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

Annotations cover mutation/safety hints (readOnlyHint=false, destructiveHint=false, idempotentHint=false), and the description adds non-obvious behavioral context: the identity subject is routinely the caller's own end customer, first_name/last_name denote the authorized representative for business identities, and requirement_id returns warnings instead of failing later. It does not cover permissions or duplicate-creation behavior, but this is well beyond the annotation baseline.

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?

Front-loads the core purpose and workflow, then layers conditional rules and the subject/representative caveat. It is longer than typical but each block earns its place; minor redundancy with the schema on phone_number digits and business-only fields keeps it from a 5.

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 14-parameter mutation tool with no output schema, the description supplies the full workflow, conditional field rules, data-authenticity guidance, and what requirement_id returns (warnings). Enough for an agent to call it correctly, though it could say more about the created-identity response fields.

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%, so parameters are already documented (including company_name requirement for business and digits-only phone). The description adds cross-field conditional context (company_name needed for business, mandatory fields from the requirement) and the requirement_id pre-check effect, but largely restates what the schema already carries. Baseline 3 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?

States a specific verb+resource (create a regulation identity) and positions it precisely in the DID registration flow as step 2 after list_requirements, which distinguishes it from sibling creation tools like create_address and create_regulation_upload_link.

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?

Gives explicit sequencing (after list_requirements, then create_regulation_upload_link, then create_address), tells when to use identity_type values per the requirement, and explains the optional requirement_id pre-check. Alternatives and ordering are unambiguously stated.

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