Results for “zero”

Complete PortSwigger deep-dive with exact payloads for every lab variant including zero-day techniques

The English summary is being prepared. Showing the original description.

Complete PortSwigger deep-dive with exact payloads for every lab variant including zero-day techniques

The English summary is being prepared. Showing the original description.

Complete PortSwigger deep-dive with exact payloads for every lab variant including zero-day techniques

The English summary is being prepared. Showing the original description.

Complete PortSwigger deep-dive with exact payloads for every lab variant including zero-day techniques

The English summary is being prepared. Showing the original description.

Complete PortSwigger deep-dive with exact payloads for every lab variant including zero-day techniques

The English summary is being prepared. Showing the original description.

PortSwigger deep-dive with exact payloads for every lab variant including zero-day techniques

The English summary is being prepared. Showing the original description.

Complete PortSwigger deep-dive with exact payloads for every lab variant including zero-day techniques

The English summary is being prepared. Showing the original description.

Complete PortSwigger deep-dive with exact payloads for every lab variant including zero-day techniques

The English summary is being prepared. Showing the original description.

Complete PortSwigger deep-dive with exact payloads for every lab variant including zero-day techniques

The English summary is being prepared. Showing the original description.

Complete PortSwigger deep-dive with exact payloads for every lab variant including zero-day techniques

The English summary is being prepared. Showing the original description.

Writes, reviews, and debugs idiomatic Rust code with memory safety and zero-cost abstractions. Implements ownership patterns, manages lifetimes, designs trait hierarchies, builds async applications with tokio, and structures error handling with Result/Option. Use when building Rust applications, solving ownership or borrowing issues, designing trait-based APIs, implementing async/await concurrency, creating FFI bindings, or optimizing for performance and memory safety. Invoke for Rust, Cargo, ownership, borrowing, lifetimes, async Rust, tokio, zero-cost abstractions, memory safety, systems programming.

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デザインデータ（Figma などのデザインカンプ）を参照してコーディングするときの解釈原則とアセットの扱い。Figma の URL・MCP・デザイン画像・カンプをもとに実装や修正をするときに必ず使う。

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UI・機能・コンポーネントの実装レイヤー（HTML/CSS/JavaScript）を決定する判断基準。実装・修正の着手前に必ず読む。アコーディオン、モーダル、ポップオーバー、開閉・切替などのインタラクション実装を依頼されたときに使う。

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フロントエンド実装のコードレビューを実施する。PR レビュー、コードレビュー、実装チェック、品質確認を依頼されたときに使う。実装レイヤー選定の妥当性から各技術軸の観点まで順に検査する。

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MUST USE for ANY work on .py .pyi .rs .ts .tsx .mts .cts .go files. One philosophy: strict types, modern stacks (Pydantic v2 / serde+thiserror / Zod / gin+sqlc+pgx+slog), modern toolchains (uv+basedpyright+ruff / cargo+clippy+miri / Bun+Biome+tsc / gofumpt+golangci-lint v2+nilaway+go-race), parse-don't-validate, exhaustive match, typed errors, no any/unwrap/panic, 250 LOC ceiling, TDD. Routes to references/{python,rust,typescript,rust-ub,go}/. Triggers: write/edit Python/Rust/TypeScript/Go code, new project, gin server, bubbletea TUI, CJK IME, connect-go RPC, sqlc pgx, branded ids, exhaustive match, unsafe Rust, miri, oversized file, refactor, TDD, e2e test, arena, allocator, bumpalo, const fn, const generics, comptime, zero-alloc, bitfield, repr, scopeguard, errdefer, Zig-like, zerocopy, packed struct.

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Safe database migration manager for zero-downtime DDL changes and rollback plans. Activate on: database migration, schema change, DDL, rollback plan, zero-downtime migration, Prisma migrate, Drizzle kit, Flyway, column rename, table alter. NOT for: query optimization (use database-optimizer), ORM modeling (use data-pipeline-engineer), backup/restore (use devops-automator).

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Semantic image-text matching with CLIP and alternatives. Use for image search, zero-shot classification, similarity matching. NOT for counting objects, fine-grained classification (celebrities, car models), spatial reasoning, or compositional queries. Activate on "CLIP", "embeddings", "image similarity", "semantic search", "zero-shot classification", "image-text matching".

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Normalizes and transforms RNA-seq count matrices for DE, visualization, clustering, and ML. Covers between-sample (TMM, TMMwsp, RLE/median-of-ratios, upper quartile), within-sample (TPM, FPKM/RPKM), variance-stabilizing (VST, rlog, log-CPM), GC-content correction (cqn, EDASeq), and single-cell (scran deconvolution, scanpy normalize_total). Encodes the composition-bias rationale, the "most genes not DE" assumption and its catastrophic failure modes (MYC amplification, apoptosis, viral host shutoff, prokaryotic stress), the "lengthScaledTPM is not TPM" naming trap, the "TPM is not for DE" rule, the blind=TRUE vs FALSE decision, ERCC spike-in normalization (SBN), and the single-cell zero-inflation breakdown of TMM/RLE. Use when choosing or applying normalization, debugging shifted-MA-plot diagnostics, handling zero-heavy single-cell data, or correcting GC bias.

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Framework RLHF de alta performance com aceleração Ray+vLLM. Use para treinamento PPO, GRPO, RLOO, DPO de modelos grandes (7B-70B+). Construído em Ray, vLLM, ZeRO-3. 2× mais rápido que DeepSpeedChat com arquitetura distribuída e compartilhamento de recursos GPU.

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Framework de pré-treinamento visão-linguagem que conecta codificadores de imagem congelados e LLMs. Use quando você precisar de legendagem de imagens, resposta a perguntas visuais, recuperação imagem-texto ou chat multimodal com desempenho zero-shot de última geração.

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Modelo de fundação para segmentação de imagens com transferência zero-shot. Use quando precisar segmentar qualquer objeto em imagens usando pontos, caixas ou máscaras como prompts, ou gerar automaticamente todas as máscaras de objetos em uma imagem.

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Modelo da OpenAI que conecta visão e linguagem. Permite classificação de imagens com zero-shot, correspondência imagem-texto e recuperação cross-modal. Treinado em 400M pares imagem-texto. Use para busca de imagens, moderação de conteúdo ou tarefas visão-linguagem sem fine-tuning. Melhor para compreensão geral de imagens.

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Create editable charts, diagrams, figures, posters, or slides from intent, data, or references.

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Durable categorized record-keeping for any predicate-enabled walk. Trigger when: - Classifying a step's output for recording (decision, finding, debt, feedback). - Promoting a scratch artifact to the ledger, to repo/docs, or to a category home (.ledger/tech-debt/, .ledger/process-feedback/). - Auditing whether a draft is structurally ready for its destination. - Running a zero-context sensibility read before committing to promotion. - Recording a known limitation as a tech-debt entry (not prose in the log). - Recording a friction, miss, improvement, or process amendment. - Prompt contains: /record, record-keeping, promote, ledger note, zettelkasten, scratch-to-ledger, zero-context read, over-strip, classification trigger, tech-debt, process-feedback, amendment.

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