add_endpoint

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key behavioral traits: it's a mutation tool (implied by 'Register'), includes an 'overwrite' parameter for handling existing endpoints, and mentions authentication via headers. However, it doesn't cover rate limits, error handling, or side effects beyond the basic 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?

The description is well-structured and front-loaded with the core purpose, followed by a bullet-point-like parameter breakdown. Every sentence earns its place by providing essential information without redundancy, making it efficient and easy to parse for an AI agent.

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?

The description is largely complete for a mutation tool with no annotations but with an output schema (which handles return values). It covers the tool's purpose and all parameters in detail. However, it lacks some behavioral context like error conditions or system state requirements, which would be beneficial given the tool's complexity.

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?

Given 0% schema description coverage, the description fully compensates by providing detailed semantic explanations for all 8 parameters. It clarifies usage (e.g., 'name' as a unique identifier for targeting, 'url' formats for gRPC/HTTP, 'protocol' options, 'signals' defaults, 'headers' for auth, 'insecure' as gRPC-only, 'timeout_seconds' as per-request, and 'overwrite' for replacement), adding significant value beyond the bare schema.

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 with a specific verb ('Register') and resource ('OTLP destination'), distinguishing it from siblings like 'remove_endpoint' (deletion) and 'list_endpoints' (querying). It precisely defines what the tool does without being vague or tautological.

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 implies usage for registering OTLP endpoints but provides no explicit guidance on when to use this tool versus alternatives like 'clear_endpoints' or 'remove_endpoint'. It lacks context about prerequisites, such as whether the system must be in a specific state, or exclusions for when not to use it.

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