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

With no annotations, the description carries full transparency burden and exceeds it: it discloses entity normalization before matching, always-list return contract with explicit no dict-wrap, and PUBLIC_DEMO data-source restriction. No contradictions 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 short paragraphs with front-loaded purpose and all key behaviors. It is slightly dense with section references and contract rationale, but each sentence contributes unique information; no fluff, though a bit more compact could be possible.

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 single-parameter listing tool, the description is complete: return type, matching semantics, data-scope restrictions, and mode behavior are all covered. An output schema exists, so detailed field-by-field return description is not required.

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 0% and there is one required param, but the description explains entity semantics thoroughly: it matches as either subject or object and is normalized for case/whitespace before matching. This is substantive meaning beyond the bare string schema.

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 it lists all facts where entity is subject or object, with explicit audit/transparency purpose. However, it does not directly contrast with sibling tools check_claim/check_triple, so differentiation rests on the entity-scoped listing behavior.

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?

Provides clear contextual usage: use for transparency/audit when entity may appear in either role, and clarifies PUBLIC_DEMO mode limits data source. It doesn't name alternative tools or state when not to use it, but the audit framing and entity-matching rule make intended use evident.

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