List models

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

Annotations already declare readOnlyHint and openWorldHint, so safety is covered. The description adds genuinely useful context beyond that: the returned field set and the meaning of each plan tier (any/casual/pro). It does not cover pagination or defaults for limit/sort, which are left to the schema.

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 tight sentences: what it returns, how to filter, and why to call it. No filler, and the field list is front-loaded before the filtering guidance.

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?

No output schema exists, yet the description enumerates the return fields, so an agent knows what comes back. Minor gap: it doesn't state default limit or that results are paginated/truncated, which matters for a 6-param listing tool.

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 100%, so the baseline is 3, but the description adds real meaning by expanding the plan enum into concrete user tiers ('any = every account with a balance; casual = Casual or Pro; pro = Pro only'), disambiguating the one parameter most likely to be misunderstood.

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?

Specific verb 'List' plus resource 'Obscurify.ai chat models', with the returned fields enumerated (IDs, context window, pricing, tool support, plan). It clearly distinguishes itself from ask/chat/second_opinion by framing itself as the model-discovery step for those tools.

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 states when to use it: 'Use it to find a model ID for ask, chat or second_opinion, or the cheapest model with what you need.' It also gives the filter-to-goal mapping ('Filter by name, plan, price or tool support') and notes no API key is required, removing a likely blocker.

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