CtrlK
BlogDocsLog inGet started
Tessl Logo

wagneripjr/airflow-dags

Author, debug and configure Apache Airflow 3 DAGs: TaskFlow API, scheduling and assets, XCom, sensors, dynamic task mapping, and multi-layer test suites

75

Quality

94%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide

SecuritybySnyk

Passed

No findings from the security scan

Overview
Quality
Evals
Security
Files

Quality

Content

86%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The body is well-structured and highly actionable, with executable code and a strong reference architecture that keeps the overview lean while delegating depth to real bundle files. Its only weakness is mild verbosity in the template and a lack of explicit feedback-loop checkpoints in the main flow.

Suggestions

Tighten the TaskFlow DAG Template: trim obvious inline comments (e.g. '# API hammered', '# I/O on every parse') and consider shortening the template to its essential, copy-paste-ready core to lift conciseness.

Add an explicit validate→fix→retry feedback loop to the authoring workflow (e.g. after drafting, run dag.test() then structural validation, fix, re-test) so the main flow surfaces its checkpoints rather than leaving them implicit in the template.

Condense the restated principles and a few redundant Common Mistakes rows that overlap the Critical Rules to further reduce token cost.

DimensionReasoningScore

Conciseness

Mostly efficient — decision table, terse BAD/GOOD pairs, and a reference list assume Claude's intelligence — but the full template and a few restatable comments ('API hammered') could be trimmed, keeping it just below lean.

4 / 5

Actionability

Provides a complete, copy-paste-ready TaskFlow template with concrete default_args (retries, backoff, timeout), specific settings (AIRFLOW__OPERATORS__DEFAULT_DEFERRABLE=True), and BAD/GOOD code covering the common cases.

5 / 5

Workflow Clarity

Clear sequence (Quick Decision Guide → Critical Rules → Template → Common Mistakes → References) with a validation checkpoint via the dag.test() block, though explicit validate→fix→retry feedback loops are not surfaced in the main authoring flow.

4 / 5

Progressive Disclosure

Clear overview SKILL.md with a Quick Decision Guide and Reference Files section mapping needs to 12 one-level-deep, real bundle files, all clearly signaled via markdown links.

5 / 5

Total

18

/

20

Passed

Description

100%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description is third-person, concise yet comprehensive, and clearly answers both what the skill does and when to use it. It lists many concrete actions and a strong set of natural trigger terms with minimal conflict risk.

DimensionReasoningScore

Specificity

Lists multiple specific concrete actions — 'builds data pipelines with TaskFlow API or traditional operators, configures scheduling and asset-driven triggers, wires XCom data passing, sets up sensors and deferrable operators, generates dynamic task mappings, and structures multi-layer test suites' — with comprehensive coverage.

5 / 5

Completeness

Explicitly answers both 'what' (the action list) and 'when' ('Use when creating, debugging, or configuring Apache Airflow 3 DAGs' plus the 'Triggers on…' clause), matching the top anchor.

5 / 5

Trigger Term Quality

Comprehensive natural trigger terms a user would actually say — 'DAG authoring, TaskFlow API, operators, sensors, scheduling, assets, dynamic tasks, XCom, or pipeline testing' — covering the Airflow vocabulary; no file extensions apply to this topic.

5 / 5

Distinctiveness Conflict Risk

Clear Airflow-3-DAG niche with distinct, domain-specific triggers unlikely to collide with other skills; the airflow-dags name reinforces specificity.

5 / 5

Total

20

/

20

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Reviewed

Table of Contents