Results for “ci”

Automates PR review and CI auto-fix for GitHub and GitLab using the Composio CLI. Pulls diffs, fetches failing job logs, posts review comments, and loops fix commits until checks go green.

Configures pre-created scratch org pools for parallel CI testing, reducing pipeline wait times by claiming pre-warmed orgs instead of provisioning on demand. Covers CumulusCI pool commands, Dev Hub limits, and CI integration.

Optimize content for AI search and LLM citations across AI Overviews, ChatGPT, Perplexity, Claude, Gemini, and similar systems. Use when improving AI visibility, answer engine optimization, or citation readiness.

Design and plan end-to-end Azure IoT and Smart City solutions: requirements, architecture, security, operations, cost, and a phased delivery plan with concrete implementation artifacts.

Builds a structured ransomware incident response playbook aligned with the CISA StopRansomware Guide and NIST Cybersecurity Framework, covering preparation, detection, containment, eradication, recovery, and post-incident phases with actionable checklists.

Use to convert references to PNAS's numbered citation style — cited in order of appearance, a numbered reference list, full author lists, abbreviated journal titles. Provides formats for article/book/chapter/dataset/preprint and an author-date → PNAS conversion table. Late-stage style pass.

Apply-now consolidation of accreted CI gates, ratchets, and hooks into one aggregator required check. Use after audit-gate-logic, or when "clean up our CI checks", "we have three lint jobs", "make one quality gate". Audit-only → audit-gate-logic. Pipeline cost → audit-cicd.

Configure and optimize Turborepo monorepo build systems with task pipelines, caching, filtering, and CI integration.

Fans out web searches, fetches sources, adversarially verifies claims, and synthesizes a cited research report.

Automates GitHub Actions, Issues, and PR management for CI/CD, project tracking, and code review workflows.

Configures GitHub Actions CI/CD pipelines for Flutter and backend monorepos, including testing, building, and deployment workflows.

Builds, simulates, and runs quantum circuits with Cirq, Google Quantum AI's framework for NISQ hardware, noise-aware low-level circuit design, and noise characterization. Use when targeting Google Quantum AI processors (Sycamore/Weber), designing noise-aware NISQ circuits, or running characterization experiments (randomized benchmarking, XEB). For IBM Quantum hardware and Qiskit Runtime prefer alterlab-qiskit; for gradient-trained quantum ML and hybrid quantum-classical models prefer alterlab-pennylane; for open-system Lindblad/master-equation dynamics prefer alterlab-qutip. Part of the AlterLab Academic Skills suite.

Generates a sequence of fullscreen video frames with cinematic visuals, auto-play, and metadata for Remotion/Hyperframes rendering.

Search and retrieve academic papers from arXiv via their REST API, including citation data from Semantic Scholar.

Automates multi-language software builds with Makefiles, dependency management, testing, packaging, and CI/CD integration.

Trigger: circuit breaker, exponential backoff, jitter delay, connection timeout, API retry. Scope: Client request resiliency, API retries, fault isolation. Boundary: Excludes visual state loading skeletons.

GitHub 仓库操作、自动化与管理。使用 gh CLI 进行问题分类、PR 管理、CI/CD 操作、发布管理和安全监控。当用户想要管理 GitHub 问题、PR、CI 状态、发布、贡献者、过期项目或任何超出简单 git 命令的 GitHub 操作任务时使用。

Builds, transpiles, and runs quantum circuits with Qiskit, IBM's quantum computing framework, including Qiskit Runtime primitives (Sampler/Estimator), circuit transpilation, and error mitigation on IBM Quantum hardware. Use when targeting IBM Quantum backends, transpiling circuits, running Runtime sessions or batches, or applying resilience/error mitigation. For Google Quantum AI hardware and NISQ circuits prefer alterlab-cirq; for gradient-trained quantum ML and hybrid quantum-classical models prefer alterlab-pennylane; for open-system Lindblad/master-equation dynamics prefer alterlab-qutip. Part of the AlterLab Academic Skills suite.

