Compose cue list (NL → setlist)

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

Annotations already indicate non-destructive and open-world behavior. The description adds transparency by detailing the two execution paths (LLM or grammar parser) and the chaining capability, which are not evident from annotations alone.

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 with two sentences that front-load the purpose and provide key behavioral details. Every word is necessary, and no information is redundant.

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 tool's complexity (8 parameters, no output schema), the description covers the main purpose and execution modes. However, it could be more complete by explaining what 'validated' entails or how errors are handled, but the essentials are present.

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 coverage is 100%, so the description adds value by explaining how parameters like 'apply' and 'containerName' relate to chaining into create_cue_sequencer, providing context beyond the schema descriptions.

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 function: converting natural language to a validated cue list (SetlistSchema variant). It distinguishes itself from siblings by mentioning the optional chaining into create_cue_sequencer and specifying the use of LLM or grammar parser.

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 implies usage for creating cue lists from descriptions, but lacks explicit guidance on when to use this tool versus alternatives like create_cue_sequencer or create_setlist_runner. It mentions the chaining option but doesn't specify conditions for preferring the LLM over the grammar parser.

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