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

Annotations already cover read-only, idempotent, non-destructive, closed-world semantics, so the description's added value is the ordering guarantee ('newest first') and the prompt-injection warning that titles and summaries derive from customer messages and are UNTRUSTED — a genuinely important disclosure for an LLM consumer. It omits pagination behavior and what the response envelope looks like beyond ordering.

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 compact sentences, front-loaded with the resource and ordering, then filters, then the mutation alternative, then the safety caveat. No redundant restatement of the tool name or title.

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?

An output schema exists, so return-value explanation is not owed. For a five-parameter list tool with strong annotations, the remaining gap is pagination: cursor and limit are never mentioned, so an agent cannot infer from the description how to iterate beyond the first page.

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 0%, so the description must compensate, and it only partially does: it names the three filter dimensions (status, signal_type, urgency) but says nothing about limit (1-50) or cursor, which are the two parameters an agent must understand to page correctly. The enum values for status and urgency are only discoverable from 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 ('AI-detected business signals from monitored conversations') and grounds it with concrete examples (sales opportunities, complaints, feature requests, unanswered questions) plus ordering ('newest first'). It also implicitly separates itself from the mutation sibling by pointing to update_signal for progression.

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?

Explicitly tells the agent which filters are available (status, signal_type, urgency) and routes mutation intent to update_signal. It stops short of saying when NOT to use this tool (e.g., use get_business_overview or get_follow_up_queue instead for aggregate/prioritized views), so it is clear context rather than full routing guidance.

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