natr

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states the action ('fetch') without detailing any behavioral traits such as data sources, rate limits, authentication needs, error handling, or what 'normalized' entails (e.g., scaling, adjustment methods). For a tool with 5 parameters and no output schema, this is a significant gap, offering no insight into how the tool behaves beyond the basic fetch operation.

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?

The description is a single sentence ('Fetch normalized average true range'), which is concise and front-loaded. However, it's under-specified—while not verbose, it lacks necessary detail for a tool with multiple parameters and complex context. The brevity doesn't earn its place by providing sufficient information, making it more of an omission than effective conciseness.

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?

Given the complexity (5 parameters, no annotations, no output schema, and many sibling tools), the description is completely inadequate. It doesn't explain the tool's purpose in context, provide usage guidelines, disclose behavior, or clarify parameters. Without annotations or output schema, the description should compensate but fails to do so, leaving the agent with insufficient information to understand or invoke the tool 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?

The schema description coverage is 0%, meaning none of the 5 parameters (symbol, interval, month, time_period, datatype) are documented in the schema. The description adds no meaning beyond the schema—it doesn't explain what these parameters represent, their expected formats, or how they affect the 'normalized average true range' calculation. With 0% coverage, the description fails to compensate, leaving parameters entirely undocumented.

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 'Fetch normalized average true range' states the action ('fetch') and the metric ('normalized average true range'), but it's vague about what resource or data source this applies to (e.g., financial instruments, time series). It doesn't distinguish from siblings like 'atr' (average true range) or 'trange' (true range), leaving ambiguity about how 'normalized' differs. This is a tautology that mostly restates the tool name 'natr' without clarifying scope or differentiation.

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 description provides no guidance on when to use this tool versus alternatives. It doesn't mention any context, prerequisites, or exclusions, and with many sibling tools (e.g., 'atr', 'trange', 'time_series_daily'), there's no indication of when 'natr' is preferred or what specific scenarios it addresses. This lack of usage information makes it difficult for an agent to select appropriately among similar tools.

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