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Lumino

list_taskruns

Retrieve Tekton TaskRuns in a Kubernetes namespace, with optional filtering by PipelineRun to monitor CI/CD pipeline execution status and details.

Instructions

List Tekton TaskRuns in a namespace, optionally filtered by a specific PipelineRun.

Args:
    namespace: Kubernetes namespace to query.
    pipeline_run: Optional PipelineRun name to filter by.

Returns:
    List[Dict]: TaskRuns with keys: name, task, pipeline_run, status, started_at, completed_at, duration.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
namespaceYes
pipeline_runNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

With no annotations provided, the description carries the full burden. It describes the read-only nature ('List', 'query') and the return format, but doesn't mention important behavioral aspects like pagination, rate limits, authentication requirements, or error conditions that would be crucial for an agent to use this tool effectively.

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 perfectly structured and concise. It starts with the core purpose, then provides clear parameter explanations in an Args section, and concludes with return value details. Every sentence earns its place with zero wasted words.

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

Completeness4/5

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

Given the tool's moderate complexity, no annotations, and the presence of an output schema (which covers return values), the description is mostly complete. It explains parameters well and provides return format details. However, it lacks some behavioral context that would be helpful for an agent, such as error handling or performance characteristics.

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?

The description provides excellent parameter semantics despite 0% schema description coverage. It clearly explains what 'namespace' and 'pipeline_run' parameters mean ('Kubernetes namespace to query', 'Optional PipelineRun name to filter by'), adding significant value beyond what the bare schema provides.

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 specific action ('List Tekton TaskRuns'), the resource ('in a namespace'), and distinguishes it from siblings by mentioning optional filtering by PipelineRun. It provides a complete picture of what the tool does beyond just the name.

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

Usage Guidelines4/5

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

The description explicitly states when to use optional filtering ('optionally filtered by a specific PipelineRun'), providing clear context. However, it doesn't explicitly mention when NOT to use this tool or name specific alternatives among the many sibling tools.

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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