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

No annotations were provided, so the description carries full burden. It thoroughly describes read-only nature, statelessness, idempotency, rate limits (free vs pro), authentication requirements, error handling, and data privacy. This is exemplary for agent understanding.

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 well-structured with clear sections (Args, Returns, Behavior, When to use, When NOT to use, Behavioral Transparency). However, it is somewhat lengthy and contains some redundancy (e.g., behavioral points repeated), which could be tightened.

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 no output schema and 3 parameters, the description covers most key aspects: purpose, parameters (most), behavior, rate limits, auth, and privacy. Missing 'api_key' explanation and a vague 'When to use' are minor gaps. Overall, it provides sufficient context for safe 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 description coverage is 0%, so the description must explain all parameters. It explains 'file_path' and 'file_base64' in the Args section, but omits 'api_key' entirely. This missing parameter reduces usefulness for agents. The explanation of the two covered parameters is adequate.

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 that the tool checks C2PA/Content Credentials metadata in files, which is a specific verb-resource combination. It distinguishes itself from sibling tools like 'detect_deepfake_image' and 'verify_certificate' by focusing on provenance manifests.

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 includes explicit 'When to use' and 'When NOT to use' sections, providing clear context. However, the 'When to use' is somewhat generic ('structured analysis or classification') and doesn't directly contrast with siblings, leaving some room for improvement.

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 and delivers comprehensive transparency: side effects (read-only), authentication (basic no auth, pro requires API key), rate limits (10/day free, unlimited pro), error handling (structured error objects), idempotency (fully deterministic), and data privacy (no data stored). No contradictions.

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 structured but verbose and contains redundancy (e.g., 'Behavior' paragraph is repeated in 'Behavioral Transparency' section). Could be more concise while retaining key 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?

No output schema is provided; the return value is vaguely described as 'Detection results with metadata findings and risk assessment.' Missing details on the output structure, and one parameter (api_key) is not explained. Adequate but not 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?

Schema coverage is 0%, so description must compensate. It explains image_base64 and image_path in 'Args', but omits the api_key parameter entirely. The behavioral transparency mentions an API key for pro tiers but does not explicitly link it to the parameter. Partial coverage of 3 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 starts with a specific verb+resource: 'Check image metadata for AI generation signatures.' It clearly distinguishes the tool from siblings like check_provenance and verify_certificate by focusing on deepfake detection via metadata analysis.

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 includes explicit 'When to use' and 'When NOT to use' sections, providing clear context and exclusions. However, it does not differentiate among sibling tools or offer specific alternatives.

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 provided, the description fully carries the burden. It explicitly states no side effects, deterministic output, rate limits (free/pro), no authentication required, and that it generates structured output without modifying external systems. This is comprehensive and goes beyond basic expectations.

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 well-structured with clear sections (overview, args, returns, behavior, usage guidance). It is concise with no unnecessary words, and every sentence contributes value. Front-loaded with key 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?

Given no output schema, the description includes a 'Returns' section summarizing the output. It covers purpose, parameters, behavior, and usage guidance adequately for a moderately complex tool (5 params). Missing explanation of the 'api_key' parameter and no explicit sibling comparison, but otherwise 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?

Schema description coverage is 0%, so the description must compensate. It lists 4 of the 5 parameters in an 'Args' section with brief explanations (e.g., content as text or base64 image, content_type as text/image). However, the 'api_key' parameter is not mentioned in the description, leaving it undocumented. The descriptions add meaning but are not highly detailed.

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 creates a signed verification certificate for content, with a specific verb 'Create' and resource 'verification certificate'. It explains what it generates (hash, timestamp, analysis). However, it does not explicitly differentiate from siblings like 'verify_certificate' or 'check_provenance', which lowers the score from a perfect 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?

The description includes dedicated 'When to use' and 'When NOT to use' sections, providing clear context for appropriate usage. It advises using for structured analysis/classification and cautions against real-time decision-making without human review. However, it lacks explicit comparison to sibling tools for when to choose this over others.

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?

Since annotations are absent, the description fully carries the burden. It details that the tool is read-only, stateless, idempotent, with rate limits (free 10/day, pro unlimited), authentication requirements, error handling, and data privacy. This is comprehensive and beyond typical expectations.

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 well-structured with clear sections (description, returns, behavior, when to use/not, behavioral transparency). While somewhat verbose, all sentences add value and the structure aids readability.

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 no output schema, the description explains return values. It covers all behavioral aspects comprehensively for a simple tool with one optional parameter. Minor gap: does not specify exact format of returned statistics.

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 one optional parameter (api_key) with 0% schema description coverage. The description mentions authentication in behavior but does not explicitly link to the api_key parameter or clarify its usage. It adds partial meaning but does not fully compensate for the lack of schema descriptions.

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 returns statistics on verifications, including counts, certificates, and uptime info. It distinguishes from sibling tools like verify_certificate or verify_text_origin by focusing on statistical aggregation rather than individual verification.

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 includes explicit 'When to use' and 'When NOT to use' sections, guiding agents to apply this tool for structured analysis but not for real-time production decisions without human review. It provides clear context but could better differentiate from siblings.

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 comprehensively covers side effects (read-only), authentication (none for basic, API key for pro), rate limits (10/day free, unlimited pro), error handling (structured errors), idempotency, and data privacy, providing full behavioral 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?

The description is well-structured with clear sections (Args, Returns, Behavior, When to use, Behavioral Transparency) but is somewhat verbose, containing redundant details that could be streamlined.

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 description fully covers all relevant aspects for a tool with 2 parameters and no output schema, including behavior, error handling, rate limits, and authentication, leaving no significant gaps for an agent.

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 description adds meaning to the certificate_id parameter by specifying its format (POA-XXXXXXXXXXXX) and clarifies api_key usage in the authentication section. However, with 0% schema description coverage, it doesn't detail api_key separately, partially compensating.

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 it verifies a previously generated content certificate by ID, with the verb 'verify' and the specific resource 'content certificate'. This distinguishes it from siblings like verify_text_origin and generate_content_certificate.

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 includes explicit 'When to use' and 'When NOT to use' sections, advising structured analysis and cautioning against real-time production use without human review. However, it does not directly compare to sibling tools.

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 thoroughly covers side effects (read-only), authentication (none for basic, API key for Pro), rate limits (10/day free), error handling (structured errors), idempotency, and data privacy. Exceeds what annotations would provide.

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?

Well-structured with clear headings (Args, Returns, Behavior, When to use, etc.) and front-loaded purpose. Slightly verbose but all content adds 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?

Given 2 params, no output schema, no annotations, the description fully explains inputs (with constraints), outputs (confidence, classification, breakdown), behavior, and limitations. Complete for agent 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?

Schema coverage is 0%, so description must compensate. It adds min 50 chars for 'text' and explains 'api_key' usage in the behavioral section (though not in the param list). Adds significant meaning 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?

The description clearly states the tool analyzes text for AI-generated patterns using specific techniques (perplexity, burstiness, repetition, phrases), and distinguishes from siblings like detect_deepfake_image which focuses on images.

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?

Provides explicit 'When to use' and 'When NOT to use' sections, including a caution about real-time decisions without human review. Lacks direct comparison to sibling tools but covers context well.

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