Aevum Security

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

Annotations already indicate safe read-only behavior. Description adds value by stating the result is 'full details' and associating the parameter with a slug from list_services, clarifying prerequisites.

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?

One sentence, no extraneous words. Front-loads the core purpose and includes necessary usage hint.

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 simple tool with rich annotations, description is adequate. 'Full details' is slightly vague on return structure but acceptable given no output schema and the tool's straightforwardness.

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?

With 0% schema coverage, description compensates by explaining the parameter is a slug from list_services. Although it does not enumerate the valid slug values, the enum in schema covers that. Adds meaningful context beyond 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?

Description specifies a clear action (get full details), resource (one Aevum Security service), and method (by slug from list_services). It distinguishes from sibling list_services by focusing on a single service.

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?

Implicitly guides the agent to use after list_services to obtain the slug. No explicit when-not-to-use but context of sibling tools provides clear 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 readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, so the description doesn't need to repeat safety traits. It adds value by disclosing the exact output structure (slug, name, summary) and the semantic meaning of slug as a service identifier, which goes 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 two short sentences, front-loaded with the primary content (list of services and fields). The second sentence adds essential cross-referencing to sibling tools without any fluff. Every word earns its place.

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 simple list tool with no parameters, no output schema, and rich annotations, the description fully covers what the tool returns and how it fits into the broader workflow. It explains the return fields and the role of the slug, making it complete for its complexity.

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 zero parameters and 100% coverage (trivially), so the baseline is 4. The description adds no parameter-specific semantics because there are none to describe, which is appropriate for a parameterless tool.

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 clearly states the tool's purpose: to list Aevum Security's cybersecurity services, specifying the exact fields returned (slug, name, one-line summary). It also distinguishes the tool by noting that the slug is the identifier used by sibling tools get_service_details and submit_enquiry, making it unique among the siblings.

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 when to use this tool: to obtain service identifiers (slugs) that are needed for subsequent calls to get_service_details and submit_enquiry. It doesn't explicitly state 'use this when you need to browse or select a service,' but the relationship is clear from the slug mention, which provides practical usage context.

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?

The description goes well beyond the annotations by disclosing irreversibility ('cannot be withdrawn once submitted'), expected response time ('within 1 business day'), return value ('Returns the enquiry id'), auth requirements ('requires an agent key passed as Authorization: Bearer'), and that it acts on behalf of the principal. This is rich behavioral context.

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 concise (two sentences plus a bracketed auth note) and front-loaded with the primary action. Every sentence adds important information: the action, the real-world consequences, the receipt, and the required authentication. No words are wasted.

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 mutating tool with no output schema, the description covers outcomes, irreversibility, response time, auth requirements, and return value. It tells the agent exactly what to expect and what is required, making it complete for decision-making.

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 already provides 100% coverage for all four parameters with clear descriptions. The tool description adds no additional parameter-specific meaning, but it does reference the service field's origin ('list_services') in the schema. Following the baseline for high schema coverage, a score of 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?

The description clearly states the action ('Submits a business enquiry'), the target ('to Aevum Security'), and the scope ('on behalf of the caller's principal'). It also distinguishes itself from read-only sibling tools by emphasizing that it creates a real, irreversible enquiry and returns an ID as proof.

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?

While there is no explicit 'use this instead of list_services' wording, the description provides strong contextual cues: it creates a real, human-read enquiry that cannot be withdrawn, implying it is for actual submissions rather than browsing. The sibling tools are clearly read-only lookups, so the usage context is effectively conveyed.

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