Analyze Dialogue Edit Candidates

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

The description adds valuable behavioral context beyond the annotations: it is deterministic, never calls a model, never persists transcript text, and never changes Premiere. These statements meaningfully expand on the readOnly and idempotent hints and directly address likely concerns about side effects and model dependence.

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?

Two short sentences carry the entire definition: the first states the core function and inputs, the second states key exclusions. There is no filler, and the most decision-relevant information is front-loaded.

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 rich input schema, the existing annotations, and the presence of an output schema, the description is complete enough for an agent to select and invoke the tool correctly. It communicates the operational constraints and data dependencies without needing to repeat schema details or return-value documentation.

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?

The schema already documents all parameters at 100% coverage, so the baseline is 3. The description adds extra semantic value by emphasizing that segments are caller-supplied and revision-bound, and that silence ranges are optional and local, which clarifies the caller's responsibilities and the intended data flow.

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 names a specific verb ('Analyze') and a precise resource ('caller-supplied, revision-bound transcript segments and optional local silence ranges'), with a clear output concept ('deterministic dialogue-edit candidates'). It also separates itself from model-driven or mutating tools by stating what it never does, which helps distinguish it from siblings.

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 gives clear context for when to use the tool: when the caller already has normalized transcript segments and optional silence data and wants deterministic analysis. It does not explicitly name sibling alternatives or state when not to use it, but the 'caller-supplied' and 'never calls a model' phrasing implies the boundary well.

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