verify_artifacts

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

No annotations are provided, so the description carries full burden. It discloses that the endpoint is public, requires no API key, and returns 404 for older generations. It does not discuss rate limits or error details beyond the 404, which is acceptable for a read-only verification tool.

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 two short paragraphs, each with a clear focus: first on purpose and returned data, second on billing paths and access. Every sentence adds information; no verbosity.

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?

With one parameter, no annotations, but an output schema present, the description covers purpose, use case, output fields, error behavior, and access requirements. It leaves no critical gaps for an agent to use this tool correctly.

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 coverage is 100%. The description adds value beyond the schema by specifying the source of the generation_id (a prior SkillGenerateResponse) and the error condition for old generations. This helps the agent understand parameter origin and edge cases.

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 fetches the provenance manifest for a past Loreto generation, enumerates specific returned fields, and distinguishes from sibling tools (e.g., generate_skills, list_skills) by focusing on verification of past outputs.

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 explains the tool's purpose ('validate what was produced before recommending') and notes it works for both billing paths and is public. It does not explicitly list when not to use the tool or name alternative tools, but the context is clear.

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