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

With no annotations provided, the description carries the full burden of behavioral disclosure. It clearly indicates this is a write operation ('Create or update') and describes the policy structure, but doesn't mention important behavioral aspects like authentication requirements, rate limits, idempotency, or what happens when updating existing policies versus creating new ones. The example helps but doesn't cover all behavioral traits.

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 (purpose, args, returns, example) and front-loads the core purpose. While comprehensive, some sentences could be more concise (e.g., the rules explanation is detailed but necessary given complexity). No wasted text, though the formatting with line breaks could be optimized for pure conciseness.

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 6-parameter mutation tool with no annotations, the description provides substantial context including parameter details, return format, and a complete example. The presence of an output schema reduces the need to fully document return values. The main gap is lack of behavioral context around permissions, side effects, and error conditions, but overall it's quite complete for the tool's 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?

Given 0% schema description coverage, the description provides excellent parameter semantics that fully compensate. It documents all 6 parameters with clear explanations, including detailed breakdown of the complex 'rules' parameter structure with its nested condition and action components. Default values for 'priority' and 'enabled' are explicitly stated, and the example demonstrates proper usage.

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 with specific verbs ('Create or update') and resource ('security policy for agent governance'). It distinguishes itself from sibling tools like get_audit_log or report_incident by focusing on policy creation/update rather than retrieval or reporting functions.

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 context through the explanation of what policies do ('define rules that control what agents can do'), but doesn't explicitly state when to use this tool versus alternatives. No guidance is provided about prerequisites, dependencies, or specific scenarios where this tool should be selected over other policy-related tools (though none appear in the sibling list).

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 carries the full burden of behavioral disclosure. It describes what the tool retrieves (audit log entries with specific filters) and includes return format details, which is helpful. However, it lacks critical behavioral traits: it doesn't mention whether this is a read-only operation, if it requires specific permissions, rate limits, pagination behavior beyond the 'limit' parameter, or error conditions. The description adds value but leaves significant gaps.

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 purpose statement, parameter documentation, return format, and examples. It's appropriately sized for a 5-parameter tool with output details. While efficient, the initial purpose sentence could be more front-loaded with key distinguishing information, and some sections (like the Returns block) are slightly verbose but still valuable.

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's moderate complexity (5 parameters, no annotations, but has output schema), the description is reasonably complete. It fully documents parameters and return format, and the output schema reduces the need to explain return values in detail. However, it lacks behavioral context (permissions, safety, rate limits) and sibling differentiation, which are important gaps for a compliance/investigation 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 description coverage is 0%, so the description must fully compensate. It does this excellently: it documents all 5 parameters with clear semantics, optional/default status, allowed values (e.g., time_range options, status values), and practical examples. The description adds substantial meaning beyond what the bare schema provides, making parameters fully understandable.

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: 'Retrieve audit log entries for compliance and investigation.' It specifies the verb ('Retrieve') and resource ('audit log entries'), and mentions the system context ('Guardian Agent'). However, it doesn't explicitly differentiate from sibling tools like 'get_compliance_status' or 'report_incident', which might have overlapping compliance/investigation domains.

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 no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'get_compliance_status' or 'validate_action', nor does it specify prerequisites, exclusions, or typical use cases beyond generic 'compliance and investigation'. The examples show how to call it, but not when it's the appropriate choice.

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 carries full burden and does well by disclosing key behavioral traits: it's a read-only operation (implied by 'Get' and 'Generates'), describes the report content structure, mentions default values for parameters, and provides example usage patterns. However, it doesn't mention potential limitations like rate limits, authentication requirements, or data freshness 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?

The description is well-structured with clear sections (purpose, args, returns, examples) and appropriately sized. Every sentence adds value, though the example section could be slightly more concise. The information is front-loaded with the core purpose stated first, followed by supporting 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's complexity (3 parameters, no annotations, but has output schema), the description is complete enough. It explains the purpose, parameters, return structure, and provides usage examples. The output schema existence means the description doesn't need to exhaustively document return values, and it provides adequate context for an agent to understand and use the tool effectively.

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 description coverage, the description fully compensates by providing detailed parameter documentation in the 'Args' section, including all 3 parameters with their purposes, acceptable values, and defaults. It adds substantial meaning beyond what the bare schema provides, explaining what each parameter controls in the compliance report generation.

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 with specific verbs ('Get compliance status and security health metrics', 'Generates a compliance report') and resources ('policy violations, security incidents, overall governance health'). It distinguishes from siblings like 'get_audit_log' or 'report_incident' by focusing on comprehensive compliance assessment rather than logging or incident reporting.

