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

Annotations already mark it readOnly and non-destructive, but the description adds valuable behavioral depth beyond that: 'no login, no AI, nothing is saved'. This discloses statelessness and privacy-relevant behavior, which is exactly the kind of context that helps an agent predict side effects. No contradiction with annotations.

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?

Two sentences carry all essential information: return payload, version, examples, docs link, usage timing, side-effect guarantees, and the pairing with validate_uef. It is front-loaded with the core deliverable and contains no fluff or repeated schema info.

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 zero-input, read-only reference tool with an output schema defined, the description covers everything an agent needs: what it returns, when to call it, what side effects it doesn't have, and how it relates to a sibling validation tool. There are no missing pieces for correct invocation.

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?

There are zero parameters locked in the schema, and schema coverage is 100%, so there is nothing for the description to explain about inputs. Per the baseline for zero-parameter tools, a 4 is appropriate; the description doesn't need to spend space on parameter semantics.

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 names a specific verb ('Return') and a precise resource ('Universal Event Format (UEF) JSON Schema for EVENT imports (schema_version 1.0)'), and it further scopes the deliverable to include examples and a docs URL. This distinguishes it from generic schema tools and from siblings like validate_uef. The phrase 'schema textbook' clarifies its specific role clearly.

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?

It explicitly states when to use it: 'before drafting or editing UEF'. It also points to a complementary alternative, validate_uef, for checking a draft locally, giving the agent clear routing guidance. No ambiguity remains about when this tool is appropriate.

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