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

Annotations mark it non-read-only, open-world and non-idempotent, and the description adds substantial context the annotations cannot: it consumes one of the user's daily Ask questions (a quota/rate constraint), returns at most ~350 words with numbered linked sources, flags thin coverage explicitly, and describes the async fallback pattern. This goes well beyond the structured 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?

Front-loaded with the trigger condition ('Use this when...') and dense with useful facts, but the single long paragraph packs quota, output format, follow-up and timeout behavior together, making it slightly heavy to scan. Little is wasted, but a small amount of structural separation would help.

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 full return-value burden and does so: length cap (~350 words), numbered sources with links, and the conversation address are all described, plus quota consumption and the timeout/get_ask_answer handoff. An agent has everything needed to call, interpret and recover from this tool.

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%, so both parameters (question, conversation_id) are already fully documented in the schema, including language handling and the conversation_id pattern. The description's 'Pass conversation_id for a follow-up' largely restates the schema field, so baseline 3 is appropriate.

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: it answers research questions from AgingResearch.News's own record of papers, trials, approvals, mouse lifespan results, researchers and companies. It scopes the subject matter precisely (biology of aging, longevity interventions, age-related disease, people/companies) and is clearly distinguishable from retrieval siblings like search_arn or find_entities.

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 explicit when-to-use conditions with concrete examples, an explicit exclusion ('Not for personal medical advice, doses or symptoms'), and routes follow-ups via conversation_id. It also names the alternative path when the call times out ('read it with get_ask_answer and its question_id'), which is exactly the when-vs-alternative guidance an agent needs.

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