Results for “pr”

Interactive visualization library. Use when you need hover info, zoom, pan, or web-embeddable charts. Best for dashboards, exploratory analysis, and presentations. For static publication figures use matplotlib or scientific-visualization.

Recover context from local AI conversation history with RecallBase. Use for same-day work summaries, resuming prior AI or coding sessions, or tracing a past decision to its source.

Create exercise directory structures with sections, problems, solutions, and explainers that pass linting. Use when user wants to scaffold exercises, create exercise stubs, or set up a new course section.

Generate AI videos on RunComfy via the `runcomfy` CLI — a smart router across the full video-model catalog: HappyHorse 1.0 (Arena #1, native in-pass audio), Wan-AI Wan 2-7 (open weights, audio-driven lip-sync), ByteDance Seedance v2 / 1-5 / 1-0 (multi-modal cinematic), Kling 3.0 / 2-6, Google Veo 3-1, MiniMax Hailuo 2-3, ByteDance Dreamina 3-0. Covers text-to-video (t2v), image-to-video (i2v), and Veo's video-extend endpoint. The skill picks the right model for the user's intent (Arena-#1 quality, multi-shot character identity, in-pass audio, cinematic motion, fastest path, sub-15s clip, longest duration) and ships each model's documented prompting patterns plus the minimal `runcomfy run` invoke. Triggers on "generate video", "make a video", "text to video", "t2v", "image to video", "i2v", "animate", "AI video", "make X move", "video from prompt", "video from image", or any explicit ask to produce a video clip from prompt or still.

Generate AI videos on RunComfy via the `runcomfy` CLI — a smart router across the full video-model catalog: HappyHorse 1.0 (Arena #1, native in-pass audio), Wan-AI Wan 2-7 (open weights, audio-driven lip-sync), ByteDance Seedance v2 / 1-5 / 1-0 (multi-modal cinematic), Kling 3.0 / 2-6, Google Veo 3-1, MiniMax Hailuo 2-3, ByteDance Dreamina 3-0. Covers text-to-video (t2v), image-to-video (i2v), and Veo's video-extend endpoint. The skill picks the right model for the user's intent (Arena-#1 quality, multi-shot character identity, in-pass audio, cinematic motion, fastest path, sub-15s clip, longest duration) and ships each model's documented prompting patterns plus the minimal `runcomfy run` invoke. Triggers on "generate video", "make a video", "text to video", "t2v", "image to video", "i2v", "animate", "AI video", "make X move", "video from prompt", "video from image", or any explicit ask to produce a video clip from prompt or still.

Audit a landing page and return prioritized conversion fixes across the hero, the proof, the friction, and the CTA, each with the reason and the expected lift direction. Ranks every fix by effort against impact so you ship the cheap wins first. Trigger on "audit my landing page", "why isn't this page converting", "CRO review", "improve my landing page", "review my hero section", or "how do I get more signups from this page".

For a repository in the babysitter-users catalog, locate its babysitter processes and any committed runs (.a5c/runs/<runId>/) and perform a retrospective on a chosen run -- what went well, what failed, process suggestions, quality of effect design, breakpoint patterns -- mirroring the /babysitter:retrospect workflow but applied to an external repo. Invoke when asked to "retrospect on repo X's run", "analyze how someone else used babysitter", or "review an external babysitter run".

Orchestrate the full MoonSpec lifecycle from a preselected single-story feature request or active feature directory through specification, planning, TDD task generation, artifact alignment, implementation, and final verification. Use when the user asks for an end-to-end MoonSpec run and the input has already been routed to one independently testable story, or when Codex needs to coordinate `moonspec-specify`, `moonspec-plan`, `moonspec-tasks`, `moonspec-align`, `moonspec-implement`, and `moonspec-verify` without manual analyze/remediation prompts.

Teleological physiology analysis framework for understanding biological systems through multi-constraint optimization. Use when analyzing physiological mechanisms, explaining apparent biological "inefficiencies", preparing for medical examinations (CICM/ANZCA Primary), understanding why biological systems are designed the way they are, or when seeking deeper mechanistic understanding beyond descriptive knowledge. Triggers on questions like "why is X designed this way", "what purpose does Y serve", "how is Z optimized", analysis of physiological trade-offs, or exploration of evolutionary/design constraints.

Off-page playbook (Lesson 10, outreach). Turns a vetted link-prospect list into them-focused outreach drafts that earn links without spamming. Picks the RIGHT people (those who LINKED to or MENTIONED our topic — never "people who tweeted it"), gives each a real "excuse" (fresh-angle / new-proof / ego-bait), keeps to ≤1 follow-up, and never makes a pushy link ask. Drafts only — every outward send is operator-gated. Outreach is a tool, not a strategy.

Verify an artifact that is about to leave the building — a partnership brief, pitch page, press release, customer email, RFP response, or any document sent to someone outside the org. Runs six checks before send — premise, confidentiality forward-test, evidence class, cold read by recipient personas, AI read, and tone metrics — and returns what to change with replacement copy. Use before sending anything outward-facing that carries customer detail, factual claims about a counterparty, or an ask.

