beam-pipeline-builder
Beam Pipeline Builder - Auto-activating skill for Data Pipelines. Triggers on: beam pipeline builder, beam pipeline builder Part of the Data Pipelines skill category.
36
3%
Does it follow best practices?
Impact
100%
1.02xAverage score across 3 eval scenarios
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./planned-skills/generated/11-data-pipelines/beam-pipeline-builder/SKILL.mdQuality
Discovery
7%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
This description is extremely minimal and template-like, providing almost no useful information for Claude to determine when to select this skill. It lacks concrete actions, meaningful trigger terms, and any explicit guidance on when to use it. The repeated trigger term and boilerplate structure suggest this was auto-generated without customization.
Suggestions
Add specific concrete actions the skill performs, e.g., 'Creates Apache Beam pipeline code, configures PCollections, defines transforms, and sets up runners for batch and streaming data processing.'
Add an explicit 'Use when...' clause with natural trigger terms, e.g., 'Use when the user asks about Apache Beam, Dataflow pipelines, PCollections, beam transforms, ETL pipelines, or streaming/batch data processing.'
Remove the redundant duplicate trigger term and replace with varied, natural keywords users would actually say when needing this skill.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | The description names 'Beam Pipeline Builder' and 'Data Pipelines' but provides no concrete actions. There is no mention of what the skill actually does—no verbs describing specific capabilities like creating, configuring, transforming, or deploying pipelines. | 1 / 3 |
Completeness | The 'what' is essentially absent—it only names the skill category without describing capabilities. The 'when' is reduced to a redundant trigger phrase with no explicit 'Use when...' clause or meaningful trigger guidance. | 1 / 3 |
Trigger Term Quality | The only trigger terms listed are 'beam pipeline builder' repeated twice. Missing natural user terms like 'Apache Beam', 'Dataflow', 'PCollection', 'ETL pipeline', 'streaming pipeline', 'batch processing', or 'data transformation' that users would actually say. | 1 / 3 |
Distinctiveness Conflict Risk | The mention of 'Beam' provides some specificity to Apache Beam pipelines, which narrows the domain somewhat. However, 'Data Pipelines' is broad enough to overlap with other pipeline-related skills, and the lack of specific actions makes it harder to distinguish. | 2 / 3 |
Total | 5 / 12 Passed |
Implementation
0%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This skill is an empty placeholder that provides no actionable content about Apache Beam pipeline building. It consists entirely of generic meta-descriptions ('Provides step-by-step guidance', 'Follows industry best practices') without any actual guidance, code, commands, or technical substance. It fails on every dimension of the rubric.
Suggestions
Add concrete, executable Apache Beam pipeline code examples (e.g., a minimal Python/Java pipeline with ReadFromSource → Transform → WriteToSink) that Claude can adapt.
Define a clear workflow for building a Beam pipeline: 1) Define PipelineOptions, 2) Build the pipeline graph, 3) Add transforms, 4) Validate with pipeline.run() in DirectRunner before deploying, 5) Deploy to Dataflow/Flink/Spark runner.
Remove all generic filler text ('Provides step-by-step guidance', 'Follows industry best practices') and replace with specific Beam patterns like windowing, triggers, side inputs, and CoGroupByKey with concrete examples.
Add references to supporting files for advanced topics (e.g., STREAMING.md for streaming patterns, TESTING.md for pipeline testing with TestPipeline, RUNNERS.md for runner-specific configuration).
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is padded with generic filler that tells Claude nothing useful. Phrases like 'Provides step-by-step guidance' and 'Follows industry best practices' are vacuous. It explains what triggers the skill rather than providing any actual technical content about Apache Beam pipelines. | 1 / 3 |
Actionability | There is zero concrete, executable guidance. No code examples, no commands, no specific API references, no pipeline patterns. The entire skill describes what it could do rather than instructing Claude how to do anything. | 1 / 3 |
Workflow Clarity | No workflow steps are defined at all. There is no sequence of actions, no validation checkpoints, and no process for building, testing, or deploying a Beam pipeline. | 1 / 3 |
Progressive Disclosure | The content is a monolithic block of generic text with no references to supporting files, no structured navigation, and no bundle files to support it. There is nothing to progressively disclose because there is no substantive content. | 1 / 3 |
Total | 4 / 12 Passed |
Validation
81%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 9 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
allowed_tools_field | 'allowed-tools' contains unusual tool name(s) | Warning |
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 9 / 11 Passed | |
- Commit
172d892
- Reviewed
Table of Contents
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