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

With annotations only providing readOnlyHint=false and no destructive hint, the description goes beyond by disclosing that verifiers are private and owner-scoped, that deploying a new verifier returns a conflict when no token is provided, and that the call returns a version token to persist. It also notes platform 'scope=system' verifiers are server-owned and cannot be deployed. A minor gap: it does not explicitly mention whether re-deploying is destructive to prior versions, though versioning implies append-only.

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 information-dense and front-loaded with the core purpose ric a clear one-sentence introduction dove. It uses paragraphs and a short list for few-shot examples, which aids scanning. However, it is quite long and repeats some schema details (input contract rules) that might have been left to the schema. Every sentence carries useful information, but it could be tightened slightly without loss.

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 an operation with versioning, optimistic concurrency, contract-specific input rules, and platform-scope restrictions, this description covers nearly everything an agent needs: the return payload fields, the token persistence requirement, the conflict behavior, and the input contract constraints. The only minor omission is an explicit note about whether re-deploying changes existing skill references, but that is not essential for invoking the tool.

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 complete (100% – all fields have descriptions), so the baseline is 3. The description adds value by explaining the version_token's role in re-deploys ('Persist version_token for the next re-deploy'), clarifying the input_contract enum semantics (text, text_image, image), and noting the few-shot examples' contract requirements. It does not restate parameter details already in the schema, which is appropriate.

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 opens with a specific verb+resource: 'Deploy a semantic verifier (an LLM-judge check skills reference by id)'. It explains what the verifier does, distinguishes it from 'run_verifier' (which it names), and clarifies that skill references them by id. This clearly identifies the tool's role and separates it from sibling tools like get_verifier or delete_verifier.

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 explicitly names the alternative 'run_verifier' for executing verifiers, states that verifiers are owner-scoped, and explains when you cannot deploy (matching an active server-owned platform verifier). It also details the re-deploy path with expected_version_token, making it clear when to deploy vs. update, and notes that a new verifier must omit the token.

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