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

With no annotations, the description carries the burden and does disclose meaningful behavior: no auth required, the agent has owner-curated context, and sessionId preserves conversation memory. However, it does not disclose return format, potential side effects of the visitor object, or whether the conversation can have persistent external effects—so behavioral transparency is adequate but not rich.

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?

Three sentences, each earning its place: the first defines the tool's purpose, the second adds auth/context details, and the third gives workflow and memory guidance. The description is front-loaded and free of filler.

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?

The description is sufficient for a conversational tool with a small parameter set: it explains how to find the slug, what to send, and how to maintain memory. Missing details like exact return format are partially covered by 'answers questions in natural language,' and the visitor object is well documented in the schema, so the gap is minor.

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%, so the baseline is 3. The description adds value beyond the schema by tying publicSlug to 'clearly_search_projects results' and clarifying that sessionId should be stable 'across calls to keep conversation memory.' This practical guidance supports correct invocation.

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 uses a specific verb and resource: 'Talk to a public Clearly project's AI agent,' and clarifies the agent answers questions using owner-curated context. It also implicitly differentiates from siblings by describing discovery ('discover projects' in clearly_search_projects) as separate and this tool as the follow-up conversation step.

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 gives clear usage context: pair with clearly_search_projects to find projects, then ask follow-ups here, and reuse sessionId for memory. It does not explicitly state when not to use this tool or mention the clearly_capture_lead sibling, so it falls just short of full exclusion guidance.

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