Results for “ma”

Mede o tamanho estrutural da feature ativa lendo requirements, duvidas, plan e tasks do ciclo forward, e gera size.json mais size.md com T-shirt sizing deterministico baseado em tasks e ajuste de risco. Use quando o usuario digitar "/reversa-pricing-size", "reversa-pricing-size", "dimensionar feature" ou "calcular tamanho da feature". Roda depois de `/reversa-to-do` e antes de `/reversa-pricing-estimate`.

Queries the FRED (Federal Reserve Economic Data) API for 800,000+ economic time series from 100+ sources, covering GDP, unemployment, inflation, interest rates, exchange rates, housing, and regional data. Use for macroeconomic analysis, financial research, policy studies, economic forecasting, fetching U.S. or international economic indicators by FRED series ID, and academic research requiring historical economic time series. Part of the AlterLab Academic Skills suite.

Drafts SEC Form 8-K current reports with item-accurate narratives, exhibit indexing, and EDGAR-ready formatting. Use when a public company must disclose a reportable event (material agreement, acquisition, personnel change, Reg FD disclosure) or file a current report within four business days. Trigger on "Form 8-K", "current report", "8-K filing", "EDGAR", "Item 1.01", "Item 2.01", "Item 5.02", "Reg FD".

Multi-perspective academic paper review with dynamic reviewer personas. Simulates 5 independent reviewers (EIC + 3 peer reviewers + Devil's Advocate) with field-specific expertise. Supports full review, re-review (verification), quick assessment, methodology focus, Socratic guided, and calibration modes. Triggers on: review paper, peer review, manuscript review, referee report, review my paper, critique paper, simulate review, editorial review, calibrate reviewer, reviewer calibration, measure reviewer accuracy.

Reconstruct a product flow, then audit how usable it is — whether it makes sense, where users get confused or stuck, whether the copy and instructions are clear, and where friction causes drop-off. Produces a prioritized, severity-weighted findings report. Works from three inputs: frontend code in a repo, a live running app driven via a browser, or a written flow / spec / screenshots. Use this skill whenever the user asks for a UX review, usability audit, "is this flow confusing", "does this signup/onboarding/checkout make sense", "why are people dropping off", "audit this form", "where's the friction", or hands over a flow and asks whether it's user-friendly. Trigger even on casual phrasings ("is my checkout any good?") — it imposes the structure ad-hoc UX opinions miss. Audits flow usability and friction; for visual polish and interface quality the impeccable audit/critique skills apply instead.

Create AI avatar, talking-head, and lip-sync videos on RunComfy via the `runcomfy` CLI. Routes across ByteDance OmniHuman (audio-driven full-body avatar), Wan-AI Wan 2-7 (audio-driven mouth sync via `audio_url` on a portrait), HappyHorse 1.0 (Arena #1 t2v / i2v with in-pass audio), and Seedance v2 Pro (multi-modal cinematic with reference audio + reference subject). Picks the right model for the user's actual intent — UGC voiceover, virtual presenter, dubbed product demo, lip-synced character, dialog scene — and ships each model's documented prompting patterns plus the minimal `runcomfy run` invoke. Triggers on "talking head", "lip sync", "avatar video", "make X speak", "audio to video", "audio driven avatar", "virtual presenter", "AI spokesperson", "dubbed video", "UGC avatar", "HeyGen alternative", "Synthesia alternative", "digital human", "make this portrait talk", "video from voiceover", or any explicit ask to put words in a face.

Create AI avatar, talking-head, and lip-sync videos on RunComfy via the `runcomfy` CLI. Routes across ByteDance OmniHuman (audio-driven full-body avatar), Wan-AI Wan 2-7 (audio-driven mouth sync via `audio_url` on a portrait), HappyHorse 1.0 (Arena #1 t2v / i2v with in-pass audio), and Seedance v2 Pro (multi-modal cinematic with reference audio + reference subject). Picks the right model for the user's actual intent — UGC voiceover, virtual presenter, dubbed product demo, lip-synced character, dialog scene — and ships each model's documented prompting patterns plus the minimal `runcomfy run` invoke. Triggers on "talking head", "lip sync", "avatar video", "make X speak", "audio to video", "audio driven avatar", "virtual presenter", "AI spokesperson", "dubbed video", "UGC avatar", "HeyGen alternative", "Synthesia alternative", "digital human", "make this portrait talk", "video from voiceover", or any explicit ask to put words in a face.

