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

No annotations are provided, so the description carries the full behavioral burden. It does disclose one genuinely important trait — the tool is paid ($1.50/call via x402, USDC on Base), which tells an agent a crypto payment is required before invoking. However, it says nothing about what the pipeline retrieves from, latency, or response characteristics, leaving most behavioral context uncovered.

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, front-loaded with the capability and then the cost, with no filler. The pricing sentence earns its place by informing an agent's invocation decision, though the capability sentence is too thin to be maximally useful.

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 paid AI-service tool with no annotations and no output schema, the description omits what the agent gets back, what corpus is retrieved from, and how it differs from siblings. Cost is covered but the operational picture is essentially missing.

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 a single parameter ('prompt') with 100% schema description coverage, so the schema already documents the argument. Per the high-coverage baseline, 3 is appropriate; the description adds no syntax, format, or content guidance beyond what the schema states.

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 expands the acronym in the tool name ('rag_query' → 'Retrieval-augmented generation pipeline') but never states a concrete action, output, or knowledge source. It is essentially a restatement of the name rather than a description of what the tool does with the prompt. With 22 AI-service siblings, it gives the agent nothing to distinguish it from knowledge_recall, longform_qa, or chatbot.

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 when-to-use, when-not-to-use, or alternative guidance. The description does not tell an agent under what circumstances this RAG pipeline should be chosen over any of the many sibling AI-service tools. Usage must be entirely inferred from the name.

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