Blue Cap Evidence Verify

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

Annotations already establish idempotency and non-destructiveness, and the description adds meaningful behavioral context by stating the result is deterministic, machine-readable, and includes provenance and assurance information. This goes beyond what the annotations alone convey and does not contradict them.

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 tightly worded sentences with no filler. The core action and target are front-loaded, and the second sentence adds value by describing the output's nature and purpose 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?

The output schema covers return values, so the description need not detail them, but the tool has four required object parameters with 0% schema coverage. Key parameters such as consumer_id and invocation_context remain semantically unexplained, and the 'frozen Blue Cap verification contract' itself is not elaborated, leaving the agent with partial context.

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, but it only references 'assurance record' and 'referenced evidence' (likely assurance_record and evidence_artifacts). The required consumer_id and invocation_context parameters are not explained at all, leaving the agent without enough meaning to populate them correctly.

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 ('Verify'), names the resource ('structured assurance record and its referenced evidence'), and specifies the standard ('frozen Blue Cap verification contract'). This clearly differentiates the tool from sibling tools like hash_compute and schema_validate, which do not perform contract-based 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 indicates the tool is for governance and audit workflows, implying when it might be used, but it does not explicitly state when to choose this tool over hash_compute or schema_validate. No exclusions or alternative selection criteria are provided.

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 cover idempotency and non-destructiveness. The description adds meaningful behavioral context by mentioning that computation happens through a 'receipted external execution' and that the digest is reproducible, giving insight beyond the structured 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 short and front-loaded with the core action. However, phrases like 'receipted external execution' and 'stable machine endpoint' are jargon-heavy and add limited clarity for the space they occupy.

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 four required parameters, a nested object, zero schema descriptions, and no usage guidance, the description is not complete enough for an agent to invoke this tool correctly. The output schema helps with return values, but the meaning of required inputs remains underspecified.

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 for all four required parameters. It addresses only 'data' and 'encoding' indirectly by mentioning UTF-8 or base64 bytes, while 'consumer_id' and especially the nested 'invocation_context' object are left completely unexplained.

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 and resource: 'Compute a SHA-256 digest' for customer-supplied bytes, and clarifies the supported encodings. This clearly distinguishes it from sibling tools like evidence_verify and schema_validate, which serve different 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?

No guidance is given on when to use this tool versus alternatives, nor are any exclusions or preconditions mentioned. The phrase 'stable machine endpoint' hints at a use context, but it does not help an agent decide between hash_compute and its 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?

Annotations declare idempotentHint=true and destructiveHint=false, and the description adds valuable behavioral detail: the result is deterministic, machine-readable, has bounded errors, and involves a 'receipted external execution.' This goes beyond the annotations without contradicting them.

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 compact sentences front-load the primary purpose and then summarize key output behavior. There is no filler, though the phrase 'receipted external execution' is jargon-heavy and slightly obscures meaning.

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?

An output schema exists, so return values do not need detailed explanation, and annotations cover safety characteristics. However, the description fails to illuminate the purpose of consumer_id and invocation_context, and the 'supported subset' of JSON Schema is left undefined. For a tool with four required parameters, this gap makes the description incomplete for an agent that must produce valid inputs.

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 only 25%, and the description compensates poorly. It indirectly maps 'supplied structured data' to the value parameter and 'customer-supplied JSON Schema' to the schema parameter, but consumer_id and invocation_context are completely unexplained in both the description and the schema, leaving critical required parameters ambiguous.

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 ('Validate'), the resource ('supplied structured data'), and the standard ('JSON Schema Draft 2020-12 supported subset'). This clearly differentiates it from siblings like evidence_verify and hash_compute, making the tool's core function unmistakable.

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 context is clear: use this tool when data must be validated against a customer-supplied JSON Schema. However, it does not explicitly name alternatives or state when not to use it, so it stops short of full usage guidance.

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