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 through the example scenarios ('Get daily compliance status', 'Get weekly report with all details'), but doesn't explicitly state when to use this tool versus alternatives like 'get_audit_log' or 'validate_action'. It provides context about time periods and detail levels but lacks explicit guidance on tool selection among 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 provided, the description carries the full burden of behavioral disclosure. It effectively describes key behaviors: this is a registration/mutation operation (implied by 'register'), it affects trust levels and tool permissions, and it returns a structured JSON result. It doesn't mention authentication requirements, rate limits, or error conditions, but provides substantial operational context beyond basic purpose.

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: purpose statement, parameter explanations, return format, and example. While somewhat lengthy, every sentence adds value. The front-loaded purpose statement is strong, though the detailed parameter explanations could be more concise while maintaining clarity.

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's complexity (7 parameters, mutation operation), no annotations, and the presence of an output schema, the description provides comprehensive context. It explains the tool's purpose, all parameters with semantics, the return format, and includes a practical example. The output schema means the description doesn't need to detail return values, and it adequately covers what's needed for effective use.

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 has 0% description coverage, so the description must fully compensate. It provides detailed semantic explanations for all 7 parameters, including examples, format requirements (e.g., 'JSON array', 'JSON object'), and allowed values for 'trust_level'. This adds significant value beyond the bare schema, making parameter usage clear and actionable.

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: 'Register a new agent with Guardian for security policy evaluation.' It specifies the verb ('register'), resource ('agent'), and context ('Guardian for security policy evaluation'), distinguishing it from sibling tools like 'create_policy' or 'get_audit_log' which handle different security functions.

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 clear context for when to use this tool: to register agents for security policy evaluation, with implications about trust levels and tool permissions. It mentions that 'Unregistered agents are treated as 'low' trust,' which helps understand the consequences of not using it. However, it doesn't explicitly state when NOT to use it or name specific alternatives among the 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 provided, the description carries the full burden of behavioral disclosure. It effectively describes the tool's behavior: it logs incidents for investigation and tracking, and the 'Returns' section details outcomes like incident ID generation, success status, and potential agent suspension. This covers key behavioral aspects without 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 well-structured with sections for purpose, usage, arguments, returns, and an example. It is appropriately sized for a 6-parameter tool, though it could be slightly more concise by integrating the example more tightly. Every sentence adds value, such as clarifying parameter options and output format.

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's complexity (6 parameters, no annotations, but with an output schema), the description is highly complete. It explains the tool's purpose, usage, all parameters in detail, return values, and includes a practical example. The output schema is referenced in the 'Returns' section, making the description comprehensive for agent use.

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 description coverage is 0%, so the description must compensate fully. It does so by providing detailed semantics for all 6 parameters, including enumerated values for 'incident_type' and 'severity', and clear explanations for others like 'description' and 'evidence'. This adds significant value beyond the basic 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's purpose: 'Report a security incident for investigation and tracking.' It specifies the verb ('report') and resource ('security incident'), and distinguishes it from siblings like 'create_policy' or 'get_audit_log' by focusing on incident reporting rather than policy management or log retrieval.

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 clear context for when to use the tool: 'Use this tool to log security incidents such as policy violations, suspicious agent behavior, or potential security threats.' It lists specific incident types, giving practical guidance. However, it does not explicitly state when not to use it or name alternatives among 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 provided, the description carries the full burden of behavioral disclosure. It effectively communicates this is a security validation tool that returns structured decisions (allowed/require_approval) and generates audit correlation IDs. However, it doesn't mention potential side effects like audit logging, rate limits, or authentication requirements that might be relevant for security tools.

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 and front-loaded with the core purpose and usage guidance, followed by organized parameter documentation and a complete example. Every sentence adds value: the security gate positioning, the workflow guidance, parameter explanations, return format details, and illustrative example all serve distinct purposes without redundancy.

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's security-critical nature, 5 parameters with 0% schema coverage, and no annotations, the description provides comprehensive context. It explains the tool's role in the security workflow, documents all parameters with examples, details the return format (though an output schema exists), and includes a complete usage example. This fully compensates for the lack of structured metadata.

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 description coverage, the description fully compensates by providing detailed parameter explanations with examples for all 5 parameters. Each parameter gets clear semantic meaning beyond the basic schema types (e.g., action_type examples like 'tool_call', 'resource_access'; target examples like 'tool name', 'resource URI'; parameters as 'JSON string of action-specific 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 clearly states the tool's purpose with specific verbs ('validate whether an agent can perform a specific action') and distinguishes it from siblings by emphasizing it's the 'PRIMARY security gate' for pre-action compliance checks. It explicitly differentiates from audit/logging tools like get_audit_log and policy management tools like create_policy.

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 explicit guidance on when to use this tool ('BEFORE performing any sensitive action') and why ('to ensure compliance with security policies'). It establishes a clear workflow relationship with other tools by positioning this as a prerequisite gatekeeper function.

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