Create AI avatar, talking-head, and lip-sync videos on RunComfy via the `runcomfy` CLI. Routes across ByteDance OmniHuman (audio-driven full-body avatar), Wan-AI Wan 2-7 (audio-driven mouth sync via `audio_url` on a portrait), HappyHorse 1.0 (Arena #1 t2v / i2v with in-pass audio), and Seedance v2 Pro (multi-modal cinematic with reference audio + reference subject). Picks the right model for the user's actual intent — UGC voiceover, virtual presenter, dubbed product demo, lip-synced character, dialog scene — and ships each model's documented prompting patterns plus the minimal `runcomfy run` invoke. Triggers on "talking head", "lip sync", "avatar video", "make X speak", "audio to video", "audio driven avatar", "virtual presenter", "AI spokesperson", "dubbed video", "UGC avatar", "HeyGen alternative", "Synthesia alternative", "digital human", "make this portrait talk", "video from voiceover", or any explicit ask to put words in a face.

Turns a raw idea, brain dump, or conversation into a complete PRD with mandatory acceptance criteria and measurable success metrics. Extracts the problem, target users, and jobs-to-be-done, runs a quick competitive scan (web if available, logged as a gap if not), drafts the full PRD (problem, personas, user stories.

Enterprise AI adoption platform for Claude Code — measures team usage via OpenTelemetry, syncs skills/MCP servers/hooks from a central dashboard, and delivers context-aware skill suggestions at prompt time. Solves the Intention-Action Gap: organizations that deploy Zeude see 3x adoption improvement (6% → 18%). Requires Supabase (config) and ClickHouse (analytics). Triggers on: zeude, ai adoption, claude code adoption, enterprise claude, opentelemetry claude, skill sync, team claude management.

Expert knowledge for Azure Attestation development including troubleshooting, best practices, security, configuration, and deployment. Use when validating attestation tokens, authoring policies, managing SGX/TPM baselines, or securing private endpoints, and other Azure Attestation related development tasks. Not for Azure Confidential Computing (use azure-confidential-computing), Azure Virtual Enclaves (use azure-virtual-enclaves), Azure Key Vault (use azure-key-vault), Azure Dedicated HSM (use azure-dedicated-hsm).

Autonomously optimize any Claude Code skill by running it repeatedly, scoring outputs against binary evals, mutating the prompt, and keeping improvements. Based on Karpathy's autoresearch methodology. Use when: optimize this skill, improve this skill, run autoresearch on, make this skill better, self-improve skill, benchmark skill, eval my skill, run evals on. Outputs: an improved SKILL.md, a results log, and a changelog of every mutation tried.

Search a codebase or UI for places that don't animate but should, and reject everything that shouldn't. Read-only; it proposes motion with exact values, it does not implement it. Use when the user asks "what could be animated here?" or wants to "make this feel more alive". For fixing existing animations, use `improve-animations` or `review-animations` instead. Source: github.com/emilkowalski/skills.

Inspect GitHub PR checks with gh, pull failing GitHub Actions logs, summarize failure context, then create a fix plan and implement after user approval. Use when a user asks to debug or fix failing PR CI/CD checks on GitHub Actions and wants a plan + code changes; for external checks (e.g., Buildkite), only report the details URL and mark them out of scope.

Write unit and integration tests for Angular v20+ applications using Vitest or Jasmine with TestBed and modern testing patterns. Use for testing components with signals, OnPush change detection, services with inject(), and HTTP interactions. Triggers on test creation, testing signal-based components, mocking dependencies, or setting up test infrastructure. Don't use for E2E testing with Cypress or Playwright, or for testing non-Angular JavaScript/TypeScript code.

AI image generation Creative Director powered by Google Gemini Nano Banana models. Use this skill for ANY request involving image creation, editing, visual asset production, or creative direction. Triggers on: generate an image, create a photo, edit this picture, design a logo, make a banner, visual for my anything, and all /banana commands. Handles text-to-image, image editing, multi-turn creative sessions, batch workflows, and brand presets.

