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Lumino

get_tekton_pipeline_runs_status

Monitor Tekton pipeline and task run status across clusters to identify failures, long-running processes, and performance trends for DevOps observability.

Instructions

Get cluster-wide status summary of all Tekton PipelineRuns and TaskRuns.

Shows running/succeeded/failed counts, recent failures, and long-running pipelines (>1 hour).

Args:
    pipeline_runs_limit: Max PipelineRuns to fetch cluster-wide (default: 500).
    task_runs_limit_per_namespace: Max TaskRuns to fetch per namespace (default: 100).
    max_namespaces: Max namespaces to scan for TaskRuns (default: 20).
    recent_failures_limit: Max recent failures to include in output (default: 10).
    long_running_limit: Max long-running pipelines to include (default: 5).

Returns:
    Dict[str, Any]: Keys: timestamp, sampling_info, pipeline_runs (total, by_status,
                    recent_failures [top N], failures_by_namespace, long_running [top N]),
                    task_runs (total, by_status, recent_failures [top N], failures_by_namespace),
                    insights.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pipeline_runs_limitNo
task_runs_limit_per_namespaceNo
max_namespacesNo
recent_failures_limitNo
long_running_limitNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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 specifying the tool's scope (cluster-wide), what data it collects (counts, recent failures, long-running pipelines), and default behaviors. However, it doesn't mention potential performance impacts of scanning multiple namespaces or any authentication/rate limit considerations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is efficiently structured with a clear purpose statement followed by organized Args and Returns sections. Every sentence adds value: the first explains what the tool does, the parameter explanations clarify controls, and the return section documents output structure without redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (5 parameters, cluster-wide scanning), the description provides complete context: clear purpose, detailed parameter semantics, and comprehensive return structure. With an output schema present, the description appropriately focuses on explaining what the tool does rather than re-describing return values.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage, the description fully compensates by explaining all 5 parameters with clear purposes and default values. Each parameter's role in controlling the scope and output of the status summary is explicitly documented, adding significant value beyond the bare schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'Get' and the resource 'cluster-wide status summary of all Tekton PipelineRuns and TaskRuns', specifying what information is included (running/succeeded/failed counts, recent failures, long-running pipelines). It distinguishes from siblings like 'list_pipelineruns' or 'list_taskruns' by focusing on aggregated status rather than listing individual resources.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for monitoring cluster-wide Tekton pipeline health with aggregated metrics, but doesn't explicitly state when to use this vs. alternatives like 'list_pipelineruns' for detailed inspection or 'analyze_failed_pipeline' for root cause analysis. No explicit exclusions or prerequisites are mentioned.

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

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