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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds that the check is deterministic and fast, but says nothing about what the diff returns, whether it flags or blocks, or how mismatches are reported.

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?

One front-loaded sentence carries the purpose, plus a short endpoint reference. There is no filler, though the endpoint notation adds little for an agent that already has the tool bound.

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 only two required parameters and no output schema, the definition covers the minimum needed to invoke the tool. It is still incomplete on the result contract, since nothing describes whether the response lists offending spans, a boolean verdict, or scores.

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 both parameters are documented structurally, establishing the baseline of 3. The description clarifies the role of each side of the comparison (LLM answer vs RAG sources) but adds no format or size guidance beyond what the schema already 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 states a specific verb and resource: a deterministic diff that catches unsupported numbers, dates, and names in an LLM answer against RAG sources. That is concrete enough to tell it apart from generic guards like tinplate_llm_output_guard, though it never names an alternative explicitly.

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?

"Fast first filter" implies the intended position in a pipeline (cheap pre-check before deeper verification), which is real usage guidance. However, it gives no explicit when-not conditions and does not name a sibling for the follow-up or heavier check, so routing is only implied.

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