arclera

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 agent knows this is a safe read operation. The description adds semantic context (returns legal identity) but no additional behavioral traits such as authentication or response format. No contradiction with 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 concise sentences: the first states the action and result, the second gives the usage scenario. Every sentence earns its place, with no redundant wording.

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 zero-parameter read-only getter, the description fully covers what it returns and when to use it. The absence of an output schema is mitigated by the clear statement 'legal identity', and sibling differentiation is sufficiently implied.

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 tool has zero parameters, and the schema covers all (vacuously). The description does not need to explain parameters. Baseline 4 applies due to the absence of parameters.

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 action ('Return the legal identity of the entity') and resource (the company's legal identity). It distinguishes itself from sibling tools by emphasizing 'legal identity' versus contact or services, and further clarifies the intended use case.

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 gives a clear when-to-use context: 'Relevant when a contract, invoice or other document must name the company exactly.' It does not explicitly name alternatives or exclusions, but the usage scenario is well implied.

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, idempotentHint, and destructiveHint. The description adds useful scope by noting the result is the single contact channel for Arclera Digital, setting expectations that there is no search or multiple-choice behavior.

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 short sentences, no filler. The core purpose is front-loaded, and the usage guidance is concise and useful.

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 no-parameter, read-only tool, the description fully covers what an agent needs: what it returns, for whom, and when to use it. No output schema is present, but the return is described simply enough that none is required.

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 tool has zero parameters and an empty schema, so the baseline is 4. The description needs to explain no parameters, and it correctly focuses on the fixed resource being returned.

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 and resource: 'Return the only contact channel for Arclera Digital.' It clearly distinguishes itself from siblings like get_company and get_services by naming the exact data being returned.

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 provides a clear trigger condition: 'Relevant when a user asks how to reach Arclera.' It does not explicitly mention sibling alternatives or when-not-to-use scenarios, but the context is sufficiently clear for a zero-parameter tool.

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, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds a small amount of semantic context ('what Arclera Digital does') but discloses no additional behavioral traits such as auth requirements, rate limits, or return format. This is adequate but not exceptional.

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 core behavior and then the relevant use case. It contains no filler or redundant information.

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 zero-parameter, read-only retrieval tool, the description is complete. It explains what the tool returns, why it is useful, and when to reach for it. Sibling names provide additional context, and no output schema is necessary given the trivial input and straightforward return.

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, so there is no parameter information to provide. The schema description coverage is effectively 100%, and the description correctly focuses on the purpose of the tool. No further parameter semantics are needed.

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 uses a specific verb ('Return') and resource ('what Arclera Digital does'), making it clear this is about the company's services. It also adds a concrete use case: judging whether work is in scope. The sibling tools (get_company, get_contact) suggest this tool is distinct from company/contact info.

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 states exactly when this tool is relevant: 'when judging whether a piece of work is in scope.' This gives clear usage context. It does not explicitly mention when not to use it or name alternatives, but the siblings are reasonably differentiated by name.

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