byok-observability-mcp

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 key behavioral traits: it runs checks 'in parallel' and returns a 'status summary table'. However, it lacks details on error handling, timeout behavior, or authentication requirements, which would be helpful for a tool interacting with multiple backends.

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 front-loaded with the core action and scope in the first sentence, followed by a clear usage guideline. Every sentence adds value without redundancy, making it efficient and well-structured.

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's complexity (checking multiple backends) and lack of annotations/output schema, the description is mostly complete. It explains what the tool does and when to use it, but could benefit from mentioning the format of the 'status summary table' or any prerequisites for backend configuration.

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 input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately focuses on the tool's behavior rather than parameters, earning a high baseline score for not introducing unnecessary complexity.

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 specific action ('Run a health check') and the resources involved ('all configured observability backends: Grafana, Prometheus, Kafka UI, Datadog'), distinguishing it from sibling tools that target individual systems. It explicitly answers the question 'are all systems up?' which reinforces its distinct purpose.

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 explicit usage guidance: 'Use this to answer 'are all systems up?''. This clearly indicates when to use this tool (for overall system status) versus sibling tools that focus on specific components like grafana_health or prometheus_health.

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