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

Annotations already cover readOnly/idempotent/safe, and the description adds meaningful behavioral information: default inclusion of both v1 and v2 processes, ordering, return shape ('capture counts, contributors, status'), and the 100-per-page cap. No contradiction with 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?

Four tight sentences, front-loaded with the action and ordering, and each sentence adds a distinct useful fact: output shape, drill-down alternative, filtering behavior, and pagination cap. No wasted words.

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?

Despite having no output schema, the description discloses the nature of the returned metadata, ordering, default version behavior, filtering options, pagination cap, and how to get the full per-process model. This is enough for an agent 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?

Schema coverage is 100%, and each parameter already has a clear description, including team_id's OAuth nuance and status enum values. The description adds only light extra guidance by grouping search/status/version as discovery filters and mentioning the page cap; the schema does the heavy lifting.

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 ('List Clarity processes for the current team') plus a concrete ordering ('most recently updated first'). It also distinguishes itself from per-process reads by explicitly saying it returns lightweight picker metadata rather than the full read model.

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 clear context for when to use it: 'suitable for building a picker', and routes the agent to GET endpoints for the full per-process read model. It also explains that search/status/version narrow discovery and that results are capped at 100 per page. It does not explicitly contrast with the sibling listClarityProcessSummaries tool, so it stops just short of full alternative routing.

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