get_scene_summary

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

With no annotations, the description carries the full burden of behavioral disclosure. It usefully reveals that the summary is AI-generated and may be null if not generated yet, which is important for setting expectations. It does not mention read-only status or response shape, but 'Fetch' strongly implies a read operation.

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 one front-loaded sentence that states the core operation immediately, followed by a valuable caveat about null returns. Every word earns its place.

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?

The definition is complete enough for a simple fetch tool: it states what the tool returns and the null condition. It relies on the schema to explain parameter aliases, which is acceptable, though it could explicitly note that a monologue id is expected despite required parameters being zero.

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 fully described in the schema itself. The tool description adds no new parameter-level semantic information, so the baseline of 3 is appropriate.

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 uses a specific verb ('Fetch') and resource ('AI-generated summary of the scene a monologue appears in'), and clarifies it is context for the speech. This clearly differentiates it from siblings like get_play_summary and get_paraphrased_monologue.

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 phrase 'context for the speech' implies when to use it, but there is no explicit guidance about when to prefer this over related tools like get_play_summary or get_paraphrased_monologue. No exclusions or alternatives are named.

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