likenessforge_models

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

Beyond the annotations it discloses that no weights are downloaded, that a retained background job is returned, and which effect flags apply by default (write) versus conditionally (inference/download). This explains why readOnlyHint is false for an otherwise list-like operation, which the annotations alone would leave puzzling.

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 short sentences, front-loaded with the operation and its key constraint, then the async return behavior, then the effect-flag caveat. No filler and no restatement of the name.

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 tool with a nested permissions object, an output schema, and background-job semantics, the description covers purpose, async behavior, and follow-up sufficiently. Missing details like result ordering or what a "model-backed plugin" contains are tolerable given the output schema handles returns.

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 only 50%, but the description compensates by telling the agent which permission flags this call should acknowledge (write as base, inference/download inspectable via danceflow_component). The empty, required "arguments" object remains unexplained, a minor gap.

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?

"List model-backed plugins without downloading weights" gives a specific verb and resource, and the qualifier distinguishes it from the weight-fetching sibling (likenessforge_download_model). It stops short of naming likenessforge_plugins, so an agent must infer how this differs from the generic plugin listing.

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 gives follow-up routing (poll danceflow_job_status, inspect danceflow_component for conditional effects) which implies the intended workflow, but it never states when to choose this tool over likenessforge_plugins or danceflow_search, nor any prerequisites or exclusions.

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