AnastasiyaW

@anastasiyaw source repo

58 skills
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15 hours ago last updated

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Lean Code · anastasiyaw
On-demand minimalism intensifier — find the smallest sufficient, verified implementation for the requested outcome. Use when the user says "be lazy / yagni / simplest / minimal / shortest / don't over-engineer", complains about bloat / boilerplate / unnecessary dependencies / abstraction, or before writing a substantial chunk of new code. Supports intensity: lite / full / ultra. Pairs with the always-on quality-code rule and the over-engineering-advisor hook. Do NOT use as a general code-review or bug-hunting pass — it only removes over-building and will not find unrelated correctness defects; use /code-review or /review for those.

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Plan To Tickets · anastasiyaw
Use when a large plan, PRD, feature, refactor, research plan, or multi-step coding task must be split into small ready-for-agent tickets with acceptance criteria, verification commands, blockers, and vertical tracer-bullet slices. Do not use for small tasks that should be implemented directly, single-bug fixes, or chat-only summaries.

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Caveman · anastasiyaw
Ultra-compressed reply mode. Cuts output tokens ~65-75% by answering in terse "caveman" style while keeping full technical accuracy, and shapes what survives: action first, state restated every turn, concrete time estimates, visible wins. Intensity levels: lite, full (default), ultra, wenyan-lite, wenyan-full, wenyan-ultra. Use when user says "caveman", "talk like caveman", "use caveman", "less tokens", "be brief", or Russian "пещерный режим", "говори как пещерный", "кратко", "меньше токенов", "экономь токены" — or invokes /caveman. Preserves the user's language (Russian in → Russian caveman out). Off only: "stop caveman" / "normal mode" / "обычный режим". Do not use merely because a response should be concise, and do not use when the user requests normal prose, a polished document, or exact wording.

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Deslop · anastasiyaw
Remove AI-generated code noise from the current diff while preserving behavior. Use for deslop, AI slop cleanup, unnecessary comments, defensive checks, any casts, or needless nesting after an agent-generated change. Do not use as permission for a broad rewrite or when a real bug has not been isolated.

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UI Design · anastasiyaw bundle
Unify product UI design, frontend implementation, and verification. Use when asked to design, redesign, build, or fix a web, desktop, or mobile interface; a page, dashboard, form, component, design system, responsive layout, accessibility, interface animation, or editable hero/banner/infographic within a product surface. Combine visual decisions with implementation. Do not use for backend-only work, generic architecture, standalone artwork or slide decks, or browser-test-only requests.

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IOS Development · anastasiyaw bundle
Comprehensive iOS app development skill. Use this skill for ANY iOS-related task: writing Swift/SwiftUI/UIKit code, architecting apps, debugging crashes, setting up navigation, networking, data persistence, animations, performance optimization, App Store submission, Xcode configuration. Trigger when user mentions: iOS, Swift, SwiftUI, UIKit, Xcode, iPhone/iPad app, Combine, CoreData, SwiftData, MVVM, TCA, URLSession, async/await, @State/@Binding/@ObservableObject, NavigationStack, XCTest, TestFlight, provisioning profiles, or any Apple platform development. Always use this skill before writing iOS code or architecture. Do NOT use for web frontends (HTML/CSS/JS, React/Vue, browser UI) — even a WebView's page content is web work; use frontend-design for that. This skill is native Apple-platform code only.

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Agent Harness Design · anastasiyaw bundle
Designing agent harnesses and tool systems — risk taxonomy for tools, permission decisions, draft/commit pattern, structured tool results, agent budgets (10 types), context trust labels against prompt injection, plan-artifact, approval records, observability and traces, evals (13 categories), event model, streaming buffering, 3rd-party skill install checklist, agentic RAG, self-improving SOP loops, model policy, reasoning effort, and Programmatic Tool Calling adoption gates. Use when building a new Agent SDK app, custom orchestrator, MCP server, Cloudflare Worker with tool calls, agentic RAG pipeline, model router, or model-tier policy; when designing tools and permissions; when writing an agent loop; or when you need trust labels for external content. Do NOT use for improving or auditing an already-built harness (use harness-audit / harness-design instead), nor for ordinary Claude Code sessions where the harness is already given.

