mcp-agentcore

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 returns (principal identity, delegation depth, cert validity, tool authorization) which is helpful, but doesn't mention authentication requirements, rate limits, error conditions, or whether this is a read-only operation. The description adds value but leaves significant behavioral aspects unspecified.

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 efficiently structured in two sentences: the first states the core functionality, the second specifies the return values. Every word earns its place with no redundancy or filler content. It's appropriately sized for the tool's complexity.

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 verification tool with no annotations and no output schema, the description provides adequate context about what the tool does and what it returns. However, it doesn't explain the regulatory framework, what constitutes valid delegation, or how to interpret the returned values. Given the security/compliance nature of this tool, more contextual information would be beneficial.

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 100%, so the schema already documents both parameters thoroughly. The description doesn't add any parameter-specific information beyond what's in the schema (e.g., it doesn't explain how tool_name relates to whitelist checking or provide examples). Baseline 3 is appropriate when the schema does the heavy lifting.

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 ('verify', 'check') and resources ('delegation chain', 'tool whitelist'), and distinguishes it from siblings by focusing on authorization verification rather than proof generation or jurisdiction checking. It explicitly answers a regulatory question about human authorization.

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 regulatory question about human authorization, suggesting this tool should be used when compliance verification is needed. However, it doesn't explicitly state when to use this tool versus the sibling tools (generate_audit_proof, verify_jurisdiction) or provide specific exclusion 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes the output components (cryptographic audit chain, Merkle epoch roots, etc.) and a key behavioral trait (chain_verification.is_valid proves tamper-resistance), which is valuable context beyond basic function.

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 appropriately sized and front-loaded, with the first sentence stating the core purpose and the second adding critical behavioral detail. It avoids redundancy, though it could be slightly more streamlined by integrating the two sentences more cohesively.

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 complexity of regulatory compliance and no output schema, the description provides a good overview of output components and tamper-proofing, but it lacks details on error handling, rate limits, or authentication needs, which are important for a tool with no annotations.

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 100%, so the schema already documents all parameters. The description does not add meaning beyond what the schema provides, such as explaining the relationship between 'from' and 'to' dates or the significance of the agent_pk, but it meets the baseline for high coverage.

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 ('Generate') and resources ('EU AI Act Art. 12 and Art. 14 compliance evidence bundle for an AI agent'), and it distinguishes itself from siblings by focusing on regulatory proof generation rather than delegation chain checking or jurisdiction 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 implies usage for regulatory compliance submission but does not explicitly state when to use this tool versus alternatives like check_delegation_chain or verify_jurisdiction, nor does it provide exclusions or prerequisites for usage.

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 and effectively discloses key behavioral traits: it performs verification checks (signature validity, temporal bounds, H3 cell authorization, facet authorization) and returns a structured result. It doesn't mention permissions, rate limits, or error handling, but covers core functionality well.

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 appropriately sized and front-loaded, with two sentences that efficiently convey purpose, checks performed, and return value without any wasted words. Every sentence adds essential 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 annotations and no output schema, the description adequately covers the tool's purpose and behavior but lacks details on the structured result format, error conditions, or dependencies. It's complete enough for basic understanding but has gaps for a verification tool with 3 parameters.

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 100%, so the schema already documents all parameters. The description adds no additional parameter semantics beyond what the schema provides, such as explaining relationships between parameters or usage examples, meeting the baseline for high coverage.

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 specific verb ('verify') and resource ('authorization to operate in a specific H3 territorial cell'), distinguishing it from sibling tools like 'check_delegation_chain' and 'generate_audit_proof' by focusing on authorization verification rather than chain checking or proof generation.

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 checking AI agent authorization in H3 cells, but does not explicitly state when to use this tool versus alternatives like 'check_delegation_chain' or provide exclusions. It offers some context but lacks clear guidance on tool selection.

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