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

Annotations already establish this is a safe, non-destructive, closed-world read, so the bar is lower. The description adds that it inspects recent runs and is intended as a post-setup smoke check, but says nothing about what happens when there are no runs, latency, or any auth/prerequisite requirements.

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?

Two short sentences with no filler; the purpose is front-loaded and the usage condition follows immediately. Every clause earns its place.

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?

There is no output schema, so the description could reasonably describe what verification returns (a pass/fail, a run list, an error when no data flows). As written, an agent knows why to call it but not what to expect back, leaving a real gap for a diagnostic tool.

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?

Schema coverage is 100% and the single optional promptName parameter is fully documented in the schema, so the baseline is 3. The description adds no syntax, defaulting, or filtering detail beyond what the schema already states.

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?

States a specific verb and resource ("Verify that your Converra integration is working") and clarifies the mechanism ("by checking recent runs"). It is clear on its own, but it does not distinguish itself from nearby siblings such as list_integrations, get_integration_guide, or get_verification_evidence, so an agent must infer the boundary.

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?

Gives explicit temporal context: "Run this after setting up the SDK or webhook to confirm data is flowing." That tells the agent when this tool is appropriate. It stops short of naming alternatives (e.g., list_integrations for enumerating integrations rather than validating one), so it is strong but not complete.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.