register_endpoint

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

With no annotations provided, the description carries the full burden. It discloses that the tool persists to models.yaml and probes the endpoint, which is useful, but it omits critical behavioral details such as whether the operation is idempotent, what happens on probe failure, error handling, or potential side effects like network timeouts. For a tool that mutates state and performs network calls, this is insufficient.

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?

The description is brief at two sentences plus a code block, which is concise. However, it lacks a clear structure: the parameter explanations are dropped inline rather than presented as a list, and key scoping info is not front-loaded. It's not bloated, but it could be more organized.

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 the tool has five parameters, no annotations, no output schema (schema is present but no output schema referenced), and 0% schema description coverage, the description is incomplete. It does not explain the return value of probing, error conditions, or how the endpoint is validated. An agent cannot fully predict the tool's behavior from the description alone.

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 explain parameters. It explicitly covers base_url (server root exposing /v1/messages) and backend (enum of llama.cpp, vllm, ollama, other), but fails to describe the other three parameters: name, host, and notes. Two of five parameters are explained, leaving the rest undocumented.

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 the tool's purpose: 'Add or update an inference endpoint (persisted to models.yaml) and probe it.' The verb 'add or update' combined with the resource 'inference endpoint' is specific, and the persistence detail distinguishes it from related tools like register_model or list_models.

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 provides no explicit guidance on when to use this tool versus alternatives. It mentions the tool registers endpoints but doesn't indicate when to prefer it over other registry-related tools, nor does it list any prerequisites or exclusions. The context about base_url and backend is informative but not usage-routing guidance.

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