Convo

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions that 'The AI will answer based on the transcript,' which hints at the tool's reliance on transcript data, but doesn't cover critical aspects like response format, error handling, rate limits, authentication needs, or whether it's read-only or mutative. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

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 extremely concise and front-loaded, consisting of two clear sentences that directly state the tool's purpose and mechanism. There's no wasted language or redundancy, making it easy for an agent to parse quickly. Every sentence earns its place by providing essential information.

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 complexity of a Q&A tool with no annotations and no output schema, the description is incomplete. It lacks details on behavioral traits (e.g., how answers are generated, limitations), output format, and usage guidelines. While it states the basic purpose, it doesn't provide enough context for an agent to fully understand how to invoke it effectively or interpret results, especially compared to sibling tools.

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 100%, with both parameters ('meeting_id' and 'question') well-documented in the schema. The description doesn't add any parameter-specific details beyond what the schema provides (e.g., it doesn't explain format constraints for 'meeting_id' or examples for 'question'). Given the high schema coverage, the baseline score of 3 is appropriate as the description doesn't compensate but also doesn't detract.

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's purpose: 'Ask any question about a specific meeting. The AI will answer based on the transcript.' It specifies the verb ('ask any question'), resource ('specific meeting'), and mechanism ('based on the transcript'). However, it doesn't explicitly distinguish this from sibling tools like 'get_summary' or 'get_transcript' which might provide similar meeting information, so it doesn't reach the highest score.

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 provides no guidance on when to use this tool versus alternatives. It doesn't mention when-not scenarios, prerequisites, or compare it to sibling tools such as 'get_summary' (for summaries) or 'get_transcript' (for raw transcripts). The agent must infer usage from the purpose alone, which is insufficient for optimal tool selection.

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