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

The annotations already indicate read-only, idempotent, non-destructive behavior, and the description adds meaningful context beyond those hints: walk-forward methodology and the no-look-ahead property ('Uses only prior buckets to build the baseline'). This gives an agent important information that annotations alone do not convey.

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 sentences, each carrying distinct and valuable content. The main action is front-loaded, the methodology detail is concise, and there is no redundancy with the schema or annotations.

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 rich annotations, optional parameters with defaults, and no output schema, the description mostly suffices: it explains the tool's purpose and its key methodological safeguard. Still, it does not explicitly state the return format or explain how the threshold parameters affect behavior, which would round out the picture.

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 description coverage is only 50%, and the description adds no direct parameter-level meaning. Parameters like minConfidence and minBaselineSamples are not explained, and the 'prior buckets' note is not connected to the sampling parameters. An agent must infer semantics from names and defaults alone.

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 opens with a specific verb, 'Validate', names the resource ('intelligence signals'), and lists concrete analyses (walk-forward forward returns, win rates, MFE/MAE, confidence calibration). This clearly distinguishes it from the get_* sibling tools, which are retrieval-oriented.

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 implies that this tool is for validating signal quality rather than for fetching market data, but it never explicitly states when to choose it over alternatives. It also does not name sibling tools like get_track_record that might serve a similar evaluative purpose, leaving selection somewhat to inference.

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