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

Annotations already cover read-only, idempotent, closed-world behavior, so the description only needs to add context. It does, by disclosing the fallback trait that near matches are suggested when no exact fact exists — an error/empty-result behavior the annotations do not reveal. It omits what happens if both id and no are supplied.

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 sentences, front-loaded with the lookup keys, with the example inline and the fallback behavior last. No filler 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?

For a simple, single-record lookup with full schema coverage and safety annotations, the description covers the essentials plus the near-match fallback. Only the combined id/no case and result shape (no output schema) remain unaddressed, which are minor.

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 the schema already documents id, no, and lang including the language default. The description adds one useful detail beyond the schema — a concrete id format example ('flamingos-embarrassed') — but nothing about precedence when id and no are both passed, so baseline is appropriate.

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?

States a specific verb and resource ('Get one fake fact') and names both lookup keys (id or catalogue number), which distinguishes it from random_fact and search_facts implicitly. It stops short of explicitly contrasting with those siblings, so it is clear but not fully differentiated.

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?

Usage is implied: call this when you already hold an id or catalogue number rather than a query string. No explicit when-to-use/when-not statement or pointer to search_facts for partial-text lookups is given.

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