'clean' 검색 결과

Download genome assemblies, gene records, and ortholog data from NCBI using the modern Datasets v2 CLI (replaces assembly_summary.txt scraping and many EFetch workflows). Use when bulk-pulling genome assemblies, gene metadata across species, ortholog sets, or BLAST databases; when E-utilities are too slow for genome-scale work; or when automatic checksum verification, parallel download, and clean accession-driven retrieval are required. Encodes the JSON-lines output format, dataformat conversion, --dehydrated for cloud workflows, and when Datasets is/isn't the right tool.

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Trim multiple sequence alignments using ClipKIT, trimAl, BMGE, Divvier, or HMMcleaner with mode selection guidance per downstream goal. Use when removing unreliable columns or contaminating residues before phylogenetic inference, HMM building, or selection analysis.

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集群数据管理 Skill —— 涵盖数据使用规范、压缩优化、数据共享（ACL）、文件扫描与清理、文件完整性校验、genozip 基因组压缩等全流程。Use when the user asks about: managing data on the HPC cluster, compressing genomic files (fq/bam/vcf), sharing data between users/groups, scanning for large files or cleaning up disk space, checking file integrity (md5/gzip/bam), using genozip, checking disk quota, or any data lifecycle management task on the NCPGR HPC cluster.

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Use when introducing a feature flag system, choosing between release flags / experiment flags / operational flags / kill switches / permission flags, designing percentage rollouts, building kill-switch + circuit-breaker patterns, structuring evaluation contexts (user IDs, plan tier, region), or building flag-cleanup discipline. Triggers: LaunchDarkly / GrowthBook / Unleash / Flagsmith / OpenFeature, percentage ramp, sticky bucketing, kill switch wired to alerting, "we still have flags from 2 years ago", flag debt, OpenFeature provider, evaluation context, default value on provider failure. NOT for A/B test statistical analysis (separate skill), traffic-split routing at the edge, build-time bundler defines, or environment-based config.

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Manage DAG execution lifecycles including start, stop, pause, resume, and cleanup. Activate on 'execution lifecycle', 'stop execution', 'abort DAG', 'graceful shutdown', 'kill process'. NOT for cost estimation, DAG building, or skill selection.

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Practical incident-response runbook for a suspected or confirmed ComfyUI / GPU-daemon compromise. Triage, scope, contain, forensic collection, weight-integrity verification, rebuild from clean snapshot, postmortem. NOT for hygiene scans on a healthy box (use supply-chain-defense-for-ml-extensions), and NOT for runtime hardening of a fresh deployment (use gpu-hosted-asset-hardening).

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Author a pull request an AI coding agent can actually get merged: a scoped, coherent diff; a Summary and Test Plan backed by real evidence; correct triage of required-and-blocking CI gates versus external/advisory checks (e.g. a Cloudflare Pages preview build); draft-while-WIP discipline; named fixup commits for real review findings; and a clean landing through a merge queue without force-pushing or bypassing branch protection. Use when opening, updating, triaging red CI on, or landing an agent-authored GitHub PR. NOT for this repo's internal release ceremony, actor embodiments, or contributor mirror-sync mechanics (use port-daddy-internal-dev), tracking backlog/issue lifecycle across a board (use agent-issue-tracker-workflow), or deciding what to build next / sequencing a roadmap (use legible-roadmap-with-sidequests).

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The standing order for local git state in every AI Matrx repo — zero worktrees, zero local branches, zero dirty files, zero open PRs, everything merged to origin/main, and no code ever lost. Use when you find a worktree, a local branch, a stale checkout, an unpushed commit, or a dirty tree in any repo under /Users/armanisadeghi/code, when asked to "clean up", "unify", "merge everything", or when you are tempted to create a worktree or branch. Works without any access to Arman.

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Lean, sharp UI posture — the everyday default for building or redesigning a UI. Use when asked to build or make a page, panel, list, form, or dashboard good, cleaner, or nicer, or for a fast confident refresh where the agent uses its judgment instead of asking for a spec.

