Ticker Analytics

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

Annotation readOnlyHint=true already signals a safe read operation. The description adds valuable behavior: it explains the tool's multimodal nature (eight analyses) and even specifies that some analyses have sub-views ('view' argument) and which arguments are relevant per analysis. It does not disclose any side effects (none expected) or potential errors, but given the annotation coverage, it adds sufficient context beyond the schema.

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?

Despite its length, the description is well-structured and every sentence earns its place. It opens with a clear statement of purpose, then uses a concise bullet-point list to enumerate the eight analyses and their specific views, followed by a compact Args section and a simple Returns note. The structure allows quick scanning while providing necessary detail for such a multi-purpose tool.

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 tool's complexity (eight analyses, multiple nuance fit-for-purpose parameters) and the absence of an output schema, the description does a good job of covering the input side and indicating the output ('The selected analytics payload with a compact summary'). It could be more explicit about the structure of the return payload or what the 'compact summary' contains, but for a read-only analytics tool, this is adequate. No output schema means the description carries some burden, but it meets the bar.

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 coverage is 0%, so the description must compensate, and it does fully. Every parameter is explained in prose: ticker, analysis (with a list of valid values), expiration (only for greeks_exposure), days (for specific analyses), view (for skew/hv_regimes), compare_with (for correlation). It also notes defaults (days default 252) and which arguments are optional. This goes far beyond the bare schema titles and adds meaningful semantics.

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 clearly states the tool's purpose: 'Get a specific per-ticker analytics view.' It further enumerates eight distinct analyses, making it obvious what the tool covers and distinguishing it from siblings that focus on single analytics (e.g., get_iv_rank, get_volatility_cone). The verb 'get' and the resource 'per-ticker analytics' are specific and unambiguous.

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 implicitly tells when to use this tool: whenever one of the eight listed analyses is needed. It provides per-analysis context (e.g., 'borrow_rate' for short-squeeze context) and clarifies which arguments apply to which analyses. However, it does not explicitly contrast with alternatives or state when NOT to use this tool (e.g., 'for volatility cone, use get_volatility_cone instead'), so it stops short of full exclusion guidance.

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