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Repo Map · anastasiyaw bundle
Ranked symbol map of a codebase within a token budget — a compact "what matters in this repo" before reading files. Use when starting work in an unfamiliar/large codebase, before a refactor or deep-review fan-out, when you need JIT context instead of dumping whole files, or asked "give me a map of this repo / where are the important functions / what's the structure". Zero-dependency (stdlib only); Aider-inspired regex extraction and PageRank ranking, not a tree-sitter parser. Do NOT use to find correctness/security defects in a change or to audit a diff; use deep-review for that (this only ranks and lists symbols, it does not evaluate code quality).

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Agents Best Practices · anastasiyaw bundle
Use when designing, auditing, refactoring, or explaining an agentic harness for any domain, especially when work must continue from a measured gap to verified completion. Covers provider-neutral loops, tools, permissions, environment adaptation, planning, durable workflow state, context, skills, observability, evals, and safety for OpenAI, Anthropic, and compatible APIs. Not for implementing an ordinary app feature or reviewing one concrete diff.

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Ml Research Lab · anastasiyaw
Machine-learning research loop for dataset curation, fine-tuning, evaluation, inference deployment, experiment tracking, and model explainability. Use when working on ML experiments, training data, model benchmarks, RunPod/GPU runs, classifier quality, vLLM/GGUF serving, SHAP-style model explanations, or research-to-code iterations. Do not use for a simple code edit that has no ML dataset, metric, model, or experiment artifact.

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Vlm Segmentation · anastasiyaw bundle
Choose and evaluate VLM or segmentation pipelines, including text-conditioned detection, masks, part labels, model-license constraints, and measured GPU deployment choices. Use when a task has a VLM or segmentation component; route pure diffusion prompting, training, or serving to its specialized skill.

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Layer New · anastasiyaw
Scaffold a new layer in a project's docs/layers/ tree following the feature-layer architecture (principle 28). A layer is a bounded concern (security, data, ui, infrastructure, domain) with its own invariants, decisions, gotchas, patterns, and feature narratives. Use when: "create a new layer", "add security layer", "scaffold layer", "start tracking <concern> separately", "/layer-new", "add bounded concern". Operates on the kb-skeleton structure; idempotent -- will not overwrite existing layers. Do NOT use to scaffold an individual feature narrative inside an existing layer; use /feature-new for that (a layer is the container, not the per-feature doc).

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Control UI · anastasiyaw
Drive and inspect a local web, IDE, or Electron UI with browser or CDP automation and evidence. Use for UI regressions, screenshots, accessibility snapshots, visual diffs, focus, keyboard, scrolling, resize, console, network, performance, or heap checks. Do not use for backend-only changes or for a screenshot without a behavior claim.

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Motion Framer · anastasiyaw bundle
Motion & Framer Motion

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UI UX Pro Max · anastasiyaw bundle
Use when designing, building, reviewing, or fixing a web, mobile, or desktop interface: pages, components, design systems, accessibility, interaction, responsive layout, typography, color, charts, or stack-specific UI implementation. Do not use for pure backend/API/database/DevOps work or non-visual scripts unless the task changes how the product looks, feels, moves, or is interacted with. Searchable local data: 79 styles, 192 palettes, 74 font pairings, 119 UX guidelines, 105 icons, 17 GSAP presets, 25 chart types, and 22 stacks.

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Control CLI · anastasiyaw
Drive and inspect an interactive CLI or TUI with a repeatable local harness, deterministic input, transcripts, and optional profiling. Use for CLI UX checks, prompt flows, startup regressions, hangs, interrupts, resize behavior, or memory growth. Do not use for a non-interactive command that a normal test can cover.

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Deep Review · anastasiyaw
Parallel competency-based code review. Launches independent Agent reviewers per competency (security, performance, architecture, database, concurrency, error-handling, frontend, testing), each with a focused checklist and isolated context. Synthesizes findings into unified report with FIX/DEFER/ACCEPT triage. Use when: "deep review", "thorough review", "parallel review", "review by competency", "full code review", or for large diffs (200+ lines) where /review may be too shallow. Complements /review (pre-landing) — this is for deep dives. Do NOT use just to orient in an unfamiliar codebase or get a structural symbol overview; use repo-map for that (this audits a concrete diff for defects, it is not a navigation map). Review is read-only unless the user explicitly asks to review and fix.

