deploy_model

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

With no annotations, the description carries the full burden and does well: it discloses persistent billing, the teardown dependency on badgr_down, hard cost and runtime limits, and a mandatory user confirmation step. It stops short of describing authentication needs or failure modes, leaving some behavioral gaps for a provisioning operation.

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?

Five sentences, front-loaded with the core action, then return values, lifecycle, limits, and a safety instruction. Every sentence earns its place with no repetition or filler.

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 annotations and no output schema, the description supplies the critical missing context: return fields, persistent billing, teardown mechanism, and required safeguards. It could be more complete by noting what happens on provisioning failure or whether the endpoint requires credentials, but the essential information for correct invocation is present.

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 the schema already documents all seven parameters. The description reinforces the required nature of max_runtime_minutes and the $5/hr cap, but adds no syntax, format, or edge-case detail beyond what the schema provides. Baseline 3 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 clearly states a specific verb and resource: 'Provision a persistent OpenAI-compatible endpoint for an LLM model.' It distinguishes the tool from teardown sibling badgr_down via lifecycle context, but does not explicitly name or contrast with other provisioning alternatives like badgr_serve or run_workload.

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?

Usage context is implied through the lifecycle note ('stays up until badgr_down is called') and the requirement to confirm with the user before serving. However, there is no explicit guidance on when to prefer this tool over siblings such as badgr_serve or run_workload, nor are there exclusions or prerequisites beyond the required runtime cap.

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