llm_manage_providers

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

No annotations are present, so the description carries the full burden. It mentions list/add/set/update but does not disclose that remove and set_fallback_cascade are destructive or config-mutating, whether changes persist immediately, or how API keys are stored. This leaves behavioral risk under-specified for a management tool.

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?

A single front-loaded sentence with no filler and clear verb phrases. It is concise and easy to scan, though the compactness sacrifices completeness of action enumeration.

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 an 8-parameter tool with a 7-value action enum and no annotations or output schema, the description is too thin. It ignores remove, get_active, and set_fallback_cascade actions, and gives no usage context for the active default flow. An agent would need to inspect the schema to discover half the tool's behavior.

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 100%, so all eight parameters are already documented structurally. The description adds light context that base_url corresponds to endpoints and api_key to key updates, but it does not explain provider_key, default_model, or fallback_cascade beyond what the schema states. A baseline 3 is appropriate given the schema coverage.

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 states a specific resource ('configured LLM providers in your Antigravity vault') and enumerates several distinct actions (list, add endpoint, set active, update API keys). This clearly differentiates it from sibling inference/query tools such as llm_query and llm_list_models. Though it omits some schema actions, the core purpose is unambiguous.

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?

No guidance is provided on when to use this tool versus alternatives; it does not name sibling tools or state conditions for choosing it. An agent must infer from the name that this is for provider configuration rather than model interaction. With siblings like llm_list_models and llm_test_connection, explicit routing would be valuable.

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