「nes」の検索結果

Spin up a live local Omnigent server + runner and exercise the native Pi TUI harness (pi-native) end-to-end — launch the real `pi` CLI via `omnigent pi`, drive turns through the web/bridge, smoke-test, and bug-bash. Load when developing, testing, or debugging the pi-native harness (omnigent/inner/pi_native_executor.py, pi_native_harness.py, omnigent/pi_native.py, pi_native_bridge.py, pi_native_credentials.py) or its bridge / extension / auth / model behavior.

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Spin up a live local Omnigent server + runner and exercise the native Antigravity (agy) TUI harness (antigravity-native) end-to-end — launch the real `agy` CLI via `omnigent antigravity`, drive turns through the web UI, smoke-test, and bug-bash. Load when developing, testing, or debugging the antigravity-native harness (omnigent/inner/antigravity_native_executor.py, omnigent/antigravity_native.py, antigravity_native_bridge.py, antigravity_native_rpc.py, antigravity_native_reader.py, antigravity_native_launch.py) or its agy launch / RPC mirror / tmux delivery / OAuth / MCP-relay behavior. NOT the in-process `antigravity` Gemini SDK harness.

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Entity compliance tracker — initialize, report upcoming deadlines, update status, run health audit, export to CSV. Maintains a compliance-tracker.yaml built from the entity table, calculates filing deadlines by entity and jurisdiction, and surfaces what's due in the next 30/60/90 days. Use when user says "entity compliance", "filing deadlines", "annual reports due", "entity tracker", "what filings are due", "entity health", or "good standing".

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프로젝트에 맞는 하네스를 설계하고, 전문 에이전트와 각 에이전트가 사용할 스킬을 만든다. 사용자가 '하네스 구성해줘', '하네스 구축해줘', '하네스 설계', '하네스 엔지니어링', '에이전트 팀 만들어줘'라고 요청할 때 사용한다. 새로운 분야나 프로젝트의 자동화 체계를 구축하거나 기존 하네스를 재구성·확장할 때도 사용한다. '하네스 점검', '하네스 감사', '하네스 현황', '에이전트/스킬 동기화'처럼 기존 하네스를 운영하거나 유지 보수하는 요청에도 사용한다. 실행 결과를 회고하고 피드백을 반영하는 작업에는 harness:evolve 스킬을 사용한다.

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Measures and interprets what a fuzzing campaign actually reaches, using llvm-cov, lcov, or a fuzzer's own coverage output. Covers baselining a new campaign, reading coverage reports, and turning uncovered regions into harness, seed, or dictionary work. Use when a fuzzer plateaus, when judging whether a harness is effective, after changing a harness, or when asking why some code is never reached.

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Designs and improves fuzzing harnesses for C/C++ and Rust. Covers mapping raw bytes onto a target API, generating structured inputs, avoiding non-determinism and false crashes, and deciding what to fuzz together. Use when writing a first LLVMFuzzerTestOneInput or fuzz_target! harness, when a campaign finds nothing or reports crashes that will not reproduce, or when the target API needs structured rather than raw input.

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Advanced API exploitation methodology focused on business logic abuse and sophisticated attack patterns that bypass traditional security controls. Covers business logic bypass through API call chaining and workflow manipulation. Addresses GraphQL-specific attacks including batching for credential brute-force, query depth exploitation, and introspection abuse. Includes pagination exploitation for data exfiltration, webhook hijacking for SSRF and data interception, and resource exhaustion through algorithmic complexity attacks. Covers race conditions in API transactions using parallel request techniques. Provides comprehensive JWT manipulation including algorithm confusion, kid injection, jku/x5u abuse, and claim tampering. Details API key leakage detection across source repositories, client-side code, and error messages. Covers undocumented endpoint discovery through predictable naming, debug routes, and source map analysis. Tooling includes Arjun, ParamSpider, jwt_tool, and GraphQL Voyager. Designed for authorized penetration testers targeting business logic layers that automated scanners miss.

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Design and implement parallax scrolling and scrollytelling data visualizations. Use when the user asks for parallax scrolling, scrollytelling, scroll-driven timelines, sticky graphics, Scrollama, ScrollTrigger, ScrollTimeline, view timelines, rich-media timelines, moviescrollers, scroll-scrubbed charts, staged narrative reveals, or interactive visual stories where scrolling changes a data visualization or media scene.

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Design, critique, route, and implement Gantt charts and schedule visualizations. Use when the user mentions Gantt charts, project schedules, roadmaps with task spans, milestones, dependencies, predecessors, critical path, baselines, WBS, resource plans, capacity timelines, MS Project, Primavera P6, Jira Advanced Roadmaps, GitHub Projects, Smartsheet, monday.com, Asana, ClickUp, Azure DevOps iterations, or importing/exporting project-management data for a timeline chart.

