quote

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

With no annotations, the description carries the full burden, and it does disclose real behavior: selection is random from a curated (not open) corpus, and the output is a short quote with author attribution. It also flags a genuine gotcha — the `lang` parameter is accepted but non-English values silently fall back to English. It omits any mention of rate limits or caching, which keeps it below a 5.

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?

Front-loaded with what the tool returns, then the related-tool pairing, then the language caveat, so the critical limitation is not buried. A clause of promotional framing ('great for daily content hooks, social posts, newsletter intros') is soft filler, but the sentences otherwise earn their 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?

For a one-optional-parameter trivia tool with no output schema, the description covers purpose, the shape of the return value, the fallback behavior, and sibling relationships — enough to call it correctly. Nothing essential is missing; only marginal detail (rate limits, determinism) is absent.

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 already 100%, so the baseline is 3, but the description adds non-obvious meaning: the enum of ten language codes is effectively a no-op and returns English anyway. That directly corrects a misleading schema signal and is the single most useful thing an agent could know about this parameter.

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 a random notable quote') plus the source pool (curated list of named authors). It also names the sibling tools it complements (did_you_know, dino_fact), so an agent can separate it from the generic 'random' tool without opening a schema.

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?

Gives concrete usage contexts ('today's trivia' outputs, daily content hooks, social posts, newsletter intros) and lists the tools it pairs with. It stops short of any exclusion or routing rule — notably it never distinguishes itself from the sibling 'random' tool — so it is clear context but not full when/when-not guidance.

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