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

Annotations already declare readOnlyHint=true, destructiveHint=false, openWorldHint=true and idempotentHint=false, and the description usefully explains the non-idempotency in billing terms: calls are charged ($0.003 via x402 USDC or card key), failed calls are free, and repeats are not free. It also reassures that the tool 'reads or computes only and changes nothing.' No latency or rate-limit detail, so not a 5.

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?

Purpose and output are front-loaded before use cases, example, pricing, and safety notes, and every sentence carries information. It is denser than ideal — pricing and behavior are packed into one long paragraph — but there is no filler.

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?

For a single-parameter tool with no output schema, the description covers what it returns (polarity plus confidence), the domain constraint (English), the cost model, and the safety profile. An agent has everything needed to decide and call 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?

There is only one parameter and the schema already documents it fully (English text up to 4,000 characters) at 100% coverage, so the baseline is 3-4. The description's inline example ('text=The checkout was fast and support answered within minutes.') reinforces the expected input shape, adding modest value over the schema.

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 names a specific verb+resource (positive/negative sentiment classification of English text) and even specifies the output (a confidence score) and the underlying model (DistilBERT fine-tuned on SST-2). It is clearly distinguishable from generic siblings like ai_classify, though it never explicitly contrasts itself with them, which keeps it just short of a 5.

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?

It gives concrete application contexts ('triage reviews, support messages, social posts and replies') plus a worked example, so an agent knows when this tool is the right fit. However, it offers no when-not guidance and does not mention alternatives such as ai_classify for related label tasks.

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