validate_fact_against_world

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

With no annotations, description bears full burden. It discloses internal delegation and null return behavior, but omits side effects, permissions, error states, and success/failure indications. Provides some useful context but remains incomplete.

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?

Extremely concise: two sentences, no filler. Front-loaded with purpose, followed by a behavioral detail. Every word earns its place.

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?

Given no annotations, no output schema, and zero schema coverage, the description is too sparse. It fails to explain return values beyond null, input expectations, or operational semantics, leaving significant gaps for an agent to invoke correctly.

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 0%, so description must add meaning. It gives general context for parameters ('observation' and 'entity name') but does not specify formats, constraints, examples, or how they relate to validation. Minimal added value beyond parameter names.

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?

Description clearly states the action ('validate') and the resource ('candidate observation against a target entity'). It distinguishes the tool's purpose, but does not explicitly differentiate from sibling validation tools like detect_contradictions or validate_graph.

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?

No guidance on when to use this tool versus alternatives. The description lacks context for selection among many sibling validation tools. No exclusions or prerequisites mentioned.

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