Count SGU mentions of a term

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

With no annotations, description discloses stem matching, coverage scope, and output components (total, segments/episodes, breakdowns). Missing details on rate limits or idempotency, but sufficient for safe invocation.

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?

Three sentences efficiently convey purpose, use cases, behavior, and limitations. Some repetition ('real occurrence count' vs 'not just how many episodes match') could be tightened, but overall well-structured.

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?

Despite no output schema, description details return values (total, segments/episodes, breakdowns by year/speaker/top episodes). Covers input, behavior, and output fully for a simple tool with two params.

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 covers both parameters (term, top_episodes) with descriptions. Description adds context: stem/inflection matching for term, default of 10 for top_episodes. Adds value beyond 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?

The description clearly states the tool counts occurrences of a word or phrase across the archive, distinguishing it from sibling tools that return matching episodes or segments. It emphasizes 'real occurrence count' not just episode matches.

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 explicit example queries and clarifies the tool counts occurrences per speaker and year. Mentions coverage limitation (transcribed episodes). Could be improved by noting when not to use (e.g., for exact phrase matching without stemming).

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