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

With no annotations, the description carries the full behavioral disclosure burden. It discloses that the output is a current, real-time signal with named fields, but it never explicitly states that calling it is non-mutating or that it does not execute trades; 'recommended action' could ambiguously suggest execution for a financial tool. This is a meaningful safety-related gap.

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; the core definition and output fields are front-loaded, and the real-time framing is a single clause. This is appropriately sized for the tool's simple scope.

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 one-parameter tool with no output schema, naming the returned fields and token universe is mostly sufficient. However, the description omits output encoding, interpretation of the anomaly/confidence scores, and any safety caveats about the recommended action, leaving some ambiguity for an agent.

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 input schema already documents the single token parameter at 100% coverage, so the baseline is 3. The description adds the Base L2 context and restates the OWB/MOLT enum values, which slightly reinforces meaning but does not add formatting, syntax, or additional semantic 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 names a specific signal product and its output components (wave phase, anomaly score, confidence, recommended action) plus the token universe (OWB/MOLT on Base L2). It is clear enough to distinguish from generic pricing or query tools, though it is noun-led and does not explicitly contrast with prediction_signals or get_prices.

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 phrase 'Real-time market analysis' plus 'current wave phase' implies when the tool is relevant, but the description never states when to prefer it over sibling tools like prediction_signals or get_prices, nor when not to use it. Usage context is present but left to inference.

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