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Verify This · anastasiyaw
Prove a concrete behavior, performance, UI, CLI, API, or memory claim with fresh baseline-versus-treatment evidence and one explicit verdict. Use when asked to verify, prove, compare before and after, show evidence, or confirm that a fix works. Do not use for vague claims such as cleaner code, a full plan-based release verification, or a known bug that needs a red-to-green reproducer.

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Feature New · anastasiyaw bundle
Scaffold a feature narrative in an existing project layer with Design, Plan, Verify, and Conclusion sections. Use when: "create a new feature", "start work on feature", "scaffold feature doc", "/feature-new", or "begin feature narrative". Inspects and preserves the target project's feature ID, registry, filename, and coordination conventions; does not create a missing layer (use /layer-new).

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Proof Verify · anastasiyaw bundle
Plan-based verification - freeze acceptance criteria before building, then verify after with an independent fresh-context agent (the builder must not verify their own work). For multi-stage work, seal accepted inputs with commit/tree, contract, input/output digests, and a fresh verdict so downstream stages do not reopen them. Use when - "verify against plan", "proof check", "independent review", "check the implementation", or confirming a feature built from a plan meets spec. Do NOT use for quick one-off checks with no plan, or for letting the builder self-verify.

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Frontend Design · anastasiyaw bundle
Создание высококачественных, визуально выдающихся фронтенд-интерфейсов. Используй ВСЕГДА когда пользователь просит создать веб-страницу, компонент, лендинг, дашборд, UI-кит, форму, карточки, навигацию, анимации, или любой другой веб-интерфейс. Скилл покрывает: HTML/CSS/JS компоненты, React/Vue/Svelte, Tailwind CSS, адаптивный и мобильный дизайн, визуальные стили (glassmorphism, neomorphism, material, flat, градиенты, тёмная тема), интерактивность (drag-and-drop, анимации, hover-эффекты, transitions), верстку (Flexbox, Grid, Container Queries), производительность, доступность (WCAG/ARIA), дизайн-системы и токены. Если пользователь хочет что-то "красивое", "современное", "стильное" в вебе — обязательно используй этот скилл. НЕ используй для нативных мобильных приложений (iOS/Swift/SwiftUI, Android) — для iOS бери скилл ios-development; этот скилл только про веб-UI (браузер).

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Humanize English · anastasiyaw
Edit English drafts for clear, natural language while preserving facts, uncertainty, technical meaning, citations and genre. Use when: humanize this text, remove AI-style filler, improve English prose, or edit an English article before publication. Not an authorship detector or a promise to bypass one. For Russian use humanize-russian; for thesis/evidence and structure use article-structure-review.

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Humanize Russian · anastasiyaw
Редактировать русский текст для ясности и естественного звучания, сохраняя факты, термины, источники и жанр. Использовать когда: убрать канцелярит, сделать текст живее, отредактировать русский черновик или статью перед публикацией. Не определяет авторство и не обещает обход детекторов. Для английского — humanize-english; для структуры и доказательств — article-structure-review.

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Flux2 Lora Training · anastasiyaw
Plan or review LoRA and edit-training work specifically for FLUX.2 Klein or Qwen-Image-Edit, including paired datasets, trainer-version contracts, and held-out fidelity checks. Do not use for generic Stable Diffusion/DiT training, prompt authoring, or model serving; route those tasks to their specialized skill.

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Pixel Art Studio · anastasiyaw bundle
Create production-quality pixel art and animations programmatically. Use when the user asks to "create pixel art", "draw a sprite", "make pixel animation", "generate sprite sheet", "convert image to pixel art", "pixelate this image", "make a pixel character", "пиксель арт", "пиксельная графика", "спрайт", "像素画", "像素艺术", "도트 그래픽", "픽셀 아트", "8-bit/16-bit/hi-bit style", "retro game art", "Aseprite-like output", "indie game sprite". Covers single-frame sprites, frame-by-frame animations, walk cycles, idle/attack/death animations, sprite sheets, GIF/APNG export, image-to-pixel-art preprocessing (downsample + quantize + dither), 30+ bundled palettes (NES, GameBoy, PICO-8, Endesga 32/64, DawnBringer 16/32, Sweetie 16, Resurrect 64, Korean 오방색/단청, Chinese 故宫/青花/五行, Russian Stoneshard-inspired), 5 dithering algorithms (Bayer 2/4/8, Floyd-Steinberg, Atkinson, Ordered, Blue Noise), automated quality scoring (orphan pixels, doublies, banding, pillow-shading, AI-slop detection), and Generator-Evaluator review via the pixe

