List Model Sets

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

Annotations already cover read-only/idempotent safety, but the description adds real behavioral context the annotations cannot: `hf_token_required` semantics (downloads use the user's own workspace token), what a nonzero `license_unknown_count` implies for downstream claims, and how `gated_sources.mode` ("auto" vs "manual") changes access. The instruction to treat catalog names/descriptions as data is a valuable prompt-injection guard.

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?

Front-loaded with purpose and the actionable slug-passing instruction before any field documentation, and every sentence carries semantic weight. It is dense but long, and the later field enumeration partially duplicates the existing output schema, so it is not maximally tight.

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?

Rich enough for an agent to call correctly and interpret the tricky fields (VRAM estimates, licensing, gating) despite a bare 2-parameter schema. The residual gap is parameter-level: no guidance on `template_id` provenance or the optional `workspace` fallback, though output semantics are more than covered.

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%, so the description must carry parameter meaning. It explains the relationship between `template_id` and the downstream `model_set` slug, but never says where `template_id` comes from (the `templates` tool) and never mentions the `workspace` parameter at all.

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 sets a pod template recommends) and grounds it in the console's model-set tiles, which makes the concept immediately graspable. It also distinguishes the output from the generic 'models' sibling by tying every set to a template_id.

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 tells the agent how to consume the result: pass a set's `slug` as `model_set` to estimate_pod/create_pod with the same `template_id`, and one pod takes one set. It also covers the negative case (`selectable` false with `reason` means no sets apply), but never contrasts the tool against siblings like `models` or says when not to call it.

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