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

Beyond the read-only and idempotent annotations, it discloses the fixed 161-point density output and the important regime-dependent behavior: Gaussian regimes include sigma_mev and invalidate the returned Landau curve. It also states defaults, although regime selection and the curve's range and units remain unspecified.

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 compact sentences front-load the purpose and outputs, then present the key validity caveat and invocation defaults. The terminology is dense, but each clause supplies useful information with little redundancy.

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 definition is sufficient to invoke the tool with or without arguments and warns about the main output-validity trap, which is especially valuable because there is no output schema. For a specialized numerical tool, it still leaves output units and structure, the density-point abscissa, and regime thresholds unclear.

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?

With 75% schema coverage, most inputs are already documented, but the description usefully adds defaults for all four arguments: muon, 10000 MeV/c, silicon, and 300 micrometres. It does not explain the particle enum codes beyond the default or clarify valid material identifiers.

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 identifies a heavy-particle energy-loss calculation and names distinctive outputs such as MPV, Landau FWHM, finite-transfer Bethe mean, and density points. Its purpose is clear, but it does not explicitly differentiate the tool from siblings such as energy_loss or detector_signal.

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 heavy-particle scope and the warning that the Landau curve is inapplicable in Gaussian regimes provide meaningful context and an explicit limitation. However, there is no guidance on when to choose this tool over energy_loss or another sibling, or what alternative workflow to use in Gaussian regimes.

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