text_to_phonemes

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

No annotations are provided, so the description carries the full burden. It discloses that conversion is approximate, uses dictionary lookup with letter-by-letter fallback, and returns a phoneme string with control prefixes. It does not mention any destructive effects or authentication needs, which are not expected for a text conversion tool.

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?

The description is concise at five sentences, front-loaded with purpose. Every sentence adds value: explaining the process, warning about unknown words, and advising editing. No unnecessary words or repetition.

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?

Given no output schema, the description explains the return value (phoneme string ready for speak) and mentions control prefixes. It provides sufficient context for an agent to use the tool effectively, though it could explicitly state the output format or include a brief example.

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?

All five parameters are described in the input schema with good detail. The description adds context about the output being editable and including control prefixes, but does not significantly enhance parameter understanding beyond what the schema already provides.

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 converts English text to an approximate klattsch phoneme string via word-by-word dictionary lookup. It specifies the fallback spelling for unknown words and distinguishes itself from sibling tools like speak and speak_file by noting the output is ready for those tools.

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?

The description advises editing the output before using it with speak and warns that unknown words sounded robotic. It provides context on when to use (conversion) and best practices, though it does not explicitly state when not to use it or compare to siblings.

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