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Diagnose SaaS business health across growth, retention, efficiency, and capital. Use when preparing a business review or prioritizing urgent fixes.

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Opinionated Rails conventions: rich models, concerns, CRUD-everything, state-as-records, minimal dependencies, Minitest with fixtures. Load this skill BEFORE any code-level thinking, not only before editing a file. It is required the moment a task touches Rails code in ANY way: designing or even just discussing a data model, schema, migration, entity, association, field, validation, class, or method name; writing, planning, reviewing, analyzing, testing, debugging, or refactoring; or proposing any model, table, column, route, or code snippet inline in chat. If you are about to name a model or sketch a column you are already in scope, even in an exploratory back-and-forth where no file is written yet. Do not let a "we're just discussing" framing defer it. Do NOT use for non-Rails backends, NestJS, or general architecture (use nestjs-modular-monolith or coding-guidelines).

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Guides design and implementation of evolutionary modular-monolith platforms with DDD (strategic + tactical), flat-by-aggregate organization, an Anti-Corruption Layer for vendor independence, a transactional outbox for events, smart resilience (backoff with jitter, circuit breakers, idempotency), and a polished architecture HTML document with elegant SVG diagrams. Use when designing a platform or backend, defining bounded contexts, organizing modules and folders, choosing monolith vs microservices, decoupling from an external service (ERP, storage, AI), making calls resilient, adding real-time push, picking a 2026 TypeScript stack (Nx, NestJS, React), or producing an architecture document or diagram. Also triggers on 'modular monolith', 'bounded contexts', 'flat-by-aggregate', 'ports and adapters', 'architecture diagram'. Do NOT use for simple CRUD, NestJS-only deep implementation (use nestjs-modular-monolith), or pure domain-model review (use tactical-ddd).

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Build scene-by-scene chapters that advance left to right on one fixed stage while the user scrolls vertically, with native scroll as the only input. One pure function turns scrollY into scene, dwell and move, so forward, reverse, scrollbar drags, fast skips and reload at depth all land on the right frame. Covers dwell versus transition budgets, a burn-wipe or pan between scenes, chapter index and progress UI, glide-to-scene links that skip intermediate scenes, keyboard and reduced-motion behaviour. Use for horizontal scrollytelling, multi-scene product tours, "scroll down to travel sideways", chapter carousels driven by the wheel, or any piece where a wheel-jacked slider keeps breaking on touch, keys, refresh or back.

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Build a paper sheet in Three.js that reads as paper up close — washi, cotton rag or kraft with baked fibre and tooth relief, laid and chain lines, a torn deckle edge with frayed fibres, four-layer thickness, a rolled corner and crease, ink that wicks along the fibres, toasted aged edges, contact shadows and back-lit translucency. Use for a hung sheet, scroll, page, label, shoji pane or card that must survive a macro close-up, or when paper looks like a flat white plane, has ruler-straight edges, no thickness, or does not glow when lit from behind. Use 3d-wood-material, 3d-cloth-material or 3d-metal-material for those materials, and paper-cinder-transition for burning paper.

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Build the effects of an ice and frost skill as one visual language in Three.js. Frost that grows like real frost, not a painted fern: a dendritic tree grown on the CPU from a seed point, stems racing outward with barbs and sub-barbs that compete for space in one time-ordered queue, side branches leaned toward their tips, baked into a distance field so the shader draws hairline feathers growing out from the seed with a bright tip, rime, crystal glints and a contact shadow. Faceted ice spikes built from half-spaces and ray-traced against their own planes (Snell, Fresnel, total internal reflection, Beer-Lambert blue, trapped bubbles, a fracture network, frosted edges) that erupt along the frost line, crack along visible planes and shatter into convex pieces that tumble, land on a face and rest, with snow lumps and ice chips settled into the crust. A low freezing mist marched as wind-stretched banks that churn in place and part around the ice, a blizzard column of powder on helical strands with a fibrous veil, glinting diamond dust, and a scanned snow floor with dunes, broken crust, a raking moon with self-shadow and two populations of glints. Use for ice or frost skills, frost novas, ice spikes or walls, glacial eruptions, shattering ice, blizzards, snow devils, freezing mist, frozen ground, "ice and frost", "frost creep", "ice shards", "realistic ice" or "skill effects only". Includes two reusable modules and a five-beat demo on a scanned CC0 snow floor with a failure-mode switch.

