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

With no annotations provided, the description carries the full disclosure burden. It usefully reveals a payment requirement ($0.005 USDC on Base via x402), which is genuine behavioral context, but says nothing about output shape, keyword count limits, input size constraints, or failure behavior.

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?

Two short sentences with no filler, and the core purpose is front-loaded before the pricing note. Nothing is wasted, though the brevity reflects under-specification rather than efficiency alone.

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 compute tool with an undocumented 'payload' parameter and no output schema, the description should explain what goes in and roughly what comes back. It covers only the purpose and price, leaving the agent unable to invoke it confidently.

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 0% and the single parameter is named 'payload' with a '{}' default, which is opaque. The phrase 'from text' weakly implies payload holds the input text, but nothing clarifies whether it is raw text, JSON, or something else.

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 gives a specific verb and resource: 'Extract top keywords/phrases from text.' That distinguishes it reasonably well from siblings like summarize, classify, and sentiment, though it does not explicitly contrast with 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?

There is no guidance on when to choose this tool over siblings such as summarize or classify, and no preconditions or exclusions are stated. The agent must infer usage from the verb alone.

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