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

Annotations already declare readOnlyHint and idempotentHint, yet the description still adds substantial non-obvious behavior: the exact denominator used for the nudge list (login member still shipping code, deduped across linked identities, excluding tracked contributors and inactive members). It also discloses the attribution rule — a call counts for the team named by the repository slug or ?team= binding, not the web switcher's last selection — which is the kind of semantics an agent cannot infer elsewhere.

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 core answer is front-loaded in the first sentence and the rest is dense, information-bearing prose with no filler. It runs long, and the attribution paragraph sits somewhat apart from the main payload, costing it a point on economy.

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 an output schema present, the description need not spell out return shapes, and it still enumerates the report's sections plus the definitional subtleties (nudge-list denominator, team attribution) that determine whether the agent interprets the numbers correctly. Nothing needed to call or trust the result is missing.

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 description coverage is 100%, so the baseline is 3 and the schema already carries the days default, clamp, and repository slug format. The description goes beyond that by explaining what repository actually does to attribution when a member belongs to several teams, adding real meaning rather than restating 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?

States a specific verb and resource: reports Coderbuds MCP adoption per member over a window, with named sub-outputs (total invocations, per-member usage, per-tool counts, nudge list). An agent knows exactly what question this answers. It does not explicitly separate itself from the nearby get-ai-adoption-tool or get-agent-activity-tool, so it stops short of a 5.

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 concrete triggering questions ("who is using the MCP", "is the team on the MCP yet") and a second use case (finding who needs setup instructions). That is clear context for when to reach for it. It names no exclusions and no sibling alternatives, which is exactly the gap that keeps it at 4.

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