correlate_health_performance

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

With no annotations, the description carries full burden and does well: it discloses that the tool returns a paired table, r, and an interpretation, and that small samples are flagged loudly. It also clarifies the timing of metrics (night/day vs during round), which is a key behavioral trait for correct interpretation.

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 relatively long but every sentence adds value: purpose, method, metric timing, output, and interpretation. It is well-structured and front-loaded, though it could be slightly more compact without losing information.

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 that an output schema exists, the description does not need to detail return fields. It covers the purpose, parameter semantics, output shape, and important caveats (small samples, correlation sign), making it complete for the tool's complexity.

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 has 0% description coverage, so the description must compensate. It does so by explicitly categorizing health_metric options into daily vs round-window metrics and explaining the lower-is-better sign interpretation for score/putts. This adds crucial meaning beyond the enum arrays.

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 computes a Pearson correlation between health/conditions and performance for each round. It distinguishes itself from sibling tools like get_health_context or get_performance_stats by focusing on the relationship between the two, not just returning raw data.

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?

It provides clear context ('Does recovery affect your golf?') and explains the distinction between daily and round-window metrics, which helps the agent decide when to use this tool. However, it does not explicitly name alternative tools or state when not to use it.

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