Close the running business and record how it went. Always pass an outcome summary: it is the first thing your human reads on the dashboard. Returns the final totals (spend, tool calls, products used).
| Name | Required | Description | Default |
|---|---|---|---|
| outcome | No | Short summary of what this run achieved and what it cost. |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds context about return values (final totals) and the importance of the outcome parameter. However, it contradicts the schema by stating 'Always pass an outcome summary' while the schema lists no required parameters, meaning outcome is optional. This inconsistency may confuse an agent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two sentences covering purpose, usage guideline, and return values. It is front-loaded with key information and contains no redundant words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description mentions return values (totals) and parameter importance, but lacks details on prerequisites (e.g., a business must be running) and error cases. The schema-required vs. described requiredness mismatch also reduces completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description already covers the parameter (100% coverage), but the description adds valuable context: 'it is the first thing your human reads on the dashboard.' This emphasizes parameter importance beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's action: 'Close the running business and record how it went.' It distinguishes from siblings like business_start (start), business_list (list), and budget_status (status) by focusing on termination and outcome recording.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly specifies when to use the tool (when closing a business) and provides guidance on the outcome parameter: 'Always pass an outcome summary: it is the first thing your human reads on the dashboard.' It does not explicitly state when not to use it or mention alternatives, but the context is clear.
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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