femm_compare_results

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

With no annotations, the description carries the full behavioral burden. It does disclose useful traits: rows are matched on the first column, and differences beyond `rtol` are flagged. However, it says nothing about side effects, session/auth requirements, or what the comparison returns, leaving real gaps relative to a no-annotation baseline.

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 sentences, front-loaded with the core action, then matching semantics, then usage examples. Some density in the parenthetical '(rows matched on the first column, e.g. angle)', but every clause carries information and nothing is wasted.

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?

There is no output schema, so the description should ideally convey the shape of the comparison result; it only notes that out-of-tolerance differences are flagged. Combined with two undescribed params, it is adequate for calling the tool but incomplete about what comes back.

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 0%, so the description must compensate, and it does well for the three substantive params: `a`/`b` are explained as paths to experiment .json files or raw JSON text, and `rtol` is explained as the difference tolerance. `label_a`/`label_b` are not described, but they are self-evident labels with defaults, making this a strong compensation.

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 (A/B comparison) and resource (two experiment results), and goes further to specify exactly what is compared: every numeric summary value and every common numeric column. No sibling tool overlaps this function, so an agent can identify it unambiguously.

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 says when to use it: 'to compare mesh refinements, the rotate vs air-gap-element methods, or two designs.' This is clear context, but it does not name a competing tool or state when-not to use it (e.g., comparing a single result or non-experiment data).

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