learning_pattern_health

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

No annotations are provided, so the description carries full burden. It discloses that the tool reads health metrics (non-destructive), but does not mention authorization needs, rate limits, or any side effects. The behavior is adequately but minimally described.

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 short (two sentences) and front-loaded with the main purpose. It efficiently lists the metrics and a usage hint. No unnecessary words, but could be slightly more 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 no output schema, the description lists the specific metrics returned, which is helpful. It covers the key information for an agent to use this tool: what it does, what it reveals, and when to use it. The single optional parameter is documented in the schema.

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 one optional parameter with description; schema coverage is 100%. The tool description does not add any extra meaning about the parameter beyond what the schema provides, so baseline 3 is appropriate.

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 gets health metrics for the pattern tracking system and lists the specific metrics revealed (total patterns, mature patterns, etc.). It provides a specific verb+resource, though it does not explicitly differentiate from siblings like inspect_status or learning_agent_summary.

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 includes 'Use to monitor learning loop maturity,' giving a clear usage context. However, it does not specify when not to use this tool or mention alternatives among the many sibling tools that might overlap.

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