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

No annotations are provided, so the description carries full burden. It does not disclose whether the tool is read-only, requires authentication, or has rate limits. It describes what is detected but not the operation's side effects or constraints.

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 convey the full purpose and scope with no redundant words. The description is efficiently front-loaded with the verb 'Run a comprehensive privacy audit' followed by specific details.

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?

Given the tool has only 2 parameters and no output schema, the description adequately covers the tool's functionality, checks, and regulations. It lacks behavioral context but is otherwise complete for an audit 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 coverage is 100%, so baseline is 3. The description adds value by explaining what the audit covers (trackers, consent, etc.), but it does not add detail to the parameters themselves beyond what the schema provides.

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 specifies the tool's purpose as running a comprehensive privacy audit on a website, listing specific checks (trackers, cookie consent, privacy policy, forms) and regulations (GDPR, CCPA, ePrivacy). It clearly distinguishes from narrower sibling tools like scan_trackers or check_consent.

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 full audits but does not explicitly state when to use it versus alternatives (e.g., scan_trackers for specific trackers). No when-not guidance is provided, but the context of 'comprehensive' gives some implicit direction.

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?

No annotations provided, so description carries full burden. It states what the tool checks but does not disclose behavioral traits like whether it is read-only, requires authentication, or has rate limits. The output format is not described.

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, front-loaded with the main action, followed by specific detection items. No wasted words.

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?

While the description covers the tool's purpose, it lacks details on return value format, error handling, or scope (e.g., whether it checks only the given URL or embedded resources). No output schema is provided.

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 coverage is 100%; the parameter 'url' is described in schema. The description adds context about consent checking but does not add detail beyond what the schema provides for the parameter itself.

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 checks cookie consent mechanisms for GDPR and ePrivacy compliance and lists specific elements detected (CMP platforms, reject options, etc.). It distinguishes from siblings like scan_trackers which focus on general trackers.

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 usage for consent compliance checks but does not explicitly state when to use this tool vs alternatives, nor does it mention prerequisites or limitations.

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?

With no annotations, the description carries full burden. It discloses that the tool outputs trackers, consent compliance, and scores, giving a clear behavioral idea. However, it does not mention if it makes external network requests, rate limits, or other side effects. It is fairly transparent for a read-only tool.

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, front-loaded with the core purpose. No unnecessary words. Every sentence contributes value.

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?

Despite no output schema, the description outlines key outputs. However, it lacks detail on the comparison format, scoring detail, or error handling. More completeness would aid agent invocation.

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 coverage is 100% with minimal descriptions. The tool description does not add extra meaning beyond the schema (e.g., URL format expectations). 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?

The description clearly states the tool's purpose: comparing privacy practices of two websites side by side. It specifies what it shows (trackers, consent compliance, overall scores), and it effectively differentiates from siblings like scan_trackers and check_consent which likely operate on single sites.

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 use for comparing two websites but does not provide explicit guidance on when to use this tool versus alternatives like scan_trackers or check_consent. It lacks when-not or exclusionary criteria.

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?

No annotations provided, so description must fully disclose behavior. It states it is a 'quick scan' and lists output contents (tracker types and GDPR concerns) but does not address side effects, rate limits, authentication needs, or response format.

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 sentence with no unnecessary words, front-loaded with the verb 'scan', and immediately conveys the tool's core function.

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 one-parameter tool with no output schema, the description adequately explains the purpose and high-level output (list of tracker types with GDPR concerns). It does not cover error handling or edge cases but is sufficient for a quick scan 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 coverage is 100% with a single 'url' property described as 'The URL to scan'. The tool description adds context that it scans a website but does not provide additional parameter semantics beyond the schema. Baseline 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 tool scans for third-party trackers on a website and lists specific types (advertising, analytics, social, fingerprinting) with GDPR concerns, distinguishing it from sibling tools like check_consent or audit_privacy.

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 on when to use this tool vs siblings (check_consent, compare_privacy, audit_privacy). The description mentions 'quick scan' but does not specify when not to use it or provide alternatives.

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