arf_list_classes

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

With readOnlyHint=true already covering the safety profile, the description adds real value: the vocabulary is returned even when `.mddata` is absent, and it warns that token positions shift when a value splits into two tokens (G_uralensis) so positions must not be used for specification. That is a non-obvious behavioral caveat an agent would otherwise get wrong.

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 is front-loaded in the first line, followed by discovery usage, return structure, and a caveat, in that order. Every sentence carries information; the token-position warning is dense but necessary rather than padding.

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 carries the burden of explaining returns, and it does so by naming the sample_token_vocabulary.tokens fields. Combined with the offline-availability note and the positional caveat, an agent has enough to call it correctly; only concrete field types/shape detail is left implicit.

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?

Zero parameters, so the baseline is 4. The description goes further by describing the shape of entries under sample_token_vocabulary.tokens (occurrence count, role breakdown, position within sample names), which tells the agent how to interpret the returned vocabulary it will feed into other tools' parameters.

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 first sentence states a specific verb and resource: returns factor tokens usable for filtering/grouping, covering both Class IDs and sample names. Siblings like arf_list_tags and arf_list_sample_roles list different vocabularies, and this description's scoping to filtering/grouping factors makes the distinction clear without opening the schema.

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?

It explicitly positions itself as the entry point for discovering what can be written into class_ids / group_levels / group_factors / group_a / group_b, which is concrete when-to-use guidance. It does not name a when-not condition or an alternative sibling, keeping it just short of a 5.

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