list_open_models

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

The readOnlyHint annotation already establishes this is a safe read, and the description adds the meaningful detail that results reflect models online at the present moment rather than a static catalog. It does not cover result ordering, whether offline models are excluded, or what the response shape looks like, so it adds only moderate context beyond the annotation.

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?

One compact sentence, front-loaded with the resource and scope, with the filter instruction at the end. The task enumeration duplicates the schema enum, which is mild redundancy, but it aids discovery and costs little space.

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?

For a read-only, single-optional-parameter listing tool with no output schema, the description covers what is listed, the liveness qualifier, and the filter. The remaining gap is the shape of each returned entry, which is only loosely implied by 'with the tasks each can do'.

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 description coverage is 0%, but the single parameter is a self-describing enum, and the description clarifies its role as a filter and enumerates the same eleven task values. It adds the semantic ('filter by task') but no syntax, default-behavior, or multi-value guidance, so it is adequate rather than rich.

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 gives a specific verb-and-resource picture: it lists open AI models that are online on the BitPull network right now, along with the tasks each supports. It is clear about what is returned, but it never distinguishes itself from siblings such as list_ai_models or list_group_models, so an agent cannot tell from the text alone which listing tool to pick.

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?

'Filter by task' and 'right now' imply the usage context: query live availability, optionally narrowed to a capability. There is no explicit when-to-use versus when-not-to-use guidance and no named alternative among the sibling listing tools, so routing must be inferred.

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