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Use when strengthening the reproducibility of an ACM MM (ACM Multimedia) paper or preparing for the ACM MM Reproducibility track and ACM artifact badging — capturing environments, media/data access, seeds, and multimodal pipelines so an independent reviewer can rebuild results and reach Artifacts Ev…

Use when reasoning about the ACM MM (ACM Multimedia) review pipeline — thematic-area routing to reviewers and area chairs, the OpenReview double-blind process and its single-blind track exceptions, the optional anonymous rebuttal, the meta-review and decision, and the oral/poster and award tiers, an…

Use when planning the end-to-end ACM MM (ACM Multimedia) campaign calendar — from thematic-area scoping and track choice, through the April OpenReview abstract/paper/supplement chain, the June anonymous rebuttal, the July decision, the August camera-ready, and the November presentation in Rio, with…

Use when drafting ASE (IEEE/ACM Automated Software Engineering) author responses, covering the double-anonymous rebuttal that must first survive the early-rejection gate and — distinctively — the criteria-bound revision-round summary-of-changes that maps every stated revision criterion to a concrete…

Use when preparing the ASE (IEEE/ACM Automated Software Engineering) camera-ready after acceptance or a successful revision, covering systematic de-anonymization, the extra content page, the mandatory Data Availability finalization, the correct IEEE/ACM template and metadata, permanentized artifact…

Use when designing or auditing the evaluation of an ASE (IEEE/ACM Automated Software Engineering) paper, covering real subject systems, fair runnable tool baselines, task-matched effectiveness metrics, ablations that isolate a learned component, oracle and correctness validation, contamination-aware…

Use when writing the related-work and positioning of an ASE (IEEE/ACM Automated Software Engineering) paper, covering the automated-SE literature lanes, delta-first positioning against prior tools/techniques, fair head-to-head framing, and double-anonymous self-citation.

Use when planning an ASE (IEEE/ACM Automated Software Engineering) research-track campaign backward from the deadline, through abstract registration, the double-anonymous submission, the early-rejection gate, rebuttal, the criteria-bound revision round, artifact evaluation, and the camera-ready in b…

Use when planning an ATC (ACM SIGOPS Annual Technical Conference, formerly USENIX ATC) campaign end to end — running the year backward from the early-June deadline through the two review rounds, the rebuttal, conditional-acceptance shepherding, the post-acceptance artifact evaluation, and the ACM Op…

This skill should be used when user asks to "create a PR", "make a pull request", "open PR for this branch", "submit changes as PR", "push and create PR", or explicitly invokes "create-pr".

Use when building a managed team skills library for a real stack. Map work to shelves, browse before curating, write meaningful `whyHere` notes, and create a starter pack once the first pass is solid.

Use when moving skills between library workspaces or upgrading from a personal library to a team library. Export from one workspace, import into another.

Build and ship Unity 6.3 LTS players: build settings and scenes, player/quality settings, the IL2CPP vs Mono scripting backend, managed code stripping, scripted BuildPipeline.BuildPlayer, and CI/headless builds

Code review and validation for CloudBase projects. After writing code for Web / miniprogram / CloudRun / cloud-function projects, call this skill to check for known pitfalls — auth guard misuse, missing database tables, RLS misconfiguration, storage domain setup, and SDK API misuse.

Use when medium-to-large changes need explicit requirements, technical design, and task planning before implementation, especially for multi-module work, unclear acceptance criteria, or architecture-heavy requests.

Trigger when: (1) User mentions "manimgl" or "ManimGL" or "3b1b manim", (2) Code contains `from manimlib import *`, (3) User runs `manimgl` CLI commands, (4) Working with InteractiveScene, self.frame, self.embed(), ShowCreation(), or ManimGL-specific patterns.

Orchestrate AI/ML pipelines for data ingestion, model training, batch inference, and RAG indexing using Prefect, Airflow, or Dagster. Build reliable, observable, and retriable workflows for production AI systems.

Set up Azure Pipelines for CI/CD, configure build and release pipelines, manage Azure DevOps projects, and integrate with Azure services

Configure CircleCI workflows and orbs for continuous integration and deployment. Create config.yml pipelines, use orbs for reusable configurations, and optimize build performance

Build, test, and deploy applications using GitHub Actions workflows. Create CI/CD pipelines, configure runners, manage secrets, and automate software delivery

Deploy and manage the ELK Stack (Elasticsearch, Logstash, Kibana) for log aggregation and analysis. Configure log pipelines, create visualizations, and implement log-based monitoring

Implement GitOps with ArgoCD for declarative Kubernetes deployments. Configure applications, manage sync policies, implement progressive delivery, and automate deployments from Git repositories

Implement Git branching strategies, PR workflows, and release management patterns. Configure GitFlow, trunk-based development, or GitHub Flow for team collaboration

Automate versioning and changelog generation using semantic versioning principles. Configure release automation, version bumping, and changelog tools