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

Annotations already cover safety (readOnlyHint true, destructiveHint false, openWorldHint false), and the description adds genuinely useful behaviour beyond them: conformers are energy-scored, optionally minimised, returned lowest-energy-first, and written as molfiles with explicit hydrogens. It also discloses a special case (a 3D molfile input also yields the energy of its own geometry), though it says nothing about cost, runtime, or what happens when no conformers converge.

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?

It is a single long sentence, front-loaded with the purpose, which is good. However, it is dense and packes in a gratuitous validation claim ('whose MMFF94 equals Halgren's OPTIMOL on all 761 validation-suite structures') that does not help an agent decide or invoke, and it repeats the force-field enum in prose.

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?

For a 13-parameter compute tool with an output schema and annotations in place, the description covers what is produced, in what format and order, plus the special 3D-input case. The main residual gap is strategy/parameter selection guidance for a tool with two enums and several tuning knobs.

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 description coverage is 100%, so per-parameter meaning is already carried by the schema and a baseline of 3 applies. The description reinforces the concepts behind minimise, force_field and strategy but adds no syntax, ranges, or practical advice (e.g. when likelyRandom beats pureRandom, or how seed values relate to reproducibility).

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: generating 3D conformers of a small molecule, naming the engine (OpenChemLib torsion-library generator) and the output ordering/format. It is clearly distinct from neighbouring chemistry tools such as canonical_tautomer or enumerate_protonation_states, but it never explicitly contrasts itself with them, leaving differentiation implicit.

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?

Usage is only implied by the described output ('lowest energy first, ... as molfiles with every hydrogen'), which hints at downstream 3D modelling but gives no explicit when-to-use or when-not guidance. Nothing tells the caller which of the four strategies to pick, when to disable minimisation, or how this relates to sibling tools that also transform molecules.

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