error_rate_rca

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

No annotations are provided, so the description fully discloses behavior. It explains the data sources (traefik/metrics, haproxy stats), the threshold logic, the cause mapping for different status codes, and the impact of passing 'counters' to skip live pulls. It also notes the specific behavior for caddy targets, providing rich behavioral context beyond a simple 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 with a summary line, detailed behavior, argument explanations, and return schema. It is appropriately sized for a complex tool; every sentence adds value, and it front-loads the core purpose before diving into specifics.

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 and the absence of an output schema, the description is exceptionally complete. It explains the return dict structure with all fields, covers edge cases (caddy, counters mode), and describes the algorithm. There is no significant missing information that would leave an agent uncertain about invocation or interpretation of results.

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 has 0% description coverage, and the description compensates fully with an 'Args' section that explains each parameter's meaning, default values, and usage. For example, it defines error_rate_pct as the threshold for flagging, min_requests as the minimum traffic, counters as injected rows, and target as the proxy name. This adds substantial meaning beyond the schema's bare property names.

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 function: ranks services by 5xx share vs the fleet baseline, identifies causes, and suggests actions. It uses specific verbs like 'rank', 'flags', and 'maps', and distinguishes itself from siblings such as error_counters by emphasizing it is the 'flagship error RCA' and providing detailed cause mapping.

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 context on when to use the tool by explaining its core function and noting special modes like passing 'counters' for pure analysis or handling caddy targets differently. However, it does not explicitly compare itself to alternatives such as backend_health_rca or error_counters, so it lacks explicit when-not guidance, placing it slightly below a perfect score.

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