'diff' 검색 결과

Integrate or upgrade cache-dit in SGLang diffusion, the image generation system. Follow guidance for resolving code conflicts, adding cache settings, testing feature combinations, and comparing generated images using quality measurements and logs.

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• Upgrading cache-dit in SGLang diffusion
• Resolving conflicts when porting upstream changes
• Adding per-request cache settings

Turn a Markdown code review into a single HTML file with code changes beside severity-labeled comments. Readers can jump to findings, inspect line numbers, and identify the named human reviewer.

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• Turning a lengthy Markdown code review into HTML
• Reading code changes beside review comments
• Jumping directly to findings by severity

Manage version control through GitButler’s but CLI. Select files or hunks, meaning sections of a diff, for commits; organize dependent branches, split or combine history, resolve conflicts, and create pull requests using task-specific command workflows.

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• Commit selected files or sections of a diff
• Split, combine, or reorder commits
• Arrange branches by dependency

Review code changes with an independent agent from a different model provider. After tests pass, check a fixed diff against acceptance criteria, send blocking issues back to the implementer, and repeat until review passes.

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• Get an independent review from another model provider
• Check a pull request against acceptance criteria
• Turn blocking findings into concrete fix tasks

Turn security findings into candidate code fixes with review results and summaries. Depending on the input, use independent source review or a pipeline with execution checks, then provide diffs for a person to review and apply.

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• Generating candidate fixes from triaged findings
• Preparing diffs for the highest-priority vulnerabilities
• Independently reviewing proposed security fixes

Choose when MSBuild copies files to build or publish folders. The skill explains settings that avoid unnecessary copies, restore output files changed by tests or apps, and apply shared copy behavior across existing projects.

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• Reducing unnecessary file copies on every build
• Restoring test databases changed between builds
• Choosing copy settings for configuration files

Design amino acid sequences from a protein backbone stored in a PDB file using ProteinMPNN. Generate multiple candidates, redesign selected chains while preserving specified residues, and vary sampling settings to prepare sequences for downstream structure prediction.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Designing sequences for RFdiffusion backbones
• Redesigning a chain while keeping interface residues fixed
• Generating candidates across multiple sampling temperatures

Inventory old and undocumented API versions, then compare their authentication, request limits, input validation, and exposed fields with current versions. Uses API specifications and archived records to identify overlooked endpoints with weaker security controls.

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• Finding API versions left reachable after deprecation
• Comparing old and current OpenAPI or Swagger specifications
• Checking security differences between API versions

Choose and implement methods for estimating causal effects from observational data or policy changes. Guidance covers method assumptions, estimation, diagnostic checks, and robustness tests that examine whether findings hold under alternative analysis choices.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Choosing a causal method for evaluating a policy change
• Analyzing policies introduced at different times across regions
• Checking instrumental variable strength and underlying assumptions

Identifies differential m6A methylation between conditions from MeRIP-seq paired IP/input data using exomePeak2 (GC-bias-aware differential via its bam_ip/bam_input control + bam_treated_ip/bam_treated_input treatment arms), QNB beta-binomial, MeTDiff HMM, and RADAR, plus the paired-symmetric edgeR/DESeq2-on-peak-counts route when batch/lot covariates need fixed-effect handling that exomePeak2's API does not accept. Covers paired vs unpaired vs interaction designs, batch confounding and per-lot meta-analysis, the stoichiometry-vs-expression-vs-IP-efficiency confound, and effect-size filtering against under-powered N=2 designs. Use when comparing m6A across two or more conditions, choosing between exomePeak2/QNB/RADAR/MeTDiff for a design, handling batch confounding when exomePeak2's API is too rigid, distinguishing real hyper/hypo-methylation from expression shifts, applying effect-size thresholds, or planning orthogonal stoichiometry validation (GLORI/SAC-seq/m6Anet mod_ratio).

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

提供在WinForms中通过ElementHost嵌入DiffPlex的WPF DiffViewer控件，实现两个字符串的对比及差异高亮显示的代码方案。

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Generate and interpret security-research diffs between Windows versions or patch levels using this repo's WinDiff CLI and databases. Use when comparing Windows builds or binaries such as ntoskrnl.exe, ntdll.dll, win32k*.sys, ci.dll, or cng.sys to find changed syscalls, symbols, types, mitigation flags, callbacks, ETW/EtwTi telemetry, code-integrity behavior, drivers, or attack surface. Explain likely intent and security relevance with Windows-internals knowledge, and frame findings for anti-malware/EDR, anti-cheat, and vulnerability-research audiences rather than returning an uninterpreted symbol list.

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Use denoising-diffusion-pytorch for PyTorch DDPM/DDIM image diffusion, 1D sequence diffusion, conditioning and guidance, and advanced diffusion variants.

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N-day / patch-diff workflow - given a CVE/advisory or a suspicious patch, diff pre- vs post-patch to locate the fixed bug, build a PoC for the unpatched version, and run variant analysis for a fresh bug. Triggers - "n-day", "patch diff", "diff the patch", "bindiff".

