Lumino

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

With no annotations provided, the description carries full burden and does well by disclosing key behavioral traits: it's a read-only analysis tool (implied by 'detect'), uses statistical analysis with a specific threshold (2.5 standard deviations), analyzes recent runs (default 50), and returns structured anomaly details. It doesn't mention rate limits, authentication needs, or data retention policies, but covers the core behavior adequately.

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 perfectly structured and concise: purpose statement first, method and threshold second, parameters third, return format fourth. Every sentence earns its place with zero wasted words, and information is front-loaded appropriately for agent comprehension.

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 moderate complexity (statistical analysis), no annotations, and the presence of an output schema (implied by the Returns section), the description is complete enough. It covers purpose, method, parameters, and return structure, providing sufficient context for an agent to understand when and how to use this tool effectively.

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?

Schema description coverage is 0%, so the description must compensate. It successfully adds meaning for both parameters: 'namespace' is explained as 'Kubernetes namespace to analyze' and 'limit' as 'Max recent PipelineRuns to analyze (default: 50)'. This provides clear semantic context beyond the bare schema, though it doesn't specify format constraints or valid ranges.

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 ('detect anomalies'), the target resources ('Tekton PipelineRuns/TaskRuns'), and the method ('z-score statistical analysis'). It distinguishes itself from siblings like 'detect_log_anomalies' by focusing on execution time analysis rather than log patterns, and from 'analyze_failed_pipeline' by targeting statistical outliers rather than failures.

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 implies usage context through the statistical method and threshold (2.5 standard deviations), suggesting it's for identifying performance outliers. However, it doesn't explicitly state when to use this tool versus alternatives like 'ci_cd_performance_baselining_tool' or 'list_recent_pipeline_runs', nor does it mention prerequisites or exclusions.

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