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

With no annotations at all, the description carries the full burden and does so well: it discloses the three model agents, the decision rule (all elements supported, non-vanishing forces, sigma_F < tau, trust_score >= 0.5), how tau is defined, that trust_score is a Beta posterior that is never exactly 1, per-structure error isolation, and full logging/privacy behavior including what is and is not stored.

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?

Purpose and the verdict rule are well front-loaded, but the logging paragraph is very long and contains forensic detail (Caddy error/unmapped-host log history, journal rotation dates) that does not change whether or how the agent calls the tool. The parenthetical reference to results/RESULTS.md is also not actionable at call time, so not every sentence earns its place.

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?

This is a complex tool with no output schema, and the description fully describes the return surface: verdict, verdict_reasons, trust_score with interval and labels_behind_score, recommended model/blend, energies, force statistics, sigma_F vs tau, domain_warning, and per-structure error entries. Nothing essential for a correct call is missing.

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 heavily for `structures`, spelling out accepted XYZ text forms, separators, the {"Z"/"symbols", "R"} object shape, Angstrom units, and per-call limits. The second parameter `include_forces` is never mentioned, and it is unclear whether it toggles per-atom force output versus the max/mean force already returned in the summary.

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?

Opens with a specific verb+resource+decision: ask the Fittest swarm whether an ML interatomic potential can be trusted for given structures or whether DFT is needed. That is concrete and clearly distinct from the siblings (explain, swarm_status, usage_stats), even though no sibling is named.

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?

Gives explicit applicability constraints — isolated molecules only, no periodic cells, exact element symbols, <=20 structures, 2..100 atoms, enumerated supported elements — which tells the agent when not to call it. It does not, however, route the agent to any sibling for adjacent needs (e.g. explanation of a verdict, service health), leaving that inference to the agent.

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