synthesize_pair

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

With no annotations, the description carries the disclosure burden and does it well: it describes the concatenated audio structure, the pause, voice auto-selection when lang is provided, defaults for rate/pause/auto_play, output directory fallback to TTS_OUTPUT_DIR, and the returned JSON fields. It does not cover overwrite behavior or auth requirements, but the main behavioral traits are disclosed.

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 front-loaded with a one-sentence purpose, followed by a concrete use example, then a clean Args list covering all parameters, and ends with a Returns line. For a 15-parameter tool, its length is justified and every section earns its 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?

Given the high complexity (15 params), no annotations, 0% schema description coverage, and only a summary output schema, the description provides enough detail to invoke the tool correctly: required texts, optional languages/voices/audio settings, output path controls, and return shape. Nothing critical for a correct call is missing.

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 description coverage is 0%, and the description compensates fully by documenting every one of the 15 parameters: meanings, defaults, allowed ranges, and relationships such as 'If lang1 is provided without voice1, auto-selects.' This is exactly what an agent needs beyond the bare 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 states a specific verb and resource: 'Synthesize a pair of texts and stitch them into one MP3' and gives the exact output shape '[text1 audio] [pause] [text2 audio]'. This clearly separates it from the single-text synthesize tool, but it does not explicitly contrast with synthesize_pair_batch, so it stops short of full sibling differentiation.

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?

It gives an explicit intended use case — language learning pairs like 'strong' (English) + 'stark' (German) — which tells an agent when the tool is appropriate. It does not mention when to prefer synthesize_pair_batch or synthesize_batch instead, so exclusions are missing.

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