list_taxonomies

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

With no annotations, the description carries the full behavioral burden and does substantial work: it warns that each taxonomy embeds its full tag tree, that even a few large taxonomies can exceed the per-tool-result token cap, and that results are name-ordered so pagination is stable. It omits any permission/auth context or statement that the call is a read-only, non-mutating operation.

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?

The purpose is front-loaded in one sentence, followed by tightly scoped parameter notes. Every sentence carries information an agent needs to size its request correctly; there is no restatement of the tool name or filler.

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?

An output schema exists, so return-shape explanation is unnecessary, and the description covers the real risk factors (payload size, pagination ordering). It leaves unstated whether results are scoped by permissions or whether there is a total-count signal to drive pagination termination, which an agent planning a full sweep would want.

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 fully compensate, and it does: both params get defaults, a definition of their effect, and the operational reason behind each. The limit explanation (embedded tag trees causing token-cap overflow) is exactly the kind of guidance the bare integer schema cannot convey, and offset is tied to the stable name ordering.

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 line states a specific verb and resource ('List every taxonomy') and adds a meaningful scope detail ('its full tag tree'), which tells the agent this is an exhaustive browse rather than a search. It does not name a sibling, but the sibling set (subjects_list, particles_list, etc.) is resource-disjoint, so ambiguity is low.

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: the agent infers this is the way to enumerate all taxonomies with their tags. There is no explicit 'use this when... instead use X' routing, and no statement of when browsing is preferable to querying or searching.

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