Answer Engine Optimization (AEO) skill — optimize content to be cited by AI language models (ChatGPT, Perplexity, Claude, Gemini, Mistral) as authoritative sources. Distinct from SEO — AEO optimizes for citation in LLM-generated responses, not search rankings. Use when planning content for AI-first search audiences, auditing existing content for E-E-A-T signals, tracking which pages get cited by which LLMs, or building a citation-friendly content strategy. Triggers — 'AEO audit', 'optimize for ChatGPT', 'get cited by Perplexity', 'LLM citation strategy', 'answer engine optimization', 'content for AI search', 'E-E-A-T audit'. Output is a markdown audit report (default) or JSON for pipeline integration. Stdlib-only Python tools.

Answer Engine Optimization (AEO) skill — optimize content to be cited by AI language models (ChatGPT, Perplexity, Claude, Gemini, Mistral) as authoritative sources. Distinct from SEO — AEO optimizes for citation in LLM-generated responses, not search rankings. Use when planning content for AI-first search audiences, auditing existing content for E-E-A-T signals, tracking which pages get cited by which LLMs, or building a citation-friendly content strategy. Triggers — 'AEO audit', 'optimize for ChatGPT', 'get cited by Perplexity', 'LLM citation strategy', 'answer engine optimization', 'content for AI search', 'E-E-A-T audit'. Output is a markdown audit report (default) or JSON for pipeline integration. Stdlib-only Python tools.

Google quantum computing framework. Use when targeting Google Quantum AI hardware, designing noise-aware circuits, or running quantum characterization experiments. Best for Google hardware, noise modeling, and low-level circuit design. For IBM hardware use qiskit; for quantum ML with autodiff use pennylane; for physics simulations use qutip.

Google quantum computing framework. Use when targeting Google Quantum AI hardware, designing noise-aware circuits, or running quantum characterization experiments. Best for Google hardware, noise modeling, and low-level circuit design. For IBM hardware use qiskit; for quantum ML with autodiff use pennylane; for physics simulations use qutip.

Gate anti-alucinacao do plugin civel: valida vigencia e existencia de dispositivo, sumula, tese, tema e enunciado ANTES de qualquer citacao entrar em peca. Cruza com context/ (CPC/CC + reformas + jurisprudencia) e, na duvida, exige checagem ao vivo (fetch real) ou bloqueia. Integra o guard global anti-alucinacao-juridica. Use antes de citar qualquer fundamento, ou quando o operador disser valida essa jurisprudencia, esse artigo existe, essa sumula esta vigente, esse tema/acordao existe, confere essa ementa, antes de citar, esse dispositivo ainda esta em vigor, checa esse fundamento.

Generates rich technical documentation pages with dark-mode Mermaid diagrams, source code citations, and first-principles depth.

Search Notion pages, synthesize findings, and publish structured briefs, summaries, comparisons, or reports with citations and source links.

Audit GitHub Actions workflow efficiency and recommend fixes to reduce CI minutes and costs.

Automates git bisect workflows with custom test scripts and CI pipeline integration to identify regression-introducing commits.

Writes a complete evergreen pillar article in the author's voice, including source research, SEO/GEO architecture, and citations.

Guides reliable application deployment with CI/CD pipelines, zero-downtime strategies, rollback plans, and post-deploy monitoring.

Build, optimize, and execute quantum circuits with Qiskit on local simulators or cloud hardware, and analyze results.

Optimize content for AI Overviews, ChatGPT, Perplexity, and other AI search systems. Use when improving GEO, AI citations, llms.txt readiness, crawler accessibility, and passage-level citability.

Optimize content for AI Overviews, ChatGPT, Perplexity, and other AI search systems. Use when improving GEO, AI citations, llms.txt readiness, crawler accessibility, and passage-level citability.

Optimize content for AI Overviews, ChatGPT, Perplexity, and other AI search systems. Use when improving GEO, AI citations, llms.txt readiness, crawler accessibility, and passage-level citability.

Optimize content for AI Overviews, ChatGPT, Perplexity, and other AI search systems. Use when improving GEO, AI citations, llms.txt readiness, crawler accessibility, and passage-level citability.

Optimize content for AI Overviews, ChatGPT, Perplexity, and other AI search systems. Use when improving GEO, AI citations, llms.txt readiness, crawler accessibility, and passage-level citability.

Optimize content for AI Overviews, ChatGPT, Perplexity, and other AI search systems. Use when improving GEO, AI citations, llms.txt readiness, crawler accessibility, and passage-level citability.