track_record

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

With no annotations, the description carries the full burden of behavioral disclosure. It explicitly mentions the tool is public, requires no key, takes no arguments, and returns a server-computed JSON with updatedAt and records. This covers key behavioral aspects like authentication and output shape.

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 concise and front-loaded, with the main purpose in the first sentence. It uses only three short paragraphs, each adding distinct value: purpose, usage conditions, and return format. No fluff or redundant repetition.

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 zero-parameter read-only tool, the description provides sufficient context: what it measures, the time window, input requirements, and output format. It could be slightly more detailed about the structure of 'records' but the given information is adequate for understanding what to expect.

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 tool has 0 parameters, and the description explicitly confirms 'Takes no arguments.' This eliminates any ambiguity and adds clarity beyond the empty schema, fully satisfying the parameter semantics dimension.

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 it provides a 'Public track record — aggregated accuracy of the published analytics' over roughly the last 35 days. It specifies the exact resource (historical performance of signals) and uses an explicit verb ('gauge'), distinguishing it from sibling tools that focus on current data (e.g., get_snapshot, get_gex).

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 gives a clear use case: 'Use it to gauge how the signals have performed historically.' It also states it's public and requires no key. While it doesn't explicitly exclude other tools, the unique purpose makes the intended usage clear.

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