Wodan Posture

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

With no annotations provided, the description carries the full burden, and it does so well. It discloses the $0.01 USDC cost, the x402 payment mechanism, the verdict taxonomy, the evidence lines, and provenance. It does not cover failure modes or side effects, but as a reporting tool this is a strong behavioral disclosure.

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 dense and information-rich, front-loading the paid cost before the functional details. The long colon-separated list of outputs is useful rather than bloated, though better formatting with bullet points could improve scannability.

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?

Because there is no output schema, the description must explain what the tool returns, and it does: verdicts, vendors, JavaScript requirements, content extractability, JSON-LD types, license hints, evidence, and provenance. It provides a complete picture of the returned posture information, though it omits error handling and typical response structure.

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 only one parameter, url, with 0% description coverage. The tool description adds meaning by specifying that the URL must be public and that the robots.txt verdict applies to the exact path. It does not explain accepted URL formats, normalization, or edge cases, so the semantic support is adequate but not thorough.

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 action: given a public URL, report whether an agent can treat it as a machine-readable data source. It enumerates the exact outputs and verdict values, making the tool's purpose specific and concrete. It does not explicitly distinguish itself from the sibling posture_preview, so it falls just short of full sibling differentiation.

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 the use case: checking a URL's posture before treating it as a data source. It also mentions the paid nature upfront, which is a relevant condition. However, it provides no explicit guidance on when to use this tool versus posture_preview or any other alternative, and no exclusions or fallback conditions.

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. It discloses that the tool is free, rate-limited, and returns a subset of the full analysis. It doesn't explicitly state read-only behavior, but 'preview' implies it. The rate limit is a key behavioral trait that is 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?

The description is short and front-loaded with the most important trait ('Free') and the scope ('headline'). Every sentence adds value—no fluff. The structure is direct and easy to parse.

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 single-parameter preview tool with no output schema, the description covers the key behavioral facts (free, rate-limited, subset of results) and the returned content. It lacks parameter documentation, but that is already penalized in parameter_semantics. Overall, the description is sufficient for basic invocation intent.

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% coverage (no description for the url parameter), and the tool description does not mention the parameter at all. An agent must infer that 'url' is a web address, but receives no guidance on format, validation, or constraints. The description fails to compensate for the minimal 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 verb 'preview' and the resource 'access posture', and differentiates it from the sibling (page_posture) by explicitly limiting the output to the 'headline' (verdict, confidence, field schema, one evidence line, price) versus the full report. This makes its purpose unambiguous.

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?

It implies usage for quick, free checks by contrasting with the full report and mentioning the price of the full report. It doesn't explicitly name the alternative or state when NOT to use it, but the context is clear enough for an agent to infer the intended use case.

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