Redige contrarrazoes (resposta ao recurso da parte contraria) defendendo a decisao recorrida — preliminares de NAO CONHECIMENTO (intempestividade, desercao, falta de pressuposto), refutacao do merito recursal, devolucao de interlocutorias nao agravaveis (CPC 1.009 §1) e pedido de majoracao de honorarios recursais (85 §11). Prazo 15 dias uteis (1.003 §5). Use quando o operador disser contrarrazoes, responder ao recurso, fui intimado da apelacao/agravo, defender a sentenca, contraminuta.

Turn a music track (an audio file, a video to pull audio from, or a track generated from a mood brief) into a beat-synced video — lyric video, slideshow, or kinetic promo. The music drives all pacing; any user-supplied images/videos are cut onto the same beat grid, and a complete video needs zero assets. Narrated pieces → the input-matched workflow (see /hyperframes). Unclear → /hyperframes.

Use to verify that the chain from conversation to evaluation to decision is complete and reconstructible, so a QA score or a customer outcome can be explained months later. Trigger for "can we prove why this decision was made", "is our audit trail complete", "reconstruct how this score was produced", evidencing an AI-assisted decision, or an auditor asking how a conclusion was reached.

Use to assemble a fair, evidence-backed coaching pack for a support agent's one-to-one from QA evaluations and conversation history. Trigger for "prepare a coaching session for X", "what areas does X need to improve", "areas of markdown for this agent", "what coaching opportunities stand out", "build a coaching agenda from these tickets", or preparing a weekly or monthly agent review.

Use when someone asks what is true, false, misleading, unsupported, unknown, or genuinely complicated in a persuasive message, article, pitch, advertisement, policy claim, or viral post. Analyze propaganda, spin, selective framing, urgency, social proof, deceptive marketing, and AI-generated persuasion by tracing claims to evidence and separating literal truth from implied conclusions. Do not use to read deception from demeanor, adjudicate intent, or replace broad domain research.

Structures and derives research formulas when the user wants to 推导公式, build a theory line, organize assumptions, turn scattered equations into a coherent derivation, or rewrite theory notes into a paper-ready formula document. Use when the derivation target is not yet fully fixed, the main object still needs to be chosen, or the user needs a coherent derivation package rather than a finished theorem proof.

Applies Han's shared Human-Readable Output Standard to a target you already have — a file on disk, text pasted into the prompt, or a draft already produced in the conversation — by dispatching the readability-editor to rewrite its prose so the main point comes first, headings are descriptive, each paragraph carries one idea, and sentences stay short and active, while preserving every fact. Use when you want to make a document or draft readable, edit or polish prose for readability, clean up writing, tighten wording, or re-apply the readability standard to something already written. Rewrites prose only, leaving code, diagrams, and citation identifiers unchanged. Does not write new feature or system documentation — use project-documentation. Does not restructure code or review it — use refactor to restructure code and code-review to audit it. Does not judge the underlying work or raise findings; it only rewrites the writing.

Make the base agentic-skills available in a project by installing them project-local with npx skillpacks init, report and fix skill-install drift, clean up legacy user-home installs, and run guided setup for project-local domain packs. Use when Codex needs to enable base skills for a project, repair stale installs, confirm initialization status, remove old global installs, or set up and route domain packs.

Interpretabilidade e explicabilidade de modelos usando SHAP (SHapley Additive exPlanations). Use essa skill ao explicar predições de modelos de machine learning, computar importância de features, gerar plots SHAP (waterfall, beeswarm, bar, scatter, force, heatmap), depurar modelos, analisar vieses ou justiça de modelos, comparar modelos ou implementar IA explicável. Funciona com modelos baseados em árvores (XGBoost, LightGBM, Random Forest), deep learning (TensorFlow, PyTorch), modelos lineares e qualquer modelo black-box.

Biblioteca Python abrangente para astronomia e astrofísica. Esta skill deve ser usada ao trabalhar com dados astronômicos, incluindo coordenadas celestes, unidades físicas, arquivos FITS, cálculos cosmológicos, sistemas de tempo, tabelas, sistemas de coordenadas mundiais (WCS) e análise de dados astronômicos. Use quando as tarefas envolvem transformações de coordenadas, conversões de unidades, manipulação de arquivos FITS, cálculos de distâncias cosmológicas, conversões de escalas de tempo ou processamento de dados astronômicos.

