airflow-operator-creator
Airflow Operator Creator - Auto-activating skill for Data Pipelines. Triggers on: airflow operator creator, airflow operator creator Part of the Data Pipelines skill category.
36
Quality
3%
Does it follow best practices?
Impact
96%
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/airflow-operator-creator/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 severely underdeveloped, essentially just restating the skill name without explaining capabilities or usage triggers. It lacks concrete actions, natural trigger terms, and explicit guidance on when Claude should select this skill. The redundant trigger terms and missing 'Use when...' clause make this ineffective for skill selection.
Suggestions
Add specific concrete actions like 'Creates custom Apache Airflow operators, defines sensor classes, implements hooks for external systems, generates boilerplate operator code'
Add a 'Use when...' clause with natural trigger terms: 'Use when the user asks to create a custom Airflow operator, build a sensor, implement a hook, or extend Airflow functionality'
Include natural keyword variations users might say: 'custom operator', 'Airflow plugin', 'DAG component', 'BaseOperator', 'PythonOperator subclass'
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | The description only names the skill ('Airflow Operator Creator') without describing any concrete actions. There are no verbs or specific capabilities listed - no mention of what creating an operator involves or what outputs are produced. | 1 / 3 |
Completeness | The description fails to answer 'what does this do' beyond the name itself, and provides no 'when should Claude use it' guidance. There is no 'Use when...' clause or equivalent explicit trigger guidance. | 1 / 3 |
Trigger Term Quality | The trigger terms are redundant ('airflow operator creator' listed twice) and overly specific. Missing natural variations users might say like 'create airflow operator', 'custom operator', 'DAG operator', 'python operator', or 'airflow plugin'. | 1 / 3 |
Distinctiveness Conflict Risk | The mention of 'Airflow Operator' provides some specificity to Apache Airflow domain, but 'Data Pipelines' category is broad. Without concrete actions described, it could conflict with other Airflow-related or data pipeline skills. | 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 actual guidance on creating Airflow operators. It consists entirely of generic meta-descriptions about what the skill supposedly does, without any concrete code examples, operator patterns, or actionable instructions. The content fails every dimension of the rubric.
Suggestions
Add executable Python code showing how to create a basic custom Airflow operator (subclassing BaseOperator with execute method)
Include concrete examples of common operator patterns (e.g., sensor operators, transfer operators) with copy-paste ready code
Define a clear workflow: 1) Create operator class, 2) Implement execute(), 3) Register in DAG, 4) Test locally
Remove all generic boilerplate ('automated assistance', 'industry best practices') and replace with specific Airflow operator implementation details
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is padded with generic boilerplate that explains nothing specific about Airflow operators. Phrases like 'automated assistance' and 'industry best practices' are filler that Claude doesn't need. | 1 / 3 |
Actionability | No concrete code, commands, or specific guidance is provided. The skill describes what it does in abstract terms but never shows how to actually create an Airflow operator. | 1 / 3 |
Workflow Clarity | No workflow or steps are defined. Claims to provide 'step-by-step guidance' but includes zero actual steps for creating operators. | 1 / 3 |
Progressive Disclosure | No references to external files or structured content organization. The content is a flat, uninformative placeholder with no navigation to detailed materials. | 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
0c08951
- Reviewed
Table of Contents
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