cursor_models

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

No annotations are provided, so the description carries the burden. It usefully discloses fallback behavior ('or a known list when it offers none'), implying results may not always reflect the local install, but says nothing about ordering, completeness, auth requirements, or latency.

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 sentences, zero waste, and the primary purpose is front-loaded. The pricing pointer is not filler since pricing is not returned by the tool and users frequently need it.

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?

With no annotations and no output schema, the description still covers what is returned (model ids), the fallback case, and how to consume the output. Only the exact return shape (e.g., array vs. text, ordering) is left unspecified, which is minor for a zero-arg list 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?

The tool takes zero parameters, so there is no parameter surface to document and the baseline of 4 applies. The description correctly implies no arguments are needed.

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 ('List the model ids the installed cursor-agent offers') plus the underlying mechanism (its `models` command). An agent can immediately distinguish it from siblings like cursor_agent, which is the tool that consumes these ids.

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 clear downstream context: 'Use an id with cursor_agent's model parameter,' which tells the agent when this tool is needed (before invoking cursor_agent with a model). There is no explicit when-not-to-use or stated alternative, but the routing intent is unambiguous.

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