ppk2_measure

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

With no annotations provided, the description fully discloses behavioral traits: it starts continuous sampling, discards a settling window, collects samples, stops, and computes statistics. It reveals the sampling rate (~100k samples/s), that raw samples are never returned by default, and explains the downsampled series option. Returns are detailed with units.

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 well-structured with an introductory sentence, process flow, parameter list, and return description. While comprehensive, it maintains clarity without excessive verbosity. The use of bullet points for arguments and clear sectioning earns a high score, though a slight reduction for minor redundancies (e.g., 'Args:' could be more compact).

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 and the tool's complexity (hardware interaction, prerequisite, high-frequency sampling), the description is remarkably complete. It covers prerequisites, process, parameter constraints, return values, and edge cases (settling window). The presence of an output schema further supports completeness.

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 description coverage is 0%, but the description fully compensates: it defines each parameter with purpose, defaults, ranges (duration_seconds: 0.05–60, settle_ms: default 200), and semantics (include_series as a flag, series_points as target count). This adds significant meaning beyond the schema fields.

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 uses a specific verb ('Sample') and a clear resource ('current') with scope ('for a fixed duration and return summary statistics'). It clearly distinguishes from sibling tools like ppk2_configure (setup) and ppk2_power (power control) by describing a measurement action.

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 explicitly states the prerequisite ('Requires a prior ppk2_configure') and outlines the process (continuous sampling, settling window, collection, stopping). It implies when to use (after configuration) but does not explicitly mention when not to use or alternative tools, though the sibling context provides differentiation.

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