get_project

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

Annotations already cover read-only/no-open-world safety, so the description instead invests in non-obvious data semantics: a timestamp only moves when a measurement is published, and neither an unchanged value nor null proves a cycle ran. That caveat is exactly the kind of behavioral context annotations cannot express.

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?

Front-loaded with what is returned, then the usage trigger, then the caveat. The second sentence is long and dense but every clause carries new information (timestamp semantics plus two alternative tools); nothing is redundant.

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 carries the burden of describing return content and does so concretely: freshness per dimension, prompts, overall status, plus the interpretation caveat for timestamps. An agent has enough to call it and read the result 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?

Single parameter with 100% schema description coverage — the schema documents projectId's format and even points at list_projects as the source. The description adds nothing about the parameter, so the baseline of 3 applies.

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 ('Get project details') and enumerates the returned content: per-dimension monitoring freshness across five named dimensions, AI monitoring prompts, and overall status. It clearly differs from list_projects (single project detail) and from the per-dimension dashboards, though it never explicitly frames itself as the 'single project' counterpart.

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 an explicit trigger ('Use this to check when each dimension last produced data') and, for the ambiguous aiVisibility case, names the exact alternatives (get_ai_visibility_dashboard's latestCheckDataAvailable, get_ai_visibility_trend's events.incompleteCycles) with the condition that selects each. Routing is fully specified.

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