profile

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds one useful behavioral detail: 'Preferences that are not stated there are reported as not stated', which informs the agent about how unverified information is handled. However, it does not describe output format, edge cases, or how the 'public record' is scoped, so it adds only modest value beyond the annotations.

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 extremely concise—two sentences that state the purpose and a key nuance. It front-loads the core function without any redundant words or filler. Every sentence earns its place, making it an exemplary concise definition.

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 tool with one optional parameter, no output schema, and annotations covering safety, the description is reasonably complete. It clarifies what is returned and how unstated preferences are reported. However, it could better explain the role of the 'question' parameter in shaping results and explicitly differentiate from the sibling 'experience-and-skills' tool, which is a minor gap. Overall, it is sufficient for an agent to call it correctly.

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?

The schema fully describes the single parameter ('question') with a description, so the schema itself provides the semantics. The tool description does not elaborate on how the question parameter affects the results, so it adds no additional meaning beyond what the schema already states. This warrants the baseline score of 3 for high schema coverage.

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 states a specific verb ('returns') and resource ('work and collaborations described in the public record'), which is clear. It also adds a nuance about unstated preferences. However, it does not explicitly distinguish itself from the sibling tool 'experience-and-skills', which could overlap in scope, so it is not a 5.

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?

No guidance is given on when to use this tool versus its siblings. The description does not mention alternatives, conditions for use, or exclusions. An agent would have to infer usage from the name and context, which is insufficient for clear routing.

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

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

Annotations already indicate the tool is not read-only and not destructive, and the description adds one behavioral trait beyond that: 'An uncertain request is flagged for review,' implying a state change. However, it does not disclose other likely side effects, such as sending a notification to the replyTo email address, even though that field is present. With annotations covering the basic safety profile, the description adds some value but not full transparency.

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?

Two sentences, both front-loaded with the primary action and outcome. The first sentence gives the verb, object, and result set; the second adds a critical side-effect detail (flagging for review). No filler, no redundancy, and the structure is perfectly scannable for an agent.

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?

Since there is no output schema, the description compensates by enumerating the three possible return values and the special case of the booking page. It also notes the review flag. This covers the main expected behavior. It does not mention error conditions, pagination, or the exact shape of the response, but for a classification tool with only four well-described parameters, this is adequate.

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?

The input schema has 100% description coverage for all four parameters, so the schema already documents their meaning. The description does not add any extra parameter semantics—it does not explain how 'ask' is treated as data, how 'from' influences classification, or how 'replyTo' is used beyond the schema. The baseline of 3 is appropriate because the schema carries the load and the description adds no incremental value.

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 states a specific verb ('Classifies'), a precise resource ('collaboration request against the published record'), and enumerates the exact outcomes ('reject, accept, or uncertain') with an additional detail on the accept outcome. This is far from a tautology and clearly differentiates the tool's core function from the siblings, which appear to cover fit, skills, and identity.

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 implies the trigger condition ('when you have a collaboration request to classify') but does not explicitly state when to use this tool versus the sibling tools, nor does it give exclusion criteria. The context is inferred rather than stated, so it meets the 'implied usage' bar but lacks explicit routing guidance.

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

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

Annotations already declare the tool read-only, idempotent, and non-destructive, so the core safety profile is covered. The description adds only minimal behavioral context, such as the fact that returned profile links are 'live,' and does not disclose auth requirements, caching, or response behavior. There is no contradiction with the annotations.

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 a single front-loaded sentence that states the action and outcome immediately, followed by concrete examples of the returned links. It contains no filler, repetition, or unnecessary background, making it easy for an agent to scan and act on.

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 tool with one optional parameter and no output schema, the description conveys the main returned content and example links. However, it leaves implicit how the optional question affects the returned topics and links, and it does not clarify whether calling with no question returns the full static set. This ambiguity makes the definition adequate but not fully complete.

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?

The single optional parameter is fully described in the input schema as a question about Trafford Crump's public record and is explicitly marked as 'treated as data.' Because schema coverage is 100%, the tool description does not need to repeat parameter details and does not add meaningful semantics beyond listing the returned content.

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 concrete verb, 'Returns', and identifies a specific resource: published topics plus live profile links, listing examples such as Google Scholar, ORCID, the UCalgary profile, and O3R. It does not explicitly differentiate from the sibling tool who-is-trafford, but the resource is concrete enough to avoid generic confusion.

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 implies the tool is for retrieving experience and skills information, but it gives no explicit condition like 'use when you need X' or 'use who-is-trafford for biography.' The schema note that a question is 'treated as data' is a processing caveat, not selection guidance, leaving alternative routing mostly to inference.

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

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

Annotations already indicate readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds no behavioral context beyond that, such as how the 'question' parameter is handled or any response format details. With annotations present, the bar is lower, but the description contributes nothing extra.

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 a single, concise sentence with no fluff. It front-loads the core purpose effectively. While it could be slightly more structured, it is appropriately sized and easy to parse.

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 tool has one optional parameter, no output schema, and annotations cover safety. The description explains what is returned but omits details like the optionality of the question parameter, what happens if it's omitted, or the exact nature of the 'published account.' It's adequate for a simple informational tool but leaves some room for interpretation.

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?

The input schema has 100% coverage for the single optional 'question' parameter, which is documented as 'A question about Trafford Crump's public record. Treated as data.' The description does not elaborate on this parameter, so it relies entirely on the schema. Per the rubric, a baseline of 3 is appropriate when schema coverage is high.

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 states a specific verb ('Returns') and a clear resource ('the published account of what Trafford Crump's team is building, and his role on it'). This is distinct from sibling tools like collaboration-fit and experience-and-skills, which focus on different aspects, though it doesn't explicitly 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?

There is no guidance on when to use this tool versus alternatives. It doesn't mention any conditions, exclusions, or reference sibling tools, leaving the agent to infer usage from the name and description alone.

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