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Flag desktop<->den contract drift introduced by this diff. High findings gate Warden clearance; medium findings are advisory only.

日本語の概要は準備中です。原文の説明を表示しています。

Commit, push, branch, and manage version control with GitButler. Use for commits, selective dirty-file or hunk commits, branches, diffs, PRs, history edits, squashes, amends, undo, merge, apply, and unapply. For selected dirty files or hunks, inspect with `but diff`; use compact `but status` for commit order, branch/stack placement, or conflict overview; use `but status -fv` when file/hunk IDs or per-commit file details matter. Replaces git write commands.

日本語の概要は準備中です。原文の説明を表示しています。

Daily competitor-watch loop for {{watch_list}}. Fetches each tracked page, diffs it against the last run's stored snapshot, filters cosmetic edits from meaningful ones, and posts a short summary to {{slack_channel}} — or nothing on a quiet day.

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Workflow 5: orchestrate a text-only resubmit of a polished paper to a different venue under hard constraints (no new experiments, no bib edits, no framework changes, never overwrite prior submissions). Use when user says "resubmit pipeline", "重投流程", "port paper to <new venue>", "resubmit to <venue>", "tighten paper for resubmission", or has a rejected/withdrawn paper to move to a different top venue under tight time budget.

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Automate Diffbot tasks via Rube MCP (Composio). Always search tools first for current schemas.

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Battle-tested PyTorch training recipes for all domains — LLMs, vision, diffusion, medical imaging, protein/drug discovery, spatial omics, genomics. Covers training loops, optimizer selection (AdamW, Muon), LR scheduling, mixed precision, debugging, and systematic experimentation. Use when training or fine-tuning neural networks, debugging loss spikes or OOM, choosing architectures, or optimizing GPU throughput.

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Build and publish a Gradio demo on Hugging Face Spaces for a user-provided LoRA. Use when someone asks to create, generate, ship, or publish a Space, demo, Gradio app, or playground for a LoRA — including LoRAs for Qwen-Image, Qwen-Image-Edit, LTX-Video, Wan, FLUX, SDXL, or other diffusion base models. Also triggers when someone describes a LoRA they trained or hosts on the Hub and wants to share it. Covers picking the right base pipeline and `diffusers` inference recipe, designing a UI tailored to the LoRA's task and inputs (Union/multi-task control, edit, video, image, etc.), respecting model-card recommendations (trigger words, steps, guidance, LoRA scale, example inputs), and shipping to ZeroGPU hardware as a private Space by default.

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Plan and coordinate the deployment of a model to Amazon SageMaker AI. Use this skill whenever the user wants to deploy, host, serve, or expose a model on SageMaker or AWS — including phrases like "deploy a model", "host this LLM on AWS", "serve this embedding model", "deploy a reranker", "deploy a text-to-image / diffusion model", "host this for async inference", "create an endpoint", "serve my fine-tuned model", or any request that involves making a model available for inference on AWS. Use this even when the user is vague (e.g. "I just want to get this running on AWS, you figure it out"). Works for text-generation LLMs, embedding models, rerankers, classifiers, text-to-image / diffusion models — picks the right serving stack and chooses between real-time and async inference. This is the entry-point skill for SageMaker deployment work — it asks clarifying questions, picks a deployment pathway, and coordinates the other deployment skills.

日本語の概要は準備中です。原文の説明を表示しています。

Review a pull request, commit, branch diff, or working-tree patch for security vulnerabilities.

日本語の概要は準備中です。原文の説明を表示しています。

Use for a standard, single-pass security audit of an entire repository or a scoped path, package, folder, or submodule with no diff to review. This is the default repository scan. Do not use for PR, commit, branch, or working-tree diffs, or for deep, multi-pass scans.

日本語の概要は準備中です。原文の説明を表示しています。

Use when the user asks for a deep, exhaustive, multi-pass, or variance-reducing repository-wide or scoped-path Codex Security scan. Run repeated complete independent Standard scans with the Codex Security deep-scan tool, which aggregates their validated findings and prepares the canonical artifacts; then complete the same scan once. Do not use for PRs, commits, branch diffs, or working-tree diffs.

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Shallow (quick) ensemble bug-finding review using 6 specialist agents in parallel. Each specialist reviews the same patch through a different lens: Logic & Types, Boundaries & I/O, Concurrency & State, Resources & Serialization, Absence Analysis, and API Completeness. Findings are merged and deduplicated. Best for: quick first-pass review of patches, triage of diffs, broad surface-level bug scan. For deeper file-focused review with full pattern catalogs and codebase investigation, use the deep-review skill instead.

