analyze_batch

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

With no annotations present, the description must convey behavior. It discloses a hard limit (20 clips), the clustering of moods, and the return of a single playlist, but does not mention handling of failure, performance implications, or side effects. This provides some transparency but not enough detail about what happens during analysis or how the output is structured beyond a mini-playlist.

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 a single, front-loaded sentence that immediately states the key constraint (up to 20 clips) and the primary action (analyze and cluster moods), followed by the outcome. There is no wasted words, and the most important information is presented first.

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?

While an output schema exists, the tool description does not cover parameter semantics, potential constraints, or usage conditions. For a tool with four parameters and no schema descriptions, it relies entirely on the description to explain usage, which it fails to adequately do. The description omits guidance on parameters like max_seconds and platform_hint, making the definition incomplete for correct invocation without external knowledge.

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?

The schema has no parameter descriptions (coverage 0%), and the description only indirectly addresses the 'sources' parameter by mentioning 'clips'. It does not explain 'extra_notes', 'max_seconds', or 'platform_hint', leaving their semantics to inference from titles. This is insufficient given the 0% coverage and the need for the description to compensate.

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 action ('Analyze'), the resource ('up to 20 clips'), and the output ('one consistent mini-playlist'), including specifics like mood clustering for a series. This distinguishes it from sibling tools such as analyze_video_music (single-video) and recommend_bgm (music recommendation).

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 the tool is for batch analysis of multiple clips for a series (up to 20 clips) and producing a cohesive playlist, which suggests when to prefer it over per-clip tools. However, it does not explicitly state when not to use it or mention alternatives, though the batch limit and series context provide clear situational guidance.

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