dm_spectrum_info

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

No annotations exist, so the description carries the full behavioral burden. It does disclose critical maturity information (experimental, NOT_TESTED, synthetic-only) and enumerated refusals, but says nothing about permissions, error behavior, or return shape. It is strong on scope limitations but incomplete on other behavioral traits.

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 compact and front-loads its core purpose before moving to limitations. Each clause adds substance, though the run of negatives becomes dense and could be grouped more clearly.

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?

No output schema exists, so the description must, and does, indicate what the tool returns: axis, spatial selection, and calibration. Maturity and refusal conditions are covered. Minor gaps remain in return-structure detail, but it is sufficient for correct invocation.

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%, so all three parameters are already documented in the schema, and the baseline is 3. The description restates a few constraints such as eV/keV calibration and the 4D rejection without adding syntax or semantics beyond what the schema already supplies.

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?

States a specific verb and resource: read spectral axis, spatial selection, and energy calibration for an explicitly named dataset. It is distinguishable from write/reduction tools like dm_spectrum_integrate through its stated exclusions, though it never names a sibling tool directly.

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?

Explicitly limits scope: no automatic spectrum-type identification, no background subtraction, no quantitative analysis, rejects 4D diffraction and nm-calibrated energy axes. It also flags genuinely useful context: experimental status with only synthetic-data coverage, so an agent knows not to trust it on real EDS/EELS/SI data. It does not point to an alternative tool for those rejected cases.

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