list_accessible_models

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

No annotations are provided, so the description carries full responsibility for behavioral disclosure. It reveals that the tool reads from the session cache and returns modules and line item counts, but it does not state that the operation is read-only or describe error handling if init_session hasn't been called. Basic transparency is present, but not comprehensive.

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 description is a single, direct sentence with no filler or redundant details. It efficiently communicates the purpose, scope, and prerequisite.

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?

Given no output schema, the description partially covers the return content by mentioning models, modules, and line item counts. It also includes the prerequisite and scope. It does not detail error conditions or formatting, but for a no-parameter list operation, it is reasonably complete.

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 input schema has zero parameters, so the description is not required to explain parameter syntax. It correctly stays silent on parameters, aligning with the empty schema. The zero-parameter baseline of 4 applies.

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 description uses the specific verb 'List' and names the resource 'all AI-layer models from the session cache', including modules and line item counts. This clearly distinguishes it from sibling tools like read_module_summary or read_module_detail, which focus on individual module details.

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?

The description explicitly states the prerequisite 'Requires init_session,' providing clear context for when this tool can be used. It does not, however, contrast with alternatives or specify when not to use it, which prevents a 5.

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