dm_spectrum

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

No annotations, so the description bears the full burden: it discloses experimental status, synthetic-only coverage, float64 arithmetic, no unit assumption, no interpolation or background subtraction, and half-open window semantics. These are exactly the behavioral facts an agent needs before calling a real-data spectrum pipeline.

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?

One dense paragraph that front-loads the operation and then layers constraints, with zero filler. Slightly compressed (many clauses chained with semicolons), but every clause carries load-bearing 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?

With no output schema, the description still conveys the return content (channel centers plus float64 intensities), and the validation/limitation surface is well covered. It could be more explicit about the returned array shape, but for a 5-param tool with full schema coverage this is close to 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 coverage is 100% and every parameter already carries a detailed description (energy axis NumPy ordering, non-clamping spatial bounds, [low,high) window). The description only restates the window and reduction semantics, adding little beyond the schema. Baseline 3 is appropriate.

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 and resource: it extracts raw channel centers and float64 intensities and reduces them by sum/mean over a spatial range. It also scops what spectrum data is accepted (eV/keV energy-axis calibration, no 4D diffraction). It doesn't name siblings such as dm_spectrum_integrate, so differentiation is implicit rather than explicit.

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?

Clear negative guidance: no background subtraction, no spectrum-type auto-identification, no element/chemical quantification, no unit assumption, rejects 4D diffraction and nm-calibrated axes. The 'experimental, real EDS/EELS/SI NOT_TESTED, synthetic only' note gives a strong when-not-to-trust signal. Missing explicit routing to an alternative tool for the excluded cases.

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