Results for “ma”

Deploy AWS Config rules for continuous compliance monitoring, including managed and custom rules aligned to CIS and PCI DSS frameworks, automatic remediation with SSM Automation, and multi-account compliance aggregation.

Eliminate standing privileges by granting temporary, time-bound access only when needed, covering JIT architecture design, approval workflows, automatic expiration, and integration with PAM and IGA platforms.

Choose and audit startup metrics using the Lean Analytics framework: separate actionable metrics from vanity metrics, identify the One Metric That Matters for your business model and stage, set targets, and plan instrumentation.

Structure the first 90 days of a VP or CPO transition as a diagnostic process, not an execution sprint, using a three-phase playbook to build evidence before making decisions.

Provides a repeatable, auditable workflow for large coding tasks by initializing repo-local task artifacts, installing subagent templates, and running a spec-freeze → build → evidence → verify → fix loop with fresh-session verification.

Find authoritative guidance for installing, configuring, operating, securing, and troubleshooting OpenClaw, including channels, model providers, Gateway operations, tools, plugins, automation, nodes, multi-agent routing, and CLI errors. Use for any question or maintenance task involving an OpenClaw installation.

Operates Redpanda's Agentic Data Plane: manages AI agents, MCP servers, LLM providers, budgets, guardrails, and Cedar access policies via the `rpk ai` CLI and API, including OAuth wiring and spend/transcript insights.

Manage schemas, subjects, compatibility levels, modes, and contexts in the Redpanda Schema Registry via the rpk registry CLI. Register or fetch Avro, Protobuf, and JSON schemas, set compatibility levels, change registry mode, and work with schema contexts.

Classifies a repository into one of six archetypes and installs a curated bundle of agent skills covering build, test, review, deploy, and docs, with a user-visible manifest and a recorded stack file.

Guides the agent to research existing tools, libraries, and patterns before writing custom code, using parallel searches across package registries, MCP servers, skills, and GitHub, then evaluating and deciding to adopt, extend, or build.

Use when planning an ACM CHI submission cycle end to end — the single September deadline, two-round review with a five-week revise-and-resubmit window, December decisions, the TAPS and publication-ready chain, and the May conference — with owners and risk buffers for each stage.

Use to plan an ACM/IEEE HRI campaign backward from the full-paper deadline through the abstract-then-paper two-step, the rebuttal, the program-committee meeting, camera-ready, and the March conference, coordinating the parallel alt.HRI, Late-Breaking Reports, video, and Student Design deadlines.

Use when planning a UIST cycle end to end — the late-March abstract and paper deadlines, the ten-week build-freeze before video production, the rebuttal window, conditional acceptance, the July camera-ready, adjunct-track parallel lanes, and the November conference — with owners and risk buffers.

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 LLM handling, and provenance for mining.

Quantum physics simulation library for open quantum systems. Use when studying master equations, Lindblad dynamics, decoherence, quantum optics, or cavity QED. Best for physics research, open system dynamics, and educational simulations. NOT for circuit-based quantum computing—use qiskit, cirq, or pennylane for quantum algorithms and hardware execution.

Use when the user wants to generate marketing copy, ad headlines, taglines, product descriptions, or brand messaging using Gemini CLI. Trigger phrases: write copy with Gemini CLI, generate ad copy via terminal, Gemini CLI copywriting, bulk product descriptions. For email copy see gemini-cli-cold-email.

Provides foundational setup, authentication, and project management workflows for Firebase using the Firebase CLI. Use when checking Firebase CLI version (must use 'npx -y firebase-tools@latest --version'), initializing a Firebase environment, authenticating, setting active projects, or setting up `google-services.json` or `GoogleService-Info.plist` files.

Guides the audit of Records of Processing Activities (RoPA) against GDPR Article 30 requirements for both controllers and processors. Activate when verifying RoPA completeness, validating mandatory fields, or preparing for supervisory authority inspections. Keywords: RoPA, Article 30, records audit, processing activities, controller records, processor records.

Toolkit for styling artifacts with a theme. These artifacts can be slides, docs, reportings, HTML landing pages, etc. There are 10 pre-set themes with colors/fonts that you can apply to any artifact that has been creating, or can generate a new theme on-the-fly.

Analyze recent code changes via git history and extract software engineering lessons. Use when the user asks 'what is the lesson here?', 'what can I learn from this?', 'engineering takeaway', 'what did I just learn?', 'reflect on this code', or wants to extract principles from recent work.

