Queue Document Analysis

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

Description explains the async behavior (returns immediately without blocking) and mentions polling and cancellation. Annotations are sparse but consistent. Could elaborate on failure modes or rate limits, but overall clear.

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?

Three sentences, each providing distinct value. No unnecessary words. Front-loaded with core purpose.

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?

Covers key workflow (enqueue, poll, cancel) and references sibling tools. No output schema, but description doesn't need to explain return values if absent. Minor gaps like error handling, but sufficient for usage.

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 low at 33%. Description adds context for optional flags (readability, entities, sentiment) but does not explain required parameters (documentId, content) beyond their names. Partially compensates but lacks full param detail.

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 enqueues a background NLP analysis of one document (readability, entities, sentiment) and returns a job id immediately. It distinguishes itself from analyze_document which is synchronous.

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?

Explicitly advises using this tool for large documents where synchronous analysis would be slow, and directs to use analyze_document for quick results. Also references polling and cancellation.

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