Compare to Target Curve

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

With no annotations, the description carries the full burden. It helpfully discloses the output surface ('deviation statistics and recommendations') and the supported curve families, but says nothing about side effects, read-only nature, cost/runtime, or what happens if the measurement lacks coverage over the evaluation range. A compare operation is presumably non-destructive, yet that is implied, not stated.

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?

Three short sentences, front-loaded with the core action and then the supported curve types, then the output. No padding, though the curve list restates the enum and could have been spent on guidance instead.

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 five-parameter analysis tool with no output schema, the description covers what it does, the curve options, and roughly what comes back. It stops short of explaining the alignment-frequency concept or the deviation metrics (e.g., RMS error, peak deviations), which an agent would need to interpret results.

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 100%, so every parameter (target_type, measurement_id, custom_curve_points, evaluation_range_hz, alignment_frequency_hz) is already documented in the schema, including the custom-curve requirement. The description's curve list largely repeats the enum, so baseline 3 applies — it adds little beyond structured 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 gives a specific verb+resource — 'Compare a measurement against a target response curve' — which cleanly separates it from rew_compare_measurements (measurement-to-measurement) and rew_optimize_room. It never names a sibling explicitly, so the differentiation is inferable rather than stated.

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?

There is no when-to-use / when-not-to-use guidance and no mention of prerequisites (e.g., the measurement must already be ingested). An agent is left to infer that this is the target-curve comparison choice versus the sibling comparison tools, and nothing tells it when to prefer 'custom' over the built-in curves.

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