audio_repeatability_bootstrap

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

With no annotations, the description must carry the behavioral burden. It does disclose a key property—'deterministic'—which suggests reproducibility given the same seed. However, it does not explain the algorithm, how the interval is computed, or any side effects (e.g., whether it modifies anything). It adds some transparency but not enough for a compute tool with no annotation coverage.

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?

A single, compact sentence that is front-loaded with the action and resource. No wasted words; it conveys the core function efficiently.

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 no annotations, no output schema, and three undocumented parameters, the description is incomplete. An agent needs to know what the output structure is, how seed affects results, the statistical interpretation, and any edge cases (e.g., minimum 2 values from schema but not mentioned). The description only covers the high-level purpose, leaving critical operational details missing.

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 0%, and the description does not mention any of the three parameters (seed, trials, values). While parameter names are somewhat self-explanatory, the description provides no elaboration on their roles, defaults, or constraints. This is a significant gap for an agent that must decide appropriate values.

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 states a specific verb ('estimate') and a distinct resource ('repeatability and a deterministic bootstrap confidence interval from repeated scalar measurements'). It clearly differentiates from sibling tools like audio_uncertainty_budget or audio_uncertainty_monte_carlo, which focus on uncertainty but not repeatability. However, it could be clearer on what 'repeatability' precisely means or what the output looks like.

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?

No guidance is given on when to use this tool versus alternatives. It implies use for repeated scalar measurements, but does not specify when a bootstrap approach is preferred over other statistical tools, nor any assumptions (e.g., normality, independence) required. An agent would have to infer that this is the right tool for computing repeatability confidence intervals.

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