「bulk」の検索結果

Import a large archive into the vault in controlled batches: triage what is worth ingesting, process oldest first, checkpoint after every batch, and keep cost visible. Use this skill whenever the user wants to import years of bookmarks, an export from another notes app, a downloads folder, a chat history dump, or says "backfill", "bulk import", "process my archive". Do NOT use for ingesting one or a few new sources, which is second-brain-ingest.

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。

Audit a second-brain vault for structural problems and repair them: broken wikilinks, orphan pages, empty stubs, frontmatter that violates the schema, near-duplicate pages, and stale index entries. Use this skill whenever the user asks to lint, clean, audit or check the health of their vault, says pages feel messy or links are broken, after a large bulk import, or when a scheduled maintenance run fires. Do NOT use for ingesting new sources, for answering questions from the vault, or for rewriting page content that is structurally fine but reads badly.

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。

Writing and executing C# scripts and macros against Power BI semantic models using Tabular Editor 2/3. Automatically invoke when the user mentions "C# script", "Tabular Editor script", "TOM scripting", "MacroActions.json", "XMLA", or asks to "automate model changes", "bulk update measures", "create calculation groups", "write a macro", "format DAX expressions", "manage model metadata".

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 importing FBX, USD, OBJ or glTF from Maya, ZBrush or Blender into Unreal Engine 5.8 in bulk or reimporting changed files, writing Editor Python tools, Interchange pipelines or import presets, enforcing naming conventions, assigning material instances by script, setting Nanite, collision and LODs per asset class, writing data validators or automation tests, fixing redirectors, or cooking and packaging from the command line (BuildCookRun, RunUAT, CI, Perforce). Also when a scripted import ignores its settings or names, a Python validator never runs, or a Mac build will not package.

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。

Improve an open-source GitHub skill and open a friendly suggestion PR upstream: fork, run skill-creator's retrofit, attach asm eval before/after metrics. Don't use for local-only skills, authoring from scratch, bulk repos, or registry publish.

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。

Linear expert for workspace/team admin, Cycles, Projects, Initiatives, Roadmaps, GraphQL API queries, triage workflows, GitHub integration, bulk operations, and Jira-to-Linear migration.

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。

Microsoft 365 tenant administration for Global Administrators. Use for tenant setup, Azure AD user management, Exchange Online and Teams config, Conditional Access policies, license management, and PowerShell bulk-operation scripts.

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。

This skill should be used when the user asks to "batch LLM requests", "should I use the batch API", "estimate batch vs realtime cost", "design a bulk LLM job", or "process thousands of prompts cheaply".

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。

Discover existing cloud resources using Terraform Search queries and bulk import them into Terraform management. Use when bringing unmanaged infrastructure under Terraform control, auditing cloud resources, or migrating to IaC.

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 fable-mode execution discipline on Claude Haiku. Routes the task to the @fable-worker-haiku agent, whose definition carries the staged loop with tightened verification (no bare "unverified" allowed) and an escalate-don't-improvise rule. Trigger when the user explicitly asks for thorough/systematic handling run cheaply or fast ("fable on haiku", "deep work mode but cheap", "stage this on haiku"). For bulk mechanical work. Do NOT use for tasks needing synthesis — benchmark note: at n=1 the skill's effect on Haiku swung both directions (+25 / −17); route quality-critical work to fable-sonnet instead.

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 fable-mode execution discipline on Claude Fable 5.1 — the top of the escalation ladder and the strongest staged run available. Routes the task to the @fable-orchestrator agent with its model overridden to Fable (`model: "fable"`), which stages the work, delegates artifact production to @fable-worker-sonnet / @fable-worker-haiku, and cold-checks deliverables with @fable-verifier. Trigger when the user explicitly asks for thorough/systematic/"deep work" handling on the strongest model ("fable on fable", "stage this on fable", "deep work mode, fable", "run this on 5.1"), or when a fable-opus run reports the task exceeds Opus's ceiling. Benchmarked 2026-09-02: zero correctness delta on Fable 5.1 at ~1.1× tokens, ~2× wall — a provenance runner, not an accuracy runner. Do NOT use for ordinary single-pass tasks — prefer fable-opus, fable-sonnet, or fable-haiku when the task doesn't need peak reasoning. Fable is plan-included; bulk work still routes down-tier.

