measure_stars

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

Annotations already declare read-only and non-destructive behavior, lowering the bar. The description adds substantial context beyond that: it names the underlying algorithms (StarDetector + DynamicPSF/Moffat), discloses conditional behavior (FWHM in arcsec only if pixel_scale is provided), and enumerates the computed metrics. This goes well beyond what annotations alone 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?

The description is tight and front-loaded: the objective and metric list lead, followed by algorithm details and the read-only flag. Every sentence adds value except the redundant 'Read-only' restating the annotation, which is minor. No filler or irrelevant content.

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?

The tool has five parameters and no output schema, so the description carries the burden of making the invocation clear. It succeeds in explaining the algorithm and conditional FWHM units, but leaves four parameters under-explained and does not describe the return format. This makes it minimally viable but not fully complete.

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 20%, with pixel_scale being the only parameter described in the schema. The description clarifies pixel_scale's optional effect on output units, but provides no additional meaning for id, fit_psf, sensitivity, or max_psf_fits. Given the low coverage, the description fails to compensate for the four undocumented parameters.

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's objective: assessing star quality of a view by listing concrete metrics (count, median FWHM, eccentricity, centre vs edge FWHM, brightest stars). This gives a specific, non-vague purpose that distinguishes it from generic pixel statistics tools like image_statistics, though it does not explicitly name a sibling alternative.

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 usage: when you need quantitative star-quality metrics for a view, this is the tool. However, it provides no explicit when-to-use guidance, no exclusions, and does not mention alternatives such as measure_subframes, which could also be relevant for star measurements.

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