Creator Desk Commerce Completion Verify

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

With no annotations, the description carries the full burden of behavioral disclosure. It communicates that the tool returns free metadata and explicitly negates verification behavior, which indicates a read-only information lookup. It could add more detail about return format or data scope, but the core behavior is transparent enough.

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 concise sentences with no filler. The main purpose is front-loaded, and the clarifying negation about verification is immediately useful for tool selection.

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 zero-parameter, no-output-schema metadata tool, the description is complete. It states what the tool provides, confirms it is free metadata, and clarifies what it does not do, which is sufficient for an agent to decide whether to call it.

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 tool has zero parameters and the schema provides full coverage with an empty properties object, so there is nothing for the description to clarify. The baseline of 4 applies because no parameter documentation burden exists.

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 provides descriptive metadata about the current Creator Desk completion standard, using a specific verb ('describing') and resource. It also explicitly differentiates itself from the verification sibling by stating 'This tool does not perform 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 clearly signals that this tool is for metadata retrieval, not verification, which implies the sibling creator_desk_verify_completion should be used for verification. However, it does not explicitly name the sibling or provide a direct 'use X when Y' routing statement.

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 disclosure burden. It reveals important behavior: the check is paid, returns VERIFIED_COMPLETE only when every required test passes, and otherwise returns defects/missing evidence plus corrective actions. It does not cover authentication, rate limits, or side effects, but for a verification tool the core gating behavior is well disclosed.

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 concise sentences with no filler. The main purpose is front-loaded, and the second sentence adds the critical pass/fail behavior. Every clause earns its place.

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 the nested evidence schema, five parameters, and no output schema, the description gives no parameter guidance or return-format details beyond 'machine-readable defects'. An agent could select the tool from the description but would struggle to construct a valid call without opening the schema and reasoning through the evidence requirements.

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%, and the description does not explain the five parameters (target_url, evidence, objective, standard_id, standard_version). It only gestures at 'evidence' and 'check', leaving the agent to infer what input is expected, especially for the nested evidence object. This is a significant compensation gap.

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 a specific verb ('Verify') and resource ('ecommerce/storefront work') and names the standard check (CDS-COMMERCE-001). It is understandable on its own, but it does not explicitly contrast itself with the sibling creator_desk_standard_info, so differentiation is implied rather than stated.

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 phrase 'before reporting completion' gives clear situational guidance about when this tool is appropriate, and 'otherwise returns... corrective actions' tells the agent what happens on failure. However, it does not state when not to use it or mention the sibling alternative, so exclusions are absent.

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