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Harness Audit · anastasiyaw bundle
Score a project's agent harness across 5 subsystems (Instructions / State / Verification / Scope / Lifecycle), identify the bottleneck, and produce a prioritized improvement plan. Use when assessing if a project is ready to graduate to [LONG-RUN] status, when an agent keeps failing despite good models, or when adopting our stack on a new codebase. Do NOT use to design or build a new harness from scratch — this only scores an existing one; for greenfield harness/agent architecture use harness-design (or agent-harness-design).

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Bug Reproducer · anastasiyaw bundle
Find likely software bugs in a codebase, rank concrete bug candidates, and prove or reject them with focused regression tests before proposing a fix. Also turn bug reports, stack traces, screenshots, failing behavior, support tickets, and regressions into minimal reproducible cases with red-to-green evidence. Use when Codex needs to hunt for unknown bugs, audit code for correctness defects, test suspicious edge cases, reproduce a reported failure, isolate root cause, or verify that an approved fix works without regressions. Honor explicit user authority for the requested fix; use approval gates only for authority that the request did not already grant or when scope materially changes. Do NOT use for ordinary implementation where no bug investigation or reproduction is needed.

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Diffusion Engineering · anastasiyaw bundle
Практическая инженерия диффузионных моделей: архитектуры, обучение, инференс, оптимизация памяти. Использовать при любых задачах с диффузионными моделями: проектирование или модификация архитектуры (UNet/DiT/Flow/Flux), выбор и настройка schedulers/samplers, дообучение (LoRA/DreamBooth/full fine-tune), оптимизация памяти (AMP/checkpointing/ZeRO/FSDP/quantization), замена или fusion текст-энкодеров (CLIP/Qwen), работа с Diffusers, отладка диффузионных пайплайнов, оценка качества (FID/CLIPScore/LPIPS), latent diffusion, VAE, guidance/CFG, rectified flow, Stable Diffusion, SDXL, Flux. Также применять при вопросах про GPU-память при обучении генеративных моделей, text-to-image пайплайны, ControlNet, multi-encoder fusion, WebDataset. Do NOT use for writing FLUX.2 Klein generation prompts (use flux2-klein-prompting) или для FLUX.2 Klein / Qwen-Edit LoRA-тренинга и edit-LoRA (use flux2-lora-training); это общая диффузионная инженерия, не специфика FLUX.2 Klein.

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Flux2 Klein Prompting · anastasiyaw
Expert prompt engineering for FLUX.2 [klein] image generation and editing model. Use this skill whenever the user wants to create prompts for FLUX.2 [klein], generate images, edit photos with the klein model, work with multi-reference image editing, or needs templates for T2I/I2I tasks. Trigger for any mention of: FLUX.2, flux klein, BFL API, image editing prompts, text-to-image prompts for FLUX, product mockups, poster generation, UI mockups, sticker packs, character design, seamless textures, or any request to write/improve/translate prompts for FLUX-family models. Also trigger when user asks about guidance_scale, inference steps, distilled vs base modes, or multi-reference workflows. Do NOT use for training a FLUX.2 Klein / Qwen-Edit LoRA (use flux2-lora-training), nor for reconstructing a prompt FROM an existing source image (use forensic-prompt-compiler); this skill is for authoring generation/edit prompts only.

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Harness Design · anastasiyaw
Design a scoped multi-agent harness for a requested long-running AI workflow. Preserve the user-approved product boundary while using Generator-Evaluator separation, testable sprint contracts, context management, and task-appropriate validation. Based on Anthropic Engineering patterns. Use when: "build a harness", "multi-agent architecture", "agent orchestration", "generator-evaluator", "long-running app", "harness design", "agent pipeline", "quality evaluation loop", "sprint contract", "build app with agents", "Claude Agent SDK architecture", or when building complex full-stack apps that need planning → generation → evaluation cycles. Also use when discussing context degradation, self-evaluation bias, or assumption testing in AI workflows. Do NOT use to stress-test or critique an already-written plan document; use plan-swarm-review for that (this skill designs the harness, it does not review plans).

