review_agent_commerce_actionsReview up to five non-sensitive public AI-agent actions for approval and evidence requirements. This tool does not execute, pay, sign, deploy, post, or reveal purchase instructions.
| Name | Required | Description | Default |
|---|---|---|---|
| actions | Yes | Actions to review. Do not submit secrets, private source, or customer data. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint=true and idempotentHint=true. The description adds behavioral context by explicitly listing actions the tool does not perform (execute, pay, sign, deploy, post, reveal), which reinforces safety and provides clarity beyond the annotations.
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 two sentences, each serving a distinct purpose: first defines the core function, second lists key exclusions. No wasted words, front-loaded with essential information.
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?
Given low complexity (1 param, no output schema, no siblings), the description adequately covers purpose, input constraints, and exclusions. However, it does not explain what 'evidence requirements' entails or the form of the review output, leaving minor gaps.
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 input schema covers 100% of parameters with descriptions, but the tool description adds important context: limiting to non-sensitive public actions and a maximum of five. This expands on the schema's generic 'actions' parameter, adding meaning about content and scale.
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 verb 'Review' and the resource 'non-sensitive public AI-agent actions' with a specific scope (up to five). It explicitly lists actions the tool does NOT perform, distinguishing its role. With no sibling tools, differentiation is not needed.
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 implicitly guides usage by stating exclusions (does not execute, pay, etc.), indicating this is a pre-execution review tool. However, it lacks explicit when-to-use or when-not-to-use guidance, but the clarity of exclusions compensates partially.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
With only one tool, there is no possibility of confusion with other tools. The tool's purpose is clearly distinct.
The single tool name follows a clear verb_noun pattern (review_agent_commerce_actions), so there is no inconsistency.
A single tool is far too few for a server claiming to be a 'commerce guard'. The tool only reviews actions and does not handle execution, approval flow, or sensitive actions, making the scope extremely narrow.
The tool is severely limited: it only reviews non-sensitive public actions up to five. There are obvious gaps such as handling sensitive actions, executing approved actions, or managing more than five actions, leaving the domain largely uncovered.