apache

Generate verified recipe playbooks from AIPs with PR implementations (post mode), or speculative user stories from AIPs without implementations (pre mode). Use when the user provides an AIP URL or AIP content, optionally with PR URLs and file paths.

Guide for contributing to the Airflow Java SDK (AIP-108). Use this skill whenever a contributor is working in the `java-sdk/` directory or on the Java coordinator in `task-sdk/src/airflow/sdk/coordinators/java/` — whether they want to add a feature, write tests, fix a bug, understand the architecture, or prepare a PR. Trigger on phrases like "Java SDK", "JavaCoordinator", "java-sdk", "annotation processor", "Builder.Task", "BundleBuilder", or anything about running JVM tasks in Airflow.

Guide for implementing a brand-new language SDK for Airflow (AIP-108). Use this skill when a contributor wants to add support for a new programming language — designing the Python coordinator, implementing the wire protocol in the target language, writing the bundle format, and structuring the PR. Trigger on phrases like "new language SDK", "new SDK", "add support for [language]", "implement coordinator for", "SubprocessCoordinator", "BaseCoordinator", "new runtime", "AFBNDL01", "supervisor schema", or anything about bringing a new language into the Airflow executor ecosystem.

Add or update translations for the Apache Airflow UI. Guides through setting up locales, scaffolding translation files, translating with locale-specific guidelines, and validating results. Use when working with i18n tasks in airflow-core/src/airflow/ui/public/i18n/locales/.

Adopt and maintain the apache-magpie framework in a project repo via the snapshot-based adoption mechanism. The only framework skill committed in an adopter's repo; every other skill is a symlink the adopt sub-action wires up. Sub-actions: `/magpie-setup` - first-time adoption (default; main-checkout only) `/magpie-setup upgrade` - refresh the gitignored snapshot per the committed lock (main-checkout only) `/magpie-setup worktree-init` - symlink a worktree's snapshot to the main's `/magpie-setup verify` - health check + drift detection `/magpie-setup skill-sources` - fetch/pin/symlink skills from trusted external sources listed in the adopter trust list (main-checkout only) `/magpie-setup override <skill>` - open or scaffold an agentic override in `.apache-magpie-overrides/` `/magpie-setup unadopt` - reverse the adoption (snapshot, locks, symlinks, hook, doc sections); preserves `.apache-magpie-overrides/` by default (main-checkout only)

Replace the manual commit-by-commit classification step in `breeze release-management prepare-provider-documentation` with AI-driven classification. For each provider with pending changes, analyze every PR (batched into one sub-agent per provider, not one per PR), pay special attention to potentially breaking changes by inspecting the actual diff, scope multi-provider PRs to the current provider's slice, ask the release manager when uncertain, and apply version bumps + changelog entries. Use during the regular provider release cycle as an alternative to the interactive breeze prompts.

Upgrade the pinned Flask-AppBuilder (FAB) dependency in the Apache Airflow FAB provider (`providers/fab/`). Bumps the exact `flask-appbuilder==` pin and its mirror constant, regenerates `uv.lock`, drives the `test_fab_alignment.py` drift tripwire, reviews the vendored security-manager `override.py` against the new upstream FAB, and conditionally re-vendors static assets / DB migrations. Use when asked to "upgrade FAB", "bump flask-appbuilder", or move the FAB provider to a newer Flask-AppBuilder release.

Track Airflow Improvement Proposal (AIP) implementation progress by comparing Confluence specs against codebase evidence. Use when asked to assess, report on, or compare AIP status.

Conventions and review steps for writing analytics SQL against the warehouse. Use whenever the task involves querying tables, building a report, or aggregating metrics.

Download and inspect CI e2e test logs from GitHub Actions artifacts. Use when investigating e2e test failures in CI.

Build SkyWalking OAP server, run javadoc checks, and verify checkstyle. Use to validate changes before submitting a PR.

Generate bytecode classes from DSL scripts (MAL, OAL, LAL, Hierarchy). Runs the compiler and dumps .class files for inspection.

Verify, commit, and push changes on a PR branch. Runs pre-flight checks (compile, checkstyle, license headers) before every push. Also creates the PR if one doesn't exist yet.

Check and fix Apache 2.0 license headers and dependency licenses using skywalking-eyes. Use before submitting a PR.

Add a new monitoring target / layer to SkyWalking OAP. Orients you to the OAL / MAL / LAL / SpanListener / SegmentListener extension points, the UI template + submodule touchpoints, the docs set that must move together, and the cross-cutting traps that don't live in any one skill.

Rebuild the SkyWalking distribution and OAP Docker image after source changes. Use before running e2e tests so the image reflects your code changes. Avoids the "image looks updated but runtime has stale jars" trap.

