get_conversation_transcript

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

No annotations are provided, so the description carries full burden. It mentions 'in chunks' and 'large conversation transcripts', hinting at pagination or size handling, but lacks details on rate limits, authentication needs, error conditions, or what 'metadata' includes. For a tool with 4 parameters and no annotations, this is insufficient behavioral disclosure.

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 and highly concise: two sentences with zero waste. The first sentence states the purpose and output, the second provides usage guidance—every word earns its place without redundancy.

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 complexity (4 parameters, no annotations, no output schema), the description is incomplete. It lacks details on parameter meanings, behavioral traits like pagination or errors, and output specifics. For a tool that handles 'large' data in chunks, more context is needed to guide effective use.

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%, so the description must compensate. It doesn't explain any parameters beyond implying 'chunk' and 'chunk_size' relate to chunking, but doesn't clarify their roles, units, or interactions. With 4 parameters (conversation_id, format, chunk, chunk_size) and no schema descriptions, this leaves significant gaps in understanding.

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 verb ('Gets') and resource ('conversation transcript'), specifying it returns data 'in chunks' with 'transcript chunk with metadata'. It distinguishes from siblings like 'get_conversation' by focusing on transcripts rather than general conversation data. However, it doesn't explicitly contrast with all siblings, keeping it at 4 instead of 5.

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 provides explicit usage guidance with 'Use when: retrieving large conversation transcripts', which clearly indicates the context for this tool. However, it doesn't mention when NOT to use it or name specific alternatives (e.g., 'get_conversation' for non-transcript data), so it falls short of a perfect 5.

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