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

Adds substantial context beyond the annotations: it consumes model inference billed to company credits, honours cooldown/quiet-period rules, may no-op into a cache read, and explicitly bounds side effects (never sends a message, never changes tags or tasks). This meaningfully fleshes out the non-readonly, non-idempotent hints.

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 doing distinct work: purpose, cost/behaviour, and side-effect scope. The core action is front-loaded and there is no 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?

For a single-parameter refresh tool with an output schema present, the description covers the operationally relevant unknowns: billing, non-deterministic/cache behaviour, and what it will not touch. Nothing needed to call it safely 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% for the single conversationId parameter, so the baseline is 3. The description only says 'one conversation' and adds no format, sourcing, or lookup detail beyond 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: regenerate the AI summary of one conversation. That verb cleanly separates it from the read-only sibling get_conversation_summary and the bulk sibling backfill_conversation_summaries without needing to name them.

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 a clear trigger condition, 'on explicit user request', and explains when the call will not actually regenerate (cooldown and quiet-period rules mean it may return the cache). It does not explicitly name the alternative get_conversation_summary or say when to prefer it, so it stops short of a 5.

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