batch_analyze

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

With no annotations provided, the description fully covers behavioral traits: it declares read-only, stateless, idempotent, and no side effects. It details authentication (basic vs pro), rate limits (10/day free, unlimited pro), error handling, and data privacy. This exceeds the burden required for transparency.

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 well-structured with clear sections, front-loading the main purpose. While slightly verbose, each section (behavior, usage, args, transparency) adds distinct value and avoids unnecessary repetition.

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 batch processing nature and two parameters, the description covers behavior, usage, and transparency thoroughly. Since an output schema exists, return values are not needed. The description lacks examples but is otherwise complete for selecting and invoking the tool correctly.

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 'Args' section adds minimal value beyond the schema, but the description compensates partially by explaining the delimiter for texts and noting authentication requirements for API key. Given 0% schema coverage, more detail on input formatting or examples would improve semantics.

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 analyzes sentiment for multiple texts at once, specifying the '|||' delimiter. It distinguishes itself from siblings like analyze_sentiment (single text) and compare_sentiments (comparison) by focusing on batch processing, though it doesn't explicitly contrast them.

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 includes explicit 'When to use' and 'When NOT to use' sections, guiding the agent towards structured analysis and away from real-time decision-making without human review. However, it could better compare with sibling tools to clarify when this batch tool is preferred over single analysis.

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