Validate paper evidence

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

The description goes beyond the sparse annotations by clarifying that the verdict is strictly about the series as submitted and explicitly listing what the service did not observe. This is valuable behavioral context for the agent, especially since the annotations do not describe the tool's internal checks. No contradiction with annotations was found.

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 compact and front-loaded, with the first sentence stating the core purpose and output. The subsequent two sentences add meaningful scope limitations without redundancy or fluff.

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 simple one-parameter validation tool, the description covers the input, the validation standard, the failure output, and important limitations. Although there is no output schema, the phrase 'with each failure's JSON pointer' gives a useful hint about return semantics, and the scope clarification is especially valuable. It could be slightly more complete with an explicit success/verdict format, but overall it is adequate.

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 single parameter is documented in the schema as 'A canli.paper-evidence.v0 record,' which provides the baseline. The description adds minimal extra semantic detail beyond the schema, referring to it as a paper or simulated performance record but not elaborating on required fields or formats.

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 function: checking whether a paper or simulated performance record meets canli.paper-evidence.v0 and returning each failure's JSON pointer. It identifies a specific verb and resource, and the standard name helps distinguish it from sibling validators, though it does not explicitly contrast with them.

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 when to use the tool: when an agent needs to validate a paper or simulated performance record against the specified standard. It also provides useful negative guidance by noting the service never saw the data source, costs, survivorship, or lookahead, but it does not name alternative tools or state when to prefer those.

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