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

Beyond the readOnlyHint annotation, the description tells the agent that no_data means 'unknown, never zero and never healthy,' that the verdict falls back to not-enough-data, and that the tool is read-only and returns no credentials. These are concrete behavioral caveats that materially affect how an agent interprets results.

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 longer than average but every clause carries information: output contents, verdict logic, missing-data semantics, credentials, and read-only status. It is front-loaded with the core purpose and only then adds edge-case guidance, so it remains scannable despite its density.

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?

With no output schema, the description takes on the job of explaining the return contents and does so thoroughly: daily fields, the comparative verdict, the no_data convention, and the insufficient-data case. Combined with full parameter schema coverage and readOnly annotations, an agent has enough to select and invoke the tool correctly.

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 already documents both install_id and read_token at 100% coverage. The description reinforces that both come from the project's dashboard page and mentions the 'Connect AI once' flow, but it does not add substantially new parameter semantics beyond what the schema provides. Baseline 3 is appropriate.

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 opens with the guiding question 'Is this project getting faster or slower?' and then specifies the exact deliverable: one project's last 30 days of measurements, ratings, crashes, alerts, and a verdict. This is a specific verb-plus-resource statement, though it does not explicitly differentiate itself from sibling trend-related tools.

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 makes the use case clear: call this when you need a project's recent performance trend and a comparison of the last 7 days against the prior 7. It gives context and even explains how to handle no_data days, but it does not explicitly state when to prefer a sibling tool or when not to use this one.

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