Report AI token usage and estimated costs. Use when: owner asks about costs today/yesterday/this week, per session, or per model. Shows main session, cron jobs, and subagents. Answers: 'how much did today cost?', 'how much was this session?', 'what was last week's spend?'

Finalizes a hotfix and merges it into main and develop using git-flow, then prunes stale branches and worktrees. This skill should be used when the user asks to "finish a hotfix", "merge hotfix branch", "complete hotfix", "git flow hotfix finish", or wants to finalize a hotfix.

Create Jira issues such as tasks, stories, bugs, or subtasks from user intent. Use when a user asks to open, file, draft, or create a Jira ticket and needs fields validated, issue text composed, Jira API or connector calls made, and the created issue link returned.

WordPress AOS animation installer — audits, installs, enqueues, initializes, and seeds Animate On Scroll on every visual element across all PHP templates. Use when the user asks to add scroll animations, AOS, fade-in effects, entrance animations, or "make elements appear on scroll" in any WordPress theme.

Expert database administrator specializing in modern cloud databases, automation, and reliability engineering. Masters AWS/Azure/GCP database services, Infrastructure as Code, high availability, disaster recovery, performance optimization, and compliance. Handles multi-cloud strategies, container databases, and cost optimization. Use PROACTIVELY for database architecture, operations, or reliability engineering.

Expert network engineer specializing in modern cloud networking, security architectures, and performance optimization. Masters multi-cloud connectivity, service mesh, zero-trust networking, SSL/TLS, global load balancing, and advanced troubleshooting. Handles CDN optimization, network automation, and compliance. Use PROACTIVELY for network design, connectivity issues, or performance optimization.

Expert database optimizer specializing in modern performance tuning, query optimization, and scalable architectures. Masters advanced indexing, N+1 resolution, multi-tier caching, partitioning strategies, and cloud database optimization. Handles complex query analysis, migration strategies, and performance monitoring. Use PROACTIVELY for database optimization, performance issues, or scalability challenges.

Manage project learnings. Review, search, prune, and export what gstack has learned across sessions. Use when asked to "what have we learned", "show learnings", "prune stale learnings", or "export learnings". Proactively suggest when the user asks about past patterns or wonders "didn't we fix this before?"

Add or upgrade PWA features to any web app: service worker, offline mode, install prompt, push notifications, and background sync. Use when asked to "make it a PWA", "offline support", "install prompt", "push notifications", "service worker", "add to home screen", "background sync", "Lighthouse PWA score", "app-like.

Drive an entire repository to a fully green baseline — typecheck, lint, tests, and build all passing from a clean checkout — when the user has explicitly authorized fixing. Use when "make the repo green", "get CI passing", "fix all the failing tests". Ratchet integrity → audit-gate-logic.

Read-only audit of a codemod or bulk mechanical transform for behavior-preservation — compiles/lints is not same-behavior. Use when "did this codemod break anything", "audit this bulk refactor", or before merging a mass find-replace. Diff quality → audit-code-review. SQL → plan-data-integrity.

Framework for building LLM-powered applications with agents, chains, and RAG. Supports multiple providers (OpenAI, Anthropic, Google), 500+ integrations, ReAct agents, tool calling, memory management, and vector store retrieval. Use for building chatbots, question-answering systems, autonomous agents, or RAG applications. Best for rapid prototyping and production deployments.

Runs LLM inference on CPU, Apple Silicon, and consumer GPUs without NVIDIA hardware. Use for edge deployment, M1/M2/M3 Macs, AMD/Intel GPUs, or when CUDA is unavailable. Supports GGUF quantization (1.5-8 bit) for reduced memory and 4-10× speedup vs PyTorch on CPU.

Reduce LLM size and accelerate inference using pruning techniques like Wanda and SparseGPT. Use when compressing models without retraining, achieving 50% sparsity with minimal accuracy loss, or enabling faster inference on hardware accelerators. Covers unstructured pruning, structured pruning, N:M sparsity, magnitude pruning, and one-shot methods.

Framework for building LLM-powered applications with agents, chains, and RAG. Supports multiple providers (OpenAI, Anthropic, Google), 500+ integrations, ReAct agents, tool calling, memory management, and vector store retrieval. Use for building chatbots, question-answering systems, autonomous agents, or RAG applications. Best for rapid prototyping and production deployments.

Runs LLM inference on CPU, Apple Silicon, and consumer GPUs without NVIDIA hardware. Use for edge deployment, M1/M2/M3 Macs, AMD/Intel GPUs, or when CUDA is unavailable. Supports GGUF quantization (1.5-8 bit) for reduced memory and 4-10× speedup vs PyTorch on CPU.