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Code Complexity · anastasiyaw bundle
Keep each unit comprehensible while the code grows: deep modules over shallow ones, information hiding, honest names, small functions with one job, error handling that does not lose the error, DRY and orthogonality, design by contract, and not leaving broken windows. Merges module-complexity management with naming/function/error-handling discipline and the pragmatic meta-rules. Use when writing or reviewing a function, class or module; when an interface feels wide, a class feels shallow, or a change in one place forces edits in three; when the user says "this is hard to follow", "clean this up", "review this code", "is this a good abstraction", "too many parameters", "pass-through method", "duplicated logic", or asks about naming, comments, error handling or unit tests. Do NOT use to decide where a new module LIVES or which modules exist (use architecture-first), to plan capacity or storage (use system-and-data-design), to execute a named transformation on a file that is already too large (use refactoring-saf

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Gemini Delegate · anastasiyaw
Делегирование задач в Gemini CLI с проверкой установленной версии, доступной модели и текущего доступа. Use when - спроси/делегируй gemini, second opinion от другого вендора, bulk-курация картинок/данных, нужен большой контекст на чтение, или диагностируй quota/model ошибку Gemini. НЕ используй для делегирования в OpenAI Codex (другой вендор/CLI — это скилл codex) и не передавай секреты во внешний LLM.

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Distill Feedback · anastasiyaw bundle
Turn captured user-correction signals into durable rules (learn-from-corrections loop). Use when - /distill-feedback, "process feedback queue", "what corrections did I give you", "encode lessons from my corrections", session-feedback-capture queued sessions, "обнови правила по моим поправкам", "разбери очередь обратной связи". Reads ~/.claude/feedback/queue.jsonl, LLM-semantically detects durable corrections, proposes atomic rules, applies human-gated via delta-merge. Do NOT use to act on a single in-session correction (just apply the fix directly) or to hand-edit settings.json behaviors; this only mines the queued feedback backlog into durable rules.

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Harness Feedback · anastasiyaw
Use when an agent says a test, VM, proof, evaluator, or release gate is overloaded, too strict, blocking staging, or causing false positives; split checks by profile, measure the burden, preserve high-risk evidence, and verify the smallest corrected workflow. Do not use for ordinary test selection, a single test failure, or a full security audit without a harness-scope question.

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Testing Strategy · anastasiyaw
Use when planning or reviewing tests for a code change, choosing between unit, focused regression, integration, contract, end-to-end, performance, security, property-based, or agent-evaluation checks; classify change risk first and select the smallest evidence set that proves the behavior. Do not use for a single obvious test command, pure documentation changes, or a full security audit without a testing question.

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Pixel Art Storyboard · anastasiyaw bundle
Convert short scene descriptions, book/album cover briefs, or 2-paragraph synopses into seamless-loop animated pixel-art covers rendered as self-contained HTML+canvas. Companion skill to pixel-art-studio. Use when the user asks to "make a cover for", "animated book cover", "looped pixel scene", "convert this story description to pixel art", "create ambient pixel animation", "обложка для книги в пиксель-арте", "анимированная обложка", "封面像素画", "픽셀 아트 표지", or provides a short narrative/synopsis and wants a visual result. Covers: 5-element scene framework (Subject + Setting + Lighting + Palette + Motion), iconographic shorthand for symbolic accents, seamless loop techniques (phase-based parametric, sub-pixel breathing, LCM-clean parallax, deterministic particle systems), loop period selection by mood, three prompt registers (LLM agent / human artist / SDXL LoRA), single-HTML-file deliverable in dark-atmospheric style with parametrized canvas rendering. Generates the same engine pattern as the user's `Grass Fiel

