not.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is short, front-loaded, and uses an argument list that is easy to scan. It contains no significant fluff, though the opening sentence mostly restates the tool name rather than adding new meaning.

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?

For a two-parameter tool with 0% schema description coverage and a large sibling set, the description leaves too much unspecified. It never defines the workflow's actual scope, the shape of the optional JSON inputs, or the successful outcomes the agent should expect, so relying on it alone is risky.

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?

With schema description coverage at 0%, the description is the sole explanation of the parameters. It says `message` is a free-text objective and `inputs` is an optional JSON string, which adds a little meaning beyond the schema. However, it never specifies what structured input keys are expected, what formats are valid, or how `message` and `inputs` combine, so the agent cannot reliably construct meaningful `inputs` values.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description identifies a specific verb and resource: running the procurement domain agent action `po_approval_workflow`. However, it never explains what that action actually accomplishes—e.g., approving or rejecting purchase orders—and it does not differentiate from similar domain-agent actions like `commerce_po_approval_workflow` beyond the prefix in the tool name.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is given for when to use this tool versus alternatives such as `list_pending_approvals`, `get_approval_details`, `approve_task`, or other procurement workflows. The routing sentence about JWT, tenant, and company scope describes execution context, not a usage condition, so the agent is left to infer when this action is 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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