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Find and identify the CCSGameRules_ResetRound function in CS2 server binary using IDA Pro MCP. Use this skill when reverse engineering CS2 server.dll or libserver.so to locate the round-reset routine. It is the only function that references the "GMR_ResetRound\n" debug log string, and is the predecessor anchor for find-CCSGameRules_PostCleanUp (which it calls). Emits a unique IDA-style byte signature and a func YAML. Mirrors the find-CCSGameRules_ResetRound.py preprocessor (xref_strings "GMR_ResetRound\n"). Trigger: CCSGameRules_ResetRound, ResetRound, GMR_ResetRound

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このマシンに溜まった Claude Code の履歴・痕跡・キャッシュを，何を消すか列挙して承認を得たうえで消し，ログイン・設定・導入済みプラグインは残す．「Claude Code の履歴を消して」「痕跡を掃除して」など，Claude Code がローカルに残したものの削除を明示的に求められたときだけ使う——「クリーンアップして」等の一般の整理の依頼では発動しない．実行中ジョブのログを見たいだけなら /ops:progress を使う．

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This skill should be used when the user asks to "既存プロジェクトのタスクを整理して", "技術的負債をIssue化して", "このコードベースを改善するタスクを洗い出して", "GitHub Projectに健全化タスクを登録して", "break down what needs to be fixed in this project", "surface tech debt as issues", or "create a project board for cleanup work". Diagnoses pain points and codebase health of an existing project, then registers improvement tasks as GitHub Issues and a Project Board.

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AndroidおよびKotlin Multiplatformプロジェクトのためのクリーンアーキテクチャパターン — モジュール構成、依存関係ルール、UseCase、Repository、データレイヤーパターン

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Vets third-party skills, plugins, MCP servers, GitHub Actions and model weights before install, with a verdict (PASS, CONDITIONAL, HOLD, FAIL) and install terms. Trigger on any should-I-install question, even with its files or hooks pasted in or a scan already clean; is this skill safe, vet this MCP server, check this GitHub Action, is this checkpoint safe or commercially usable, what does this installer write, a licence check before a fold-in, what changed in a plugin update; or say trustwarden (vet, revet, terms, refresh). Uses skillspector, zizmor, pinact and Scorecard when present; lists files no scanner read. Runtime permissions are gatewarden's; secrets shieldwarden's; your own skills skillwright's; sandboxing a download hypervrunner's.

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Writes and cleans up messages and docs for their channel and reader (email, Slack, a text, release notes, store pages, READMEs, Claude Docs) in a plain voice that never moves a fact. Trigger to write, rewrite, shorten, line-edit, retell or change the tone of any message, even a two-line text; to strip dashes or AI tells; to fix UI wording (a dialog, button or error); to score text without rewriting; to plan release comms; to write a store page, launch post or listing title, blurb and tags; to write in a voice or learn one; or say commscribe (draft, reshape, humanize, audit, retell, formats, cadence, voice, docs). It never sends. A skill's own files (SKILL.md, references) are skillwright's; brand voice and layout brandscribe's; sourced write-ups researchscribe's.

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Elite website image-to-code skill for Codex. For visually important web tasks, it must first generate the design image(s) itself, deeply analyze them, then implement the website to match them as closely as possible. In Codex, it must prefer large, readable, section-specific images instead of tiny compressed boards, generate fresh standalone images for sections or detail views instead of cropping old ones, avoid lazy under-generation, avoid cards-inside-cards-inside-cards UI, and keep the hero clean, spacious, readable, and visible on a small laptop.

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Clean editorial-style interfaces. Warm monochrome palette, typographic contrast, flat bento grids, muted pastels. No gradients, no heavy shadows.

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Overrides default LLM truncation behavior. Enforces complete code generation, bans placeholder patterns, and handles token-limit splits cleanly. Apply to any task requiring exhaustive, unabridged output.

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[71] CLOSE. Quick, safe cleanup after completing a milestone. Fix objective issues only (syntax errors, dead code, poor naming). Must be <5% of main task time, <30 seconds per fix, and reversible. Use after key points, not after every small change.

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[52] EXECUTE. Three-stage refactoring workflow: (1) iterative research of refactor/modularization options, (2) plan + risk/edge-case analysis + Scope150 validation, then implement with tests after user confirmation, and (3) apply Scout105 cleanup protocol. Use when asked to refactor, modularize, or restructure code safely.

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Create platform-native content systems for X, LinkedIn, TikTok, YouTube, newsletters, and repurposed multi-platform campaigns. Use when the user wants social posts, threads, scripts, content calendars, or one source asset adapted cleanly across platforms.

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A hard-edged writing style contract for timeless, forceful English prose without modern AI tics. Use when users ask for prose or rewrites that must be clean, exact, concrete, and free of AI cadence, filler, or therapeutic tone.

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Build production-grade Azure Cosmos DB NoSQL services following clean code, security best practices, and TDD principles.

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Master proven backend architecture patterns including Clean Architecture, Hexagonal Architecture, and Domain-Driven Design to build maintainable, testable, and scalable systems.

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