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Forensic Prompt Compiler · anastasiyaw
Forensic image-to-prompt compiler for image generation models. Use this skill whenever the user wants to: convert/describe an existing image into a generation prompt, reconstruct a scene as a prompt, generate prompts from reference images for AI image tools (Midjourney, FLUX, Stable Diffusion, DALL-E, or any diffusion model), write prompts that preserve exact visual properties of a source image, or needs precise control over identity-safe subject description, geometry lock, lighting reconstruction, color anchoring, or handler-based special cases (floating scenes, collages, close-ups, jewelry, garments, surreal elements). Also trigger for requests involving: image editing prompts, reference-driven generation, pose description, camera angle locking, fabric/material description, or any "turn this image into a prompt" task. Do NOT use for composing prompts from scratch with no source image (use flux2-klein-prompting), nor for training a LoRA on edit pairs (use flux2-lora-training); this skill reconstructs a promp

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Plan Swarm Review · anastasiyaw bundle
Iterative plan review using multisampling + focused decomposition. Launches parallel independent agents to find issues that single-pass review misses. Up to four bounded rounds: broad, multisample, focused, focused-plus-multisample. Use when: "swarm review", "review plan thoroughly", "multisample review", "deep plan review", "plan swarming", "stress test the plan", or when evidenced cross-component risk warrants deeper plan review. Size alone does not require a swarm or another review round. Do NOT use to design a multi-agent harness or Generator-Evaluator architecture from scratch; use harness-design for that. Ordinary code/diff review routes to deep-review; use this skill's code mode only when the user explicitly requests a swarm security/bug review of code.

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Architecture First · anastasiyaw bundle
Decide module boundaries before the first file: what modules exist, which way dependencies point, who owns state, and what each module may know. Use when starting a project, service, site, API, or subsystem; adding a feature with no obvious home; resolving a circular import or inverted framework dependency; or writing an ARCHITECTURE.md or ADR. Do not use for a one-file script, throwaway experiment, bug fix inside an established seam, naming/function-shape cleanup (use code-complexity), an existing oversized module (use refactoring-safely), or capacity/data scaling decisions (use system-and-data-design). This defines earned boundaries; it does not license speculative layers.

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Refactoring Safely · anastasiyaw bundle
Change the structure of code that already exists without changing what it does: smells as triggers, the named transformations (extract/inline, move feature, organise data, simplify conditionals), and above all the workflow that makes it safe — characterization tests first, one transformation at a time, green between every step. Use when a file or function is already too large; when asked to "split this module", "extract this", "break up main.py", "clean up this legacy code", "reduce coupling here"; when a shape advisory fires on a grown file; or before any restructuring of code that has users. Do NOT use to decide the target layout of a NEW project (use architecture-first), for unit-level naming and function quality in code you are writing fresh (use code-complexity), for capacity or storage decisions (use system-and-data-design), or to strip over-engineering on request (use lean-code). This is the transformation with a net; deciding WHERE things should end up is a different question, and doing both at once i

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Remote Compute Ops · anastasiyaw bundle
Operate GPU and remote compute across RunPod (Pods and Serverless), Massed Compute VMs, and owned or virtual remote servers through existing bridges, SSH sessions, MCP/API adapters, bounded polling, cost controls, and resumable lifecycle checks. Use when the user mentions RunPod, Massed Compute, a remote GPU/server/VM, SSH bridge/tunnel/bastion/Tailscale, training or inference on rented compute, GPU inventory, billing, or asks to minimize API/SSH connections and avoid rate limits. Do not use for generic cloud architecture, local-only GPU work, or application code with no remote-resource operation.

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Epistemic Challenge · anastasiyaw
Use this skill when the user asks the agent not to agree automatically, to challenge an assumption, evaluate a proposal critically, identify counterevidence, or make a high-consequence decision under uncertainty. Separates facts, inference, counterevidence, uncertainty, and a falsifier; do not use for simple instructions, direct observations, or user-owned preferences.

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Architecture Quality · anastasiyaw
Keep web applications, APIs and services readable as they grow: choose feature or domain seams, assign state ownership, enforce dependency direction, keep adapters thin, and verify file shape. Use when starting or extending a web app, backend, frontend, API or multi-page product; when a change makes a module hard to read; when architecture review finds a god file, cross-feature imports, a circular dependency or a framework-heavy domain. Load architecture-first first for a new system, and refactoring-safely for an existing oversized module. Do not use for a one-file script, throwaway spike or a purely local naming change.