Intelligent inbox triage that connects to Gmail or Outlook, scores emails by importance (0-100) using sender recognition, urgency keywords, thread depth, time sensitivity, and business relevance, categorizes into Urgent/Important/Routine/Archive, and generates reply suggestions for top priority items. Use when the user wants to check email, review inbox, triage messages, see what's urgent, or get reply suggestions. Triggers on check email, inbox triage, what's important, email summary, unread emails, priority inbox.

SLF4J - Simple Logging Facade for Java. Standard logging API that abstracts underlying implementation (Logback, Log4j2). Provides parameterized logging and MDC support. USE WHEN: user mentions "slf4j", "java logging api", "parameterized logging", asks about "how to log in Java", "logger facade", "MDC in java", "logging best practices java" DO NOT USE FOR: Logback configuration - use `logback` instead, Log4j2 configuration - use Log4j2 skill, Node.js logging - use `winston` or `pino` instead, Python logging - use `python-logging` instead

Design data systems by understanding storage engines, replication, partitioning, transactions, and consistency models. Use when the user mentions "database choice", "replication lag", "partitioning strategy", "consistency vs availability", "stream processing", "ACID transactions", "eventual consistency", or "LSM tree vs B-tree". Also trigger when choosing between SQL and NoSQL, designing data pipelines, or debugging distributed system consistency issues. Covers data models, batch/stream processing, and distributed consensus. For system design, see system-design. For resilience, see release-it.

Operate Firebase from the terminal with `firebase-tools`: install/auth the CLI, bootstrap `firebase.json` / `.firebaserc`, run the Emulator Suite, deploy Hosting / Functions / rules / App Hosting, manage preview channels, and handle Firebase admin tasks like auth import/export, Remote Config, App Distribution, and Extensions. Use when the job is Firebase platform/project operation through the CLI. Triggers on: firebase deploy, firebase init, firebase emulators, firebase hosting, firebase functions, firebase firestore, firebase database, firebase auth import, firebase remote config, firebase app distribution, firebase extensions, firebase apphosting, firebase dataconnect, firebase cli, firebase-tools, deploy firebase, firebase preview channel, firebase login, firebase use, firebase target apply. Route backend AI workflow orchestration to `genkit` and direct in-app SDK integration to `genkit` (`client-ai-logic` mode).

Pay HTTP 402 payment challenges issued by OKX's Agent Payments Protocol (APP) on X Layer using tokens from any chain via the Uniswap Trading API. Use this skill whenever the user encounters a 402 challenge whose network resolves to X Layer (chain 196), mentions "APP", "Agent Payments Protocol", "OKX agent payment", "OKX Onchain OS", "OKX agentic wallet", "x402 on X Layer", "USDT0", "x42", "Instant Payment", "Batch Payment", "pay for X Layer API", or wants to pay an OKX-backed merchant. Even when the user does not explicitly say APP, prefer this skill for any 402 challenge whose network resolves to X Layer (chain 196). For 402 challenges on other chains (Ethereum, Base, Arbitrum, Tempo) use pay-with-any-token instead.

Use DuckDB from MATLAB via Database Toolbox (R2026a+) as a non-math operations engine on large tabular files (CSV/Parquet/JSON) and as a zero-config embedded database. Use when connecting to DuckDB, querying CSV, Parquet, and JSON files directly with SQL, reducing or profiling large data before MATLAB analysis, creating portable development databases, or installing DuckDB extensions. Triggers on: DuckDB, duckdb(), large CSV/Parquet/JSON, file too large for readtable, filter/aggregate at source, deduplicate, reduce before analysis, profile large file, persistent file import, analytical engine, SQL on CSV, SQL on Parquet, SQL on JSON, query CSV with SQL, query Parquet with SQL, run SQL on files, SQL queries on files, query files directly, SQL without database, in-process SQL.

Generate AI music on RunComfy via the `runcomfy` CLI — a smart router across the music-model catalog. Routes to ElevenLabs AI Music Generation (premium 44.1 kHz stereo vocal tracks, 5 s–5 min, $0.0083/s) and ACE Step / ACE Step 1.5 (StepFun-AI open-weights, tag-driven composition, multilingual lyrics, $0.0002–0.0003/s, ~27× cheaper), plus ACE Step audio-inpaint (regenerate a time range inside an existing track) and ACE Step audio-outpaint (extend a track before or after). Picks the right model for the user's actual intent — premium vocal hook, cheap background music library, multilingual pop song, repair a bad chorus, lengthen a 30 s draft into a 2 min cut — and ships each model's documented prompting patterns plus the minimal `runcomfy run` invoke. Triggers on "generate music", "make a song", "AI music", "background music", "instrumental track", "soundtrack", "jingle", "theme music", "royalty-free music", "compose", "music with lyrics", "extend music", "fix this song", "inpaint music", or any explicit ask to

Audits an EXISTING UI/codebase for generic AI patterns and applies targeted craft fixes — layout, interactivity, content, iconography, and code quality — without discarding the project's own identity. Use when a UI looks flat, generic, or "AI-slop" and there is code to improve, not build from scratch. Triggers on: "improve the design", "looks generic", "not polished enough", "redesign this", "elevate the UI", "it looks boring", "make it better looking", "apply taste", "design review". Works with any CSS framework. For designing a NEW project's identity from a brief, use `taste-skill` instead — this skill only upgrades what's already built. Source: github.com/Leonxlnx/taste-skill (redesign-skill), restored to the full checklist + the project-identity rule the earlier port had dropped.

