dag-factory

Authors Apache Airflow DAGs declaratively from dag-factory YAML configs. Use when building DAGs declaratively from YAML via dag-factory; creating/editing dag-factory templates/YAML configs,reating/editing dag-factory YAML configs, defaults, dynamic tasks, datasets, or callbacks; or validating dag-factory configurations; upgrading or re-pinning dag-factory.

Quality

90%

Does it follow best practices?

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Securityby

Passed

No findings from the security scan

Quality

Content

88%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 highly actionable, well-sequenced with validation checkpoints, and cleanly sectioned with a useful routing table. The main gap is a missing referenced bundle file (reference/migration.md) and a few prose sections that could be tightened.

Suggestions

Ship the referenced reference/migration.md file (or remove the [reference/migration.md] links) so the progressive-disclosure pointers resolve to real content.

Trim the explanatory prose in 'Before Starting' and 'Determine What the User Needs' to rely more on the routing table, cutting redundant sentences about what dag-factory 'is for'.

Add an explicit 'validate first / back up' note next to `dagfactory convert --override` since it mutates files in place.

Dimension	Reasoning	Score
Conciseness	Mostly efficient with tables, code blocks, and a routing table that compresses guidance well; a few prose passages (e.g. the 'Before Starting' use-case routing and some explanatory sentences) could be trimmed without losing meaning.	4 / 5
Actionability	Provides copy-paste-ready, executable examples throughout — the loader snippet, full YAML DAG, KPO with __type__, dynamic task mapping, datasets, callbacks, and `dagfactory` CLI commands — covering the common cases concretely.	5 / 5
Workflow Clarity	Clear sequencing from 'Before Starting' version checks through a routing table, numbered Project Setup, a Validation Workflow, Cause/Fix troubleshooting, and a final Verification Checklist with explicit validation checkpoints and feedback loops.	5 / 5
Progressive Disclosure	Well-signaled one-level-deep references to [reference/migration.md] for pre-1.0 migration and a clean section structure, but the referenced migration.md file is not present in the bundle, so navigation is not fully resolvable.	4 / 5
	Total	18 / 20 Passed

Description

92%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 specific, complete, and clearly distinct, with a strong 'Use when' clause and concrete trigger scenarios. Its main weakness is a duplicated/typo-ridden phrase ('configs,reating/editing dag-factory YAML configs') that slightly hurts readability and trigger-term cleanliness.

Suggestions

Fix the duplicated typo 'configs,reating/editing dag-factory YAML configs' — remove the repeated fragment and restore the missing 'c' so the trigger list reads cleanly.

Tighten the 'Use when' clause to avoid repeating 'dag-factory YAML configs' verbatim; vary phrasing to add synonym coverage (e.g. 'YAML DAGs', 'dag-factory templates') rather than restating the same term.

Dimension	Reasoning	Score
Specificity	Lists multiple concrete actions — 'Authors Apache Airflow DAGs declaratively from dag-factory YAML configs' plus creating/editing configs, defaults, dynamic tasks, datasets, callbacks, validating, and upgrading/re-pinning — giving comprehensive coverage.	5 / 5
Completeness	Explicitly answers both 'what' ('Authors Apache Airflow DAGs declaratively from dag-factory YAML configs') and 'when' via a concrete 'Use when ...' clause enumerating trigger scenarios.	5 / 5
Trigger Term Quality	Strong natural keywords ('building DAGs declaratively from YAML', 'dynamic tasks', 'datasets', 'callbacks', 'validating', 'upgrading'), but some common variations are missing and the duplicated 'creating/editing dag-factory YAML configs' phrase adds noise rather than new terms.	4 / 5
Distinctiveness Conflict Risk	Names a specific tool (dag-factory) with a clear declarative-YAML niche and distinct triggers, giving minimal overlap risk with other Airflow skills.	5 / 5
	Total	19 / 20 Passed

Validation

93%

Warnings & errors only

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

Validation — 15 / 16 Passed

Validation for skill structure

Criteria	Description	Result
relative_links	Relative link issues: 4 missing	Warning

	Total	15 / 16 Passed

Repository: astronomer/agents
Path: skills/dag-factory/SKILL.md
Commit: dbd9bb7

Reviewed: ~23 hours ago

Table of Contents

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