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Article Structure Review · anastasiyaw
Проверить структуру технической статьи после черновика: задача читателя, жанр, опора значимых утверждений на доказательства и честные ограничения. Use after the first draft, before publication. Исправлять структуру, когда это входит в запрос; не создавать обязательный конвейер из других навыков. Для локальной языковой редактуры — humanize-english или humanize-russian.

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Script Evaluator · anastasiyaw
Evaluate video scripts and presentations for flatness, tension, and emotional impact. Use when: 'is this script good', 'review script', 'evaluate video', 'why is this boring', 'flatness check', 'script review', 'improve script', 'rate this video'. Scores 6 dimensions (tension, specificity, emotional arc, hook, customer voice, visual variety), identifies specific problems, and suggests concrete fixes with examples. Do NOT use to generate a new script or scene structure from scratch (use video-narrative-arc), to build the product brief (use product-meaning-extractor), or to render/finish the video (use remotion-production-guide or video-post-production); this only critiques an existing script/scene.

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Native Cpp Memory · anastasiyaw bundle
Use this skill when diagnosing or correcting ownership, lifetime, or allocator defects in native C++ code.

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Notebooklm Grounded Research · anastasiyaw bundle
Use when: NotebookLM, notebooklm MCP, large documentation sets, courses, books, papers, or citation-backed research are mentioned. Retrieves a small grounded answer from a stable corpus, preserves citations, and verifies claims against primary documentation, repository code, and tests. Do not use when: the answer is already in a small local file, the source is rapidly changing, or a live runtime/test is the authority.

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System And Data Design · anastasiyaw bundle
Decide whether the system will hold, and where the data lives: requirements and load first, then back-of-the-envelope numbers, building blocks (cache, queue, load balancer, CDN), and the data layer in depth — storage engines, indexes, replication, partitioning, transactions and consistency, batch vs stream. Use when sizing or scaling anything; choosing a database, cache, queue or index; when asked "will this hold", "how many machines", "which database", "do we need a queue", "read replica", "sharding", "eventual consistency", "why is this query slow at scale"; when designing an ingestion or processing pipeline; or when a service is slow under load rather than wrong. Do NOT use for module layout, dependency direction or domain boundaries (use architecture-first), for function- and naming-level quality (use code-complexity), for restructuring code that is already too large (use refactoring-safely), or for a low-traffic internal tool where the honest answer is one process and one database.

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Workflow Orchestration · anastasiyaw bundle
Написание и запуск Claude Code dynamic workflows (JS-оркестратор субагентов). Use when user просит workflow своими словами или включает ultracode, нужен fan-out на десятки-сотни агентов, codebase-wide аудит/миграция, cross-checked research, competency-review, batch-обработка списка элементов через стадии. Покрывает: примитивы phase/agent/parallel/pipeline/workflow, pipeline vs parallel, schema, budget, resume, quality-паттерны (adversarial verify, judge panel, loop-until-dry), и наши добавки к платформе (accounting, bounded retry, error policy, .runs observability, eval-harness, billing-дисциплина). Триггеры: явная просьба «use/run a workflow» или «запусти воркфлоу», оркестратор, fan-out, ultracode, deep-research, 1000 агентов, скрипт агентов. Do NOT use to design the agent/Generator-Evaluator architecture itself (use harness-design) or for a single one-shot subagent/review where no deterministic multi-stage script is needed; this writes the JS orchestrator, it is not for ad-hoc one-off agent calls.

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Observability Monitoring · anastasiyaw bundle
Design, audit, and troubleshoot production monitoring and observability using user-impact checks, layered telemetry, USE/RED, SLI/SLO/SLA, error budgets, cardinality controls, actionable alerting, burn-rate response, and postmortems. Use when asked about monitoring, наблюдаемость, алерты, Prometheus, Grafana, OpenTelemetry, logs, traces, profiles, service health, or incident evidence. Do not use for generic dashboard styling, frontend-only UI work, or unrelated code review.