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Analyzes the current project to surface high-value Routines use cases across the three trigger types (schedule, API, GitHub events). Usage: /routines-discover

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This skill helps users automatically extract official website and social media profiles. Agent should proactively apply this skill when users express needs like search for official website and social media contacts of a company, find YouTube and LinkedIn profiles by company name, extract social media links from a specific website URL, discover a company's X and Facebook presence, gather business contact details using their brand name, retrieve TikTok and Instagram links from a target website, track competitor social media strategy, extract multi-platform social links for lead generation, find official contact channels of local businesses, collect canonical profile URLs for outreach campaigns, or build a contact database from Yellow Pages leads.

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Drive tuios from inside one of its panes. Find out where you are running, read and write other panes, run work and wait on it instead of polling, report your own state so the person sees it, and talk to the other agents and the person safely. `tuios --skill <topic>` prints the rest: fleets of agents, turn checkpoints, shipping a worktree, the Inbox and approvals, push notifications, pairing a phone, mail, other machines, clients, events, MCP, the tmux shim, herdr's command line, pane grants, configuration, agent features off, errors and recipes.

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Hunt vector-store / embedding-layer weaknesses in RAG pipelines (OWASP LLM08 Vector and Embedding Weaknesses) — persistent corpus poisoning that survives across sessions and users (distinct from one-shot indirect prompt injection, which is owned by hunt-llm-ai), cross-tenant vector-database IDOR (unauthenticated or unscoped queries against Pinecone/Weaviate/Chroma/Milvus/Qdrant/pgvector), source-text/metadata leakage in similarity-search results, and retrieval-hijack via adversarial embedding proximity ('SEO poisoning' for RAG). Targets: any app with a shared knowledge base, document upload feeding a chatbot, or a directly reachable vector-DB port. Validate: a second, clean session/account must inherit a poisoned result, or a cross-tenant artifact must be independently verifiable — confabulation is not a finding, same bar as hunt-llm-ai. Use when target is RAG-backed, exposes a vector-DB port, or lets users upload documents that other users' queries later retrieve.

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Hunting skill for business logic vulnerabilities. Built from 12 public bug bounty reports. Covers coupon-race-stacking (Instacart, Stripe, Reverb), negative-quantity-in-cart price tampering (Upserve, Eternal/Zomato), decimal/fraction price-field overflow (Shipt), client-side checkout amount trust on PayPal redirect (WordPress.org), price-per-unit mass-assignment (Krisp), and archived-price swap / cart-TOCTOU (Stripe). Use when hunting business logic — heavy emphasis on financial-impact-demonstrated cases.

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Chinese LaTeX thesis assistant for existing .tex degree thesis projects (XeLaTeX/LuaLaTeX/latexmk). Use this skill whenever a user works on a Chinese master's or doctoral thesis needing compilation, GB/T 7714 bibliography checks, chapter structure mapping, template detection (thuthesis, pkuthss), terminology consistency, logic coherence review, heading lead-in checks, title optimization, de-AI editing, experiment chapter review, three-line table validation, or abstract structure diagnosis. Trigger even for single issues like "帮我编译论文", "检查国标格式", "看看绪论逻辑", "毕业论文", "学位论文", "硕士/博士论文", "三线表", "检查摘要", or "摘要结构".

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Deep-review-first audit for Chinese and English academic papers across LaTeX, Typst, and PDF formats. Use whenever the user wants reviewer-style paper critique, pre-submission readiness checks, pass/fail gate decisions, structured revision roadmaps, or re-audits of revised manuscripts. Trigger even if the user only says "review my paper", "check if this is ready to submit", "audit this PDF", "simulate peer review", "find the biggest problems in this manuscript", or "re-check whether I fixed the review issues". Do not use for direct source editing or compilation-heavy repair; route those to the format-specific writing skills instead.

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Unwraps hard-wrapped markdown files so that each sentence ends with a newline instead of mid-sentence line breaks. Joins continuation lines within a paragraph into single lines, then re-breaks at sentence boundaries (period, question mark, exclamation point). Preserves blank lines, headings, fenced code blocks, block quotes, and list items. Use when asked to unwrap text, fix line breaks, reflow sentences, or clean up hard-wrapped markdown or .qmd files.

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Deeply analyze any empirical economics PDF using the five-question framework (五问框架): research question, identification strategy, core estimand, robustness logic, and scholarly contribution. Converts the PDF to Markdown, dispatches 5 parallel sub-agents (one per question), then compiles a 2000–3000 Chinese-character report with a transferable methodology checklist. Optimized for empirical economics papers in top journals (AER, QJE, JPE, RFS, RoF, JFE, etc.). Use this skill whenever the user wants to: - systematically analyze an empirical economics paper - apply the 五问框架 (five-question framework) to a paper - extract transferable research design elements from a top-journal paper - understand a paper's identification strategy, estimand, or robustness logic - run /five-questions, /five-q, or /paper-five-q-analysis - "帮我做五问分析", "用五问框架分析这篇论文", "analyze this paper with the five-question framework"

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