Infer input schema

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

Annotations already declare readOnlyHint=true and idempotentHint=true, but the description adds context: uses AST-level analysis via opa parse, no OPA server needed, and accepts inline source, files, or directories. No contradictions.

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?

Every sentence adds value: purpose, method, use cases, input formats. Well-structured with no fluff or redundancy.

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?

Though no output schema, the tool returns a JSON Schema object which is self-describing. Description covers input modes thoroughly. Slight lack of output format details is acceptable given the tool's nature.

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 description coverage is 100%, so baseline is 3. The description adds value by explaining mutual exclusivity of source and paths, allowed root constraint for paths, and recursive directory walking, beyond what the schema provides.

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 it statically analyzes Rego policies to return a JSON Schema of input.* fields. It uses specific verbs ('analyse', 'return') and resource ('input.* fields'), differentiating it from siblings like rego_eval or opa_query_decision.

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 mentions it's a 'correct starting point' for integration tests, schema validation, or documenting policy API, implying when to use. It does not explicitly state when not to use or name alternatives, but the context is reasonably clear.

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