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

Beyond the readOnlyHint annotation, the description discloses two important behaviors: ambiguous names produce a not-found with closest names (rather than a guess), and absent fields are null (rather than omitted or fabricated). These are non-obvious and help an agent set user expectations accurately. It does not contradict the annotations; it adds complementary detail.

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?

The description is longer than typical, but each sentence earns its place: the first enumerates the response content, the second covers accepted inputs, the third explains ambiguity handling, and the fourth defines null semantics. It is front-loaded with the core purpose, and there is no filler. A slightly tighter phrasing could remove redundancy, but the structure is purposeful.

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 read-only detail tool with two parameters and no output schema, the description covers what is returned (the full field list), how inputs work, how ambiguity is handled, and how absent fields are represented. It does not describe edge cases like event/speaker not found independently, but the ambiguous-name not-found behavior covers a key failure mode. Overall, an agent has enough context to call the tool correctly and interpret results.

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 the baseline is 3. The description adds meaning beyond the schema by stating that 'speaker' can be a name or surname or a speakerId as returned by events_speakers, and that 'eventIdOrSlug' accepts common short forms ('the stroll'). This helps an agent map natural-language input to the correct parameter format.

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 opens with a specific verb and resource: 'Everything an event publishes about one person on its programme.' It enumerates the exact fields (job title, role, company, bio, expertise tags, social links, portrait, organizer profile link, sessions with local time), and clearly distinguishes itself from the sibling events_speakers by focusing on a single person. An agent immediately understands this is a detail lookup for one speaker.

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 clarifies accepted inputs (name or speakerId, event ID/slug/name) and gives concrete disambiguation guidance: if the name is ambiguous, the tool returns closest names instead of guessing, and the agent should ask the user which one. It doesn't explicitly say 'use this instead of events_speakers when you need a single speaker's details,' but the singular focus and reference to events_speakers provide strong implicit usage context.

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