byok-observability-mcp

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the output ('list current on-call participants') and a use case ('find who to page'), but fails to describe critical behaviors like response format, pagination, error handling, authentication needs, or rate limits. For a tool with zero annotation coverage, this is a significant gap.

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 highly concise and front-loaded, consisting of two short sentences that directly state the tool's function and utility. Every word earns its place, with no redundant or vague phrasing, making it efficient for an AI agent to parse.

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 lack of annotations and output schema, the description is incomplete. It doesn't explain the return format (e.g., list structure, fields like names or schedules), error scenarios, or operational constraints. For a tool that likely returns critical on-call data, more context is needed to ensure reliable use by an AI agent.

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?

The tool has 0 parameters with 100% schema description coverage, so the schema fully documents the inputs. The description adds no parameter information, which is acceptable here since no parameters exist. A baseline of 4 is appropriate as it doesn't need to compensate for any gaps.

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: 'List current on-call participants for all schedules.' It specifies the verb ('List'), resource ('on-call participants'), and scope ('for all schedules'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from sibling tools like 'opsgenie_list_alerts' or 'opsgenie_ack_alert', which prevents a perfect score.

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 implied usage guidance with 'Helps you find who to page,' suggesting it's for identifying contacts during incidents. However, it lacks explicit when-to-use rules, alternatives (e.g., vs. 'opsgenie_list_alerts' for alert details), or prerequisites, leaving some ambiguity for an AI agent.

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