Run SkyWalking E2E tests locally

Run unit tests, integration tests, or slow integration tests matching CI. Use to validate changes before submitting a PR.

Mine bug patterns from any git repository. Discovers bug-fix commits via git log heuristics, analyzes each in parallel with subagents, writes individual analysis files, and synthesizes a generalized PATTERNS.md with repo-specific details stripped. Invoke explicitly with /bug-archaeology.

Comprehensive guide for writing Apache Cassandra in-JVM distributed tests (dtests). Use when creating tests that simulate multi-node Cassandra clusters within a single JVM for faster integration testing. Covers cluster creation (single-node, multi-node, multi-datacenter), configuration (all cassandra.yaml parameters, features, network topology), instance lifecycle (startup/shutdown/restart), query execution, message filtering for failure scenarios, running code on instances, ClusterUtils utilities, and debugging classloader-related issues (serialization failures, same-class-different-classloader problems).

Deep file-focused code review for correctness bugs. Unlike shallow-review which runs 6 specialists in parallel across the entire patch, deep-review focuses on user-specified files with full pattern catalogs (500+ patterns), codebase investigation, and source-level context gathering. Use when: the user specifies particular files for focused review, a shallow review flagged areas that need deeper investigation, reviewing critical-path code changes, examining complex serialization/lifecycle/state-machine changes. The user instructs which files to focus on (typically a subset of files in the patch).

Use git heatmap analysis to identify high-churn files and lines as candidates for thorough review or bug hunting. Works for PR reviews, security audits, bug hunts, or any code analysis task.

Multi-pass deep code review for large patches (1000+ LOC) that maximizes real bug detection. Orchestrates targeted-review, shallow-review, and deep-review in parallel across all HIGH and MEDIUM risk files and commits: understands the feature holistically, splits by file and commit, runs deep review on every HIGH/MEDIUM file, targeted review across the same scope, and per-commit shallow review, followed by cross-cut consistency checks. Use when: reviewing a large patch (feature branch, multi-commit, or single large diff, 1000+ LOC), doing a thorough pre-merge review, or when shallower reviews miss bugs due to patch size. Triggers on: "review this branch", "review these commits", "review this feature", "mega review", "thorough review", "full review of X commits", or when the user specifies a commit range or feature for review.

Deep code analysis with ASCII visualizations showing structure, flow, and state transitions. Use when analyzing patches/diffs, explaining classes or subsystems, understanding code architecture, reviewing changes for inconsistencies, or when asked to visualize how code works. Provides before/after diagrams, data/control flow, concurrency analysis, assumptions, and failure modes. Triggers on explain this patch/code/class, how does X work, show me the flow, visualize this change, code review requests, or proactive analysis during PR reviews.

Used to analyze Apache ShardingSphere community issues. Emphasizes root-cause-first and evidence-first classification before conclusions, and produces copy-ready GitHub issue replies in the voice of an Apache ShardingSphere community maintainer.

Generate standard unit tests for one or more target classes in Apache ShardingSphere; by default, target 100% class/line/branch coverage and pass quality gates; perform explicit merge analysis, suitability filtering, and refactor optimization for parameterized tests.

Review Apache ShardingSphere or user-authorized downstream pull requests and PR discussions from public or authorized repository evidence. Use for code-correctness or mergeability decisions, CI-focused review, root-cause and regression analysis, complete consolidated findings, copy-ready committer feedback, challenged findings, multi-round review, and formal review of local implementation candidates in the repository completion loop.

Apply Apache ShardingSphere's written coding standards during implementation, fixes, refactoring, and code review, or perform a standalone read-only compliance audit of a user-specified scope. Uses CODE_OF_CONDUCT.md, applicable AGENTS.md rules, Checkstyle, Spotless, and other repository-defined standards. Does not judge architecture, runtime ownership, caches, lifecycle, or other semantic design rules.

Implement, fix, refactor, or remove repository code under required scope, non-regression, verification, and review gates. Use whenever a task may change a production, test, script, or other implementation artifact, including build logic, generated source, and behavior-affecting configuration. Also use it alongside a specialized code-changing Skill. Do not use for read-only analysis or review, diagnosis-only work, or prose-only changes.

Fix BE (C++) code formatting issues using clang-format

Run clang-tidy on newly added/modified BE C++ code

Review code with Doris-specific checklists

Run Doris docker-based regression tests from a clean package

Fix FE (Java) code style issues using Checkstyle

Register, extend, or audit instructions in the table-driven T.ptx dialect (python/tvm/backend/cuda/ptx/table.py), and move the table to a newer PTX ISA version (9.3, 9.4, ...). Use when adding a PTX instruction or qualifier, widening an operand domain, fixing a ptxas certification failure, or checking the table's comments against the PTX ISA document.