add_to_vocabulary

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

Discloses side effect of writing to database, persistence across restarts, and idempotency behavior for identical pairs - all beyond the absent 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?

Every sentence adds value, front-loaded with purpose and return values, structured with clear sections (USE WHEN, NOT FOR, ALTERNATIVES, BEHAVIOR, PARAMETERS).

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?

Covers all aspects for a simple two-parameter tool: purpose, when to use, parameters, side effects, idempotency, and return values (output schema exists but description already sufficient).

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?

With 0% schema coverage, description fully explains both parameters: term is required and non-empty, pronunciation is optional with format hints and inference fallback.

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 adds a custom term to ContextPulse's voice vocabulary so Whisper recognizes it, distinguishing it from siblings like remove_from_vocabulary and get_vocabulary.

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?

Explicitly tells when to use (for mis-transcribing proper nouns/technical terms), when not to use (bulk loads, use CLI), and provides alternatives (remove_from_vocabulary, get_vocabulary).

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