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Video Narrative Arc · anastasiyaw
Proven narrative arc templates for product videos and ads. Use when: 'write script', 'video structure', 'narrative arc', 'scene plan', 'storyboard', '15 second video', '30 second video', '60 second video', 'how to structure the video', 'video script template'. Provides beat-by-beat templates with timing, emotional arc mapping, hook formulas, and pacing rules. Covers 10s-90s formats for social, product demos, launches, and pitches. Do NOT use to judge or score an already-written script (use script-evaluator), to derive the product insight/brief from scratch (use product-meaning-extractor), or to render the video in code (use remotion-production-guide); this stage only produces the structured script/beats.

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Cross Harness Continuation · anastasiyaw bundle
Use when work moves between Claude Code and Codex, a session resumes from a handoff, or an agent may rewrite an existing implementation. Loads the shared CONTINUITY.json contract, preserves accepted decisions, checks Git baseline and scope, and requires explicit replan mode for intentional redesign. Do NOT use for fresh work with no prior agent's decisions to preserve, for a single-harness session that no one else is continuing, or as a general handoff-writing helper (see the session-handoff rule); this skill governs the contract between agents, not the notes one agent leaves itself.

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Deepseek Provider Contract · anastasiyaw bundle
Validate a proposed DeepSeek API integration before any key or project context is sent: check thinking-mode tool-call history, strict-schema assumptions, bounded output, and provider data boundaries. Use when integrating DeepSeek, adding DeepSeek tool calls or streaming, debugging DeepSeek 400 after a tool call, or evaluating a DeepSeek harness/MCP. Do NOT use for a generic model comparison, ordinary local coding, or to send a repository transcript to a provider by default.

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Desktop Sessions Discovery · anastasiyaw bundle
Discover, search, and selectively restore Claude desktop app sessions hidden across multiple accountIds. Use when user mentions "missing sessions after account switch", "lost desktop sessions", "where do my old sessions live", or runs multiple Claude accounts on the same machine. Do NOT use for Claude Code CLI session history or resuming work within one session — this only recovers the native desktop app's per-accountId session files; for in-session continuity use handoffs.

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Video Post Production · anastasiyaw
Video post-production rules: audio mastering, color, captions, platform export. Use when: 'add music', 'add voiceover', 'export for tiktok', 'add captions', 'color grade', 'audio levels', 'master audio', 'export settings', 'platform requirements'. Covers FFmpeg patterns, audio chain, subtitle standards, and platform-specific export configs. Do NOT use to generate or animate the video frames/scenes in code (use remotion-production-guide), to write the script (use video-narrative-arc), or to evaluate script quality (use script-evaluator); this is the finishing stage applied to an already-rendered video.

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Product Meaning Extractor · anastasiyaw
Deep product analysis before creating videos, presentations, or ads. Use when: 'analyze product', 'extract value', 'product brief', 'what makes this product special', 'prepare brief', 'understand the product', 'video brief'. Takes a URL or product description and outputs a structured brief with core insight, enemy, transformation, proof, mechanism, and emotional hooks. Based on JTBD, StoryBrand, Obviously Awesome (April Dunford), and Value Proposition Canvas frameworks. Do NOT use for writing the script or scene timing (use video-narrative-arc), scoring an existing script (use script-evaluator), or rendering video (use remotion-production-guide); this is the upstream brief-only step before any script is written.

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Remotion Production Guide · anastasiyaw
Remotion (React video framework) production guide with Apple-style design rules. Use when: 'create video with remotion', 'remotion project', 'render video', 'product demo video', 'animated video', 'video from code'. Covers project setup, animation library, spring presets, typography rules, color palettes, pacing tables, scene templates, 3D integration, and export settings for all platforms. Do NOT use to write the script or narrative beats (use video-narrative-arc), to critique a script's impact (use script-evaluator), or for FFmpeg audio mastering/captions/platform color-grade on a finished render (use video-post-production); this stage builds and renders scenes in React/code.

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Thermo Nuclear Code Quality Review · anastasiyaw
Run an opt-in strict maintainability review for giant files, spaghetti growth, misplaced logic, weak boundaries, unnecessary abstractions, and missed structural simplifications. Use for a thermonuclear review, harsh code-quality audit, code-judo review, or a file approaching 1000 lines. Do not use as an automatic rewrite mandate or for cosmetic cleanup.

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58 published skills