Expert PCI DSS compliance advisor covering PCI DSS v4.0.1 (current) and v4.0. Use this skill whenever a user asks about PCI DSS, payment card security, cardholder data protection, CDE scoping, SAQ types (A, A-EP, B, B-IP, C, C-VT, P2PE, D), ROC, AOC, QSA assessments, ASV scans, merchant levels, service provider levels, network segmentation, penetration testing, tokenisation, encryption of PAN data, or any of the 12 PCI DSS requirements. Also trigger for questions like "are we PCI compliant?", "how do I scope my CDE?", "which SAQ applies to us?", "what changed in PCI DSS v4.0?", "how do I prepare for a QSA audit?", or any request involving payment data security, cardholder data environment, or PCI certification readiness.

Route local Git work into the safest next move: branch hygiene, selective staging, commit cleanup, merge-vs-rebase choice, conflict resolution, lease-safe pushes, and recovery from resets or bad history edits. Use when the user needs help preparing a branch, cleaning up commits, syncing with an updated base, resolving local Git conflicts, pushing rewritten history safely, recovering lost commits, or getting a diff ready for review. Not for hosted PR review, repo administration, or sprint planning.

Post-exploitation workflow. Covers privilege escalation (Linux SUID/sudo/kernel, Windows UAC/service/token), persistence assessment, local enumeration, credential harvesting, and pivot preparation. Structured workflows for Linux and Windows targets using impacket, netexec, john, linpeas/winpeas, and standard Kali tools. Includes kernel exploit reference tables, GTFOBins exploitation chains, Potato attack selection, Docker/container escapes, DLL hijacking, SSH key harvesting, credential recovery from memory, and Windows token manipulation. Chains from /pentester or /credential-audit when access is obtained.

| Use when starting a chain from a GitHub issue — turning an issue URL or number into a triaged, planned, dispatched, and reviewed pull request. Classifies the thread (bug → root-cause discipline, feature → plan chain, question → drafted reply), synthesizes a spec from the issue's own acceptance criteria, then runs the standard chain with a PR exit. Trigger with /hyperflow:issue, "work on issue #N", "fix this issue <url>", "implement this issue", "triage issue #N and raise a PR".

동시에 굴리던 여러 워크트리를 한 번에 통합합니다. 각 워크트리와 연결된 이슈를 확인하고 증거로 실제 해결 여부를 판정한 뒤, merge 를 시도하기 전에 충돌을 확정하고 계획한 순서대로 누적 검증해 순서 때문에 깨지는 경우까지 잡아냅니다. 충돌은 작업 브랜치 쪽에서 양쪽 의도를 보존하는 방향으로 해소해 승인받고, 비판 서브에이전트로 모호성을 걸러낸 다음 PR 을 merge 하고 통합 테스트로 재검증하고 이슈를 닫습니다. `$issue-merge`, "워크트리 전부 merge", "이슈들 통합", "PR 충돌 해결하고 합쳐줘" 요청과 issue-end 에서 merge 를 선택했을 때 사용합니다.

Provides frameworks for both acquiring companies and being acquired, covering strategic rationale, due diligence, valuation, integration, and negotiation.

Orchestrates multi-framework compliance programs by selecting applicable frameworks, mapping control overlaps, simulating audits, and consolidating evidence checklists.

Provides frameworks for international market expansion, including market selection, entry modes, localization, and go-to-market strategy.

Creates persona-targeted, step-by-step CodeTour walkthroughs that link to real files and line numbers for onboarding, architecture, PR review, and more.

Generate, review, fix, and migrate Playwright end-to-end tests with templates, CI integration, and optional TestRail/BrowserStack sync.

Ensures skills are invoked before any response, including clarifying questions, and establishes how to find and use skills.

Orchestrate expensive frontier models as reviewers and cheaper subagents for bounded, token-heavy work to optimize cost and quality.

Review UI implementations against design quality standards and design system compliance, or create distinctive, production-grade frontend interfaces from scratch.

Provides guidance and reference material for instrumenting web applications with Azure Application Insights, including telemetry patterns, SDK setup, and configuration references.

Create, run, and analyze evaluation suites for Microsoft 365 Copilot declarative agents using the @microsoft/m365-copilot-eval CLI.

Guides through interactive deployment of Azure OpenAI models with full control over version, SKU, capacity, content filtering, and advanced options.

Serve LLMs and VLMs on NVIDIA Jetson devices using vLLM or SGLang with optimized Docker containers and quantization presets.