authoring-language-sdk-tasks

The language-neutral foundation for Airflow language SDKs — implement task logic in a non-Python language while the DAG stays in Python. Use when the user wants to run an Airflow task in another language (Java, Kotlin, Go, or other JVM/native languages), asks how the Python `@task.stub` pairs with native task code, how task/DAG IDs must match across the two sides, how data passes via XCom as JSON, or which language SDKs exist. This skill owns the shared Python-stub pattern and conceptual model; for a specific language's native API, build, and runtime, use that language's skill (e.g. authoring-java-sdk-tasks, authoring-go-sdk-tasks).

Quality

86%

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Securityby

Passed

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Quality

Content

78%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.

A well-structured conceptual foundation skill with an executable Python example, concrete contract guidance, and excellent progressive disclosure to per-language companion skills. Main weakness is minor redundancy between the rules and pitfalls lists.

Suggestions

Consolidate the overlapping items between 'Rules that apply regardless of language' and 'Language-agnostic pitfalls' (ID matching, queue/retries on stub, upstream reference) into a single list to remove redundancy.

Add one short native-side snippet or a concrete pointer to where the matching native IDs appear in a companion skill, so the two-sided contract is shown end-to-end rather than only on the Python side.

Dimension	Reasoning	Score
Conciseness	Lean and assumes competence (no basic Airflow/DAG explanations), but the 'Rules that apply regardless of language' list and the 'Language-agnostic pitfalls' list overlap on IDs-matching, queue/retries-on-stub, and upstream-reference points — minor redundancy that could be tightened.	4 / 5
Actionability	Provides a complete, copy-paste-ready Python stub DAG example and a concrete XCom type table; the native-side code is absent but its absence is explicitly justified as living in per-language companion skills, leaving only minor gaps.	4 / 5
Workflow Clarity	The two-sided model is clearly sequenced (Python stub then native implementation) and the pitfalls list functions as a verification checklist for the cross-side contract; no explicit validate-fix-retry loop is present, but no destructive/batch operation requires one here.	4 / 5
Progressive Disclosure	A clear overview that deliberately stops at shared concepts and routes native API, type mapping, build, and runtime details to well-signaled one-level-deep companion skills via dedicated 'Per-language skills' and 'Related Skills' sections; content is appropriately split with easy navigation.	5 / 5
	Total	17 / 20 Passed

Description

95%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.

A strong, third-person description with explicit 'what' and 'when' coverage, comprehensive natural trigger terms, and clear boundary guidance against sibling per-language skills. Specificity is slightly conceptual but still concrete.

Dimension	Reasoning	Score
Specificity	Names the domain and lists several concrete actions ('implement task logic in a non-Python language', '@task.stub pairs with native task code', 'task/DAG IDs must match', 'data passes via XCom as JSON'), but the actions lean conceptual rather than distinct operations, leaving minor gaps versus a fully comprehensive list.	4 / 5
Completeness	Explicitly answers both what ('language-neutral foundation... implement task logic in a non-Python language while the DAG stays in Python', 'owns the shared Python-stub pattern and conceptual model') and when (a concrete 'Use when...' clause with multiple trigger phrases).	5 / 5
Trigger Term Quality	Comprehensive natural trigger phrases including synonyms and language names — 'run an Airflow task in another language (Java, Kotlin, Go...)', '@task.stub', 'task/DAG IDs must match', 'XCom as JSON', 'language SDKs' — that a user would naturally say.	5 / 5
Distinctiveness Conflict Risk	Clear niche (shared language-neutral foundation) with an explicit boundary clause routing per-language native API/build/runtime to companion skills, minimizing conflict risk with the sibling skills it names.	5 / 5
	Total	19 / 20 Passed

Validation

100%

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 — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository: astronomer/agents
Path: skills/authoring-language-sdk-tasks/SKILL.md
Commit: dbd9bb7

Reviewed: ~22 hours ago

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