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 of behavioral disclosure. It describes the tool's dual behavior (specific metric vs. all metrics) but lacks details on permissions, rate limits, error handling, or response format. It adequately covers basic operation but misses deeper behavioral traits.

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 a single, efficient sentence with zero waste. It front-loads the core purpose and immediately follows with the key usage note, making it easy to parse and understand quickly.

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 low complexity (1 optional parameter, no output schema, no annotations), the description is complete enough for basic use. However, it lacks details on output structure (e.g., format of returned metadata) and error cases, which could be helpful for an agent invoking it.

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 schema description coverage is 100%, so the schema already documents the parameter. The description adds value by explaining the semantic effect of omitting the parameter ('Omit metric_name to list all metadata'), which clarifies usage beyond the schema's technical specification.

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 specific verbs ('Get help text, type, and unit') and resource ('for a specific Prometheus metric'), and distinguishes it from siblings by focusing on metadata retrieval rather than listing metrics (prometheus_list_metrics) or querying values (prometheus_query).

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 guidance on when to use this tool vs. alternatives: 'Omit metric_name to list all metadata' indicates the tool's dual functionality, and the context of sibling tools (e.g., prometheus_list_metrics for listing metric names without metadata) clarifies its role in the ecosystem.

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