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Use Pierre Computer Company's `@pierre/trees` (path-first file tree) and `@pierre/diffs` (shiki-based code/diff renderer) in Kolu. Pierre ships Preact/vanilla cores with optional React wrappers — Kolu consumes the vanilla classes and wraps them in thin SolidJS components. Trigger when: wiring up a file tree, rendering unified diffs or syntax-highlighted files, replacing `@git-diff-view`, or any mention of `@pierre/trees` / `@pierre/diffs` / "pierre library".

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Implement a generative diffusion model (DDPM or score-based) with noise scheduling, U-Net architecture, training loop, and sampling procedures including DDIM acceleration. Use when building a generative model for image, audio, or molecular synthesis; implementing DDPM from a research paper; adding a custom noise schedule or conditioning mechanism; replacing a GAN-based generator with a diffusion alternative; or prototyping before scaling with production frameworks like diffusers.

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Analyze pre-trained generative diffusion models (Stable Diffusion, DALL-E, Flux) by computing quality metrics (FID, IS, CLIP score, precision/recall), inspecting noise schedules, extracting and visualizing attention maps, and probing latent spaces. Use when evaluating a pre-trained generative diffusion model's output quality, comparing noise schedule variants, analyzing cross-attention patterns for text-conditioned generation, interpolating between latent codes, or detecting out-of-distribution inputs.

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Before committing any non-trivial change, dispatch the diff to a reviewer runtime via ATO (`ato dispatch <reviewer> --session <id>`), parse the numbered/severity-tagged findings, apply or defer each one with a recorded justification, then commit. Fights the "build passes therefore ship it" failure mode — what Garry Tan calls the AI agent complexity ratchet. Place in the v2.16 stack: this skill is the LAST gate. `ato-warroom` decides the design; `ato-mission` runs the multi-step work and produces the diff; `ato-review` checks the diff before commit. When the review is part of a Mission, dispatch the review with `--require-tools read_file,grep,git_diff,git_log` so the reviewer can walk the source itself instead of reasoning from a paraphrase (PR-1.5 tool surface). Receipts land in `execution_logs` and the Mission narrative. Fires automatically before commits touching public surface (CLI subcommands, Tauri commands, MCP tools, schema migrations, security boundaries) or whenever a diff exceeds ~50 LOC of behavior change.

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Identifies differential m6A methylation between conditions from MeRIP-seq paired IP/input data using exomePeak2 (GC-bias-aware differential via its bam_ip/bam_input control + bam_treated_ip/bam_treated_input treatment arms), QNB beta-binomial, MeTDiff HMM, and RADAR, plus the paired-symmetric edgeR/DESeq2-on-peak-counts route when batch/lot covariates need fixed-effect handling that exomePeak2's API does not accept. Covers paired vs unpaired vs interaction designs, batch confounding and per-lot meta-analysis, the stoichiometry-vs-expression-vs-IP-efficiency confound, and effect-size filtering against under-powered N=2 designs. Use when comparing m6A across two or more conditions, choosing between exomePeak2/QNB/RADAR/MeTDiff for a design, handling batch confounding when exomePeak2's API is too rigid, distinguishing real hyper/hypo-methylation from expression shifts, applying effect-size thresholds, or planning orthogonal stoichiometry validation (GLORI/SAC-seq/m6Anet mod_ratio).

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Geração de imagens com tecnologia de ponta usando Stable Diffusion via HuggingFace Diffusers. Use quando gerar imagens a partir de prompts em texto, realizar tradução de imagem para imagem, inpainting ou construir pipelines de difusão customizados.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Install or synchronize BMS差分 from a beatoraja-compatible difficulty table, optionally download missing parent songs, and place charts into matching music folders without overwriting existing files. Use for 難易度表 URL, header.json, url_diff, or beatoraja差分 installation requests; do not use for ordinary BMS library organization unrelated to a difficulty table.

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当 AI 改完代码、要决定这份 diff 放不放行时使用。不逐行精读，按四步走查高风险点——意图是否匹配、有没有碰到边界条件、副作用面有多大、能不能回滚——每步有明确的放过与打回判据。改动文件数、增删行数、动到的迁移/锁文件/CI/配置/鉴权/测试文件和危险 hunk 先由 scripts/diff_risk.py 统计（粘贴进来的 diff 文本也能读，不需要 Git），越过固定阈值时必须人工逐段过。只有口头描述、没有改动内容时不给结论，只列要补的材料。diff 里新写的测试可不可信交给 ai-generated-test-auditor；没有基线的整段新代码走 ai-code-onboarding-checklist。

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PR・ブランチの変更差分（git diff）を静的解析してセキュリティ脆弱性を検出する。開発中・PRレビュー時に使用。手動呼び出し専用: /sec-diff-review

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

提供在WinForms中通过ElementHost嵌入DiffPlex的WPF DiffViewer控件，实现两个字符串的对比及差异高亮显示的代码方案。

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.