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Findings-driven targeted code review. Understands the patch via patch-explainer and surrounding code via codebase-analysis, then consults a catalog of bug patterns (~11 categories under references/categories/). Picks only categories whose diff-signals match the patch and items whose "look for" hints match actual code shapes, groups them by review focus (function/file/feature), and spawns parallel subagents — each with a tight scope and selective checklist. Use for medium-to-large patches (50-1000 LOC) as a focused alternative to whole-patch ensemble or whole-file deep review. Triggers on: "review this patch/diff/change", "find bugs in this change", "scoped review", "what could go wrong here", "review using findings", or proactive PR review.

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Draft or submit Apache SeaTunnel pull requests in English using the repository's required title and body conventions. Use when Codex needs to prepare a PR from the current branch or diff, infer a compliant `[Type][Module][SubModule] Description` title, fill the required PR template, describe what changed from git history or file diffs, or open the PR after the user provides or omits the change summary.

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Split one oversized commit or branch into a stack of independently reviewable Graphite (gt) PRs - deciding what genuinely separates, what is atomic and must stay whole, and proving each lower PR builds and passes without the ones above it. Use when asked to "split this PR", "this commit is too big", "break this into a stack", "can we separate this out", or when a diff bundles several concerns across different layers.

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Read-only code quality audit — scan the current working directory for common issues (bugs, dead code, security hotspots, missing error handling) and return a prioritised findings report. No files are edited. Use when asked to "audit the code", "quick audit", "find issues", "code scan", or "what's wrong with this codebase". (munder-difflin)

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Fetch a URL and return a concise markdown summary of its content. Read-only: no files are written; the summary is returned as output only. Use when asked to "fetch and summarize", "summarize this URL", "what does this page say", or "get the content of <url>". Proactively suggest when the user pastes a URL and asks what it contains. (munder-difflin)

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Generate candidate fixes for verified security findings. Consumes TRIAGE.json (preferred), VULN-FINDINGS.json, INCIDENTS.json, or a vuln-pipeline results directory. Pipeline input is delegated to the execution-verified `vuln-pipeline patch` ladder; static-analysis input gets a per-finding patch subagent + independent reviewer and is written as inert diffs for human review. Writes PATCHES/bug_NN/{patch.diff,patch_result.json}, PATCHES.md, and PATCHES.json. Use when asked to "fix the findings", "patch these vulns", "generate fixes", or "close the loop on triage".

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Compares Trailmark code graphs at two source code snapshots (git commits, tags, or directories) to surface security-relevant structural changes. Detects new attack paths, complexity shifts, blast radius growth, taint propagation changes, and privilege boundary modifications that text diffs miss. Use when comparing code between commits or tags, analyzing structural evolution, detecting attack surface growth, reviewing what changed between audit snapshots, or finding security-relevant changes that text diffs miss.

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Runs a Trailmark structural review gate over a branch, pull request, fix commit, release diff, or git ref range to detect new entrypoints, new tainted paths, removed validation or authorization calls, privilege-boundary drift, blast-radius growth, complexity growth, and newly reachable sensitive sinks. Use when reviewing a PR, branch, remediation commit, or release diff where graph-level security regressions should be checked before merge.

日本語の概要は準備中です。原文の説明を表示しています。

Run or plan bulk RNA-seq differential-expression analysis from count matrices with replicate, design formula, contrast, batch, normalization, QC plot, and result-table checks.

日本語の概要は準備中です。原文の説明を表示しています。

Use when the user asks for a deep, exhaustive, multi-pass, or variance-reducing repository-wide or scoped-path Codex Security scan. Run repeated complete independent Standard scans with the Codex Security deep-scan tool, which aggregates their validated findings and prepares the canonical artifacts; then complete the same scan once. Do not use for PRs, commits, branch diffs, or working-tree diffs.

日本語の概要は準備中です。原文の説明を表示しています。

Review a pull request, commit, branch diff, or working-tree patch for security vulnerabilities.

日本語の概要は準備中です。原文の説明を表示しています。

Use for a standard, single-pass security audit of an entire repository or a scoped path, package, folder, or submodule with no diff to review. This is the default repository scan. Do not use for PR, commit, branch, or working-tree diffs, or for deep, multi-pass scans.

日本語の概要は準備中です。原文の説明を表示しています。