ingest_voice

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

Describes the conversion and output structure but does not disclose side effects (e.g., whether it persists to context memory or is purely analytical). No annotations to contradict.

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?

Well-structured with args and return explained. Could be slightly more concise but generally efficient.

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 presence of output schema (implied by context signals) and two simple parameters, the description adequately covers the tool's behavior and return values.

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?

Adds meaningful context: transcript is 'full transcript text', source is an identifier with an example. Schema had no descriptions (0% coverage), so this compensates well.

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 it ingests a transcript into context memory, extracting structured fragments (decisions, actions, etc.). This distinguishes it from sibling tools like ingest_diagram or ingest_diff.

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 mentions pre-transcribed text sources (Whisper, AssemblyAI) but does not explicitly state when to use this tool versus alternatives, nor provides exclusion criteria.

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