Expert knowledge for Azure Reliability development including best practices, decision making, architecture & design patterns, and limits & quotas. Use when choosing Azure regions/zones, AKS/DB/queue designs, Web PubSub scaling, or DR/failover architectures, and other Azure Reliability related development tasks. Not for Azure Resiliency (use azure-resiliency), Azure Monitor (use azure-monitor), Azure Service Health (use azure-service-health), Azure Sre Agent (use azure-sre-agent).

| Use when reviewing an incoming GitHub pull request — runs the multi-level (L1-L5) audit against the PR's real diff range, posts findings as one batched review (inline, summary, or local-only), offers the standard fix chain on NEEDS_FIX, and optionally merges. The maintainer-side counterpart to /hyperflow:issue. Trigger with /hyperflow:pr, "review PR #N", "review this pull request <url>", "audit the PR", "check this contribution".

Expert-level Windows batch file (.bat/.cmd) skill for writing, debugging, and maintaining CMD scripts. Use when asked to "create a batch file", "write a .bat script", "automate a Windows task", "CMD scripting", "batch automation", "scheduled task script", "Windows shell script", or when working with .bat/.cmd files in the workspace. Covers cmd.exe syntax, environment variables, control flow, string processing, error handling, and integration with system tools.

Captures learnings, errors, and corrections to enable continuous improvement. Use when: (1) A command or operation fails unexpectedly, (2) User corrects Claude ('No, that's wrong...', 'Actually...'), (3) User requests a capability that doesn't exist, (4) An external API or tool fails, (5) Claude realizes its knowledge is outdated or incorrect, (6) A better approach is discovered for a recurring task. Also review learnings before major tasks.

Ship workflow: detect + merge base branch, run tests, review diff, bump VERSION, update CHANGELOG, commit, push, create PR. Use when asked to "ship", "deploy", "push to main", "create a PR", "merge and push", or "get it deployed". Proactively invoke this skill (do NOT push/PR directly) when the user says code is ready, asks about deploying, wants to push code up, or asks to create a PR. (gstack)

Determines whether to perform adrenal venous sampling (AVS) to lateralize aldosterone excess in patients with confirmed primary aldosteronism (PA) who are being evaluated for surgical treatment. Indicated when surgery is feasible and desired by the patient, or when subtype workup is planned for a surgical candidate, especially in those younger than 35 years with spontaneous hypokalemia, marked aldosterone excess, and unilateral adrenal lesions on CT.

Create or maintain STRATEGY.md - the product's target problem, approach, users, key metrics, and tracks of work. Use when starting a new product, updating direction, or when prompts like 'write our strategy', 'update the roadmap', 'what are we working on', or 'set up the strategy doc' come up. Also triggers when ce-ideate, ce-brainstorm, or ce-plan need upstream grounding and no strategy doc exists yet.

Jest is a comprehensive JavaScript testing framework built by Meta, designed for zero-configuration testing of JavaScript and TypeScript applications. It provides a complete ecosystem for unit testing, integration testing, and snapshot testing with built-in code coverage, mocking capabilities, and parallel test execution. Jest works seamlessly with React, Node.js, Angular, Vue, and virtually any JavaScript project, making it the most widely adopted testing framework in the ecosystem.

Audit agent skills, plugins, prompts, manifests, scripts, dependencies, and bundled assets for provenance, prompt-injection, permission, execution, exfiltration, persistence, and update risk. Use when evaluating a third-party skill before installing, enabling, updating, publishing, or distributing it; reviewing an untrusted SKILL.md, agent configuration, MCP integration, archive, or repository; comparing a package with a known-good version; or investigating unexpected tool, network, credential, or filesystem behavior.

Unity XR — XR Interaction Toolkit 3.x (Interactor/Interactable/Manipulation), AR Foundation (planes, anchors, image tracking, body tracking), OpenXR, hand tracking on Quest/Vision OS. USE WHEN: VR/AR/MR projects, integrating XR controllers, AR plane detection, XR locomotion, hand tracking, eye tracking, OpenXR features. DO NOT USE FOR: regular 3D gameplay (use `unity-physics-anim`); rendering pipeline (use `unity-rendering` — XR has URP-specific considerations).