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。

Edit, query, and transform Word documents (.docx) with the SuperDoc CLI. Use when the user asks to read, search, modify, format, comment, track changes, or review changes in .docx files. Triggers on any task involving Word documents — text replacement, redlining, contract markup, template filling, bulk edits, content extraction, or document review.

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。

When the user wants help with paid advertising campaigns on Google Ads, Meta (Facebook/Instagram), LinkedIn, Twitter/X, or other ad platforms. Also use when the user mentions 'PPC,' 'paid media,' 'ROAS,' 'CPA,' 'ad campaign,' 'retargeting,' or 'audience targeting.' This skill covers campaign strategy, audience targeting, and optimization. For bulk ad creative generation and iteration, see ad-creative.

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。

When the user wants to generate, iterate, or scale ad creative — headlines, descriptions, primary text, or full ad variations — for any paid advertising platform. Also use when the user mentions 'ad copy variations,' 'ad creative,' 'generate headlines,' 'RSA headlines,' 'bulk ad copy,' 'ad iterations,' 'creative testing,' or 'ad performance optimization.' This skill covers generating ad creative at scale, iterating based on performance data, and enforcing platform character limits. For campaign strategy and targeting, see paid-ads. For landing page copy, see copywriting.

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。

Audits skills in this repo for consistency, API drift, and structural gaps. Produces a prioritized report grouped by severity (Critical/High/Medium/Low). Use when asked to "audit skills", "check the skill repo for drift", or when planning bulk skill cleanup. Read-only — does not apply fixes.

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。

SimBu can be used to simulate bulk RNA-seq datasets with known cell type fractions. You can either use your own single-cell study for the simulation or the sfaira database. Different pre-defined simulation scenarios exist, as are options to run custom simulations. Additionally, expression values can be adapted by adding an mRNA bias, which produces more biologically relevant simulations.

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。

granulator is an R package for the cell type deconvolution of heterogeneous tissues based on bulk RNA-seq data or single cell RNA-seq expression profiles. The package provides a unified testing interface to rapidly run and benchmark multiple state-of-the-art deconvolution methods. Data for the deconvolution of peripheral blood mononuclear cells (PBMCs) into individual immune cell types is provided as well.

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。

Methods to infer clonal tree configuration for a population of cells using single-cell RNA-seq data (scRNA-seq), and possibly other data modalities. Methods are also provided to assign cells to inferred clones and explore differences in gene expression between clones. These methods can flexibly integrate information from imperfect clonal trees inferred based on bulk exome-seq data, and sparse variant alleles expressed in scRNA-seq data. A flexible beta-binomial error model that accounts for stoc

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。

Expert knowledge for Azure Health Data Services development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when using FHIR/DICOM APIs, bulk import/export, de-identification, events, or Synapse/Data Lake integrations, and other Azure Health Data Services related development tasks. Not for Azure Health Bot (use azure-health-bot), Azure Data Manager for Agriculture (use azure-data-manager-for-agri), Azure Energy Data Services (use azure-energy-data-services).

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。

Friday bulk football matchday simulations on MiroShark - pay $1 USDC per sim via x402 (Finance District agent wallet), launch Premier League, Serie A, and La Liga matchday sims in parallel, collect share links and full reports, and render or hand off one video per sim.

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。

Programmatic inbox management for Smartlead. Enable/disable warmup with correct ramp settings, set signatures in bulk, tag inboxes (active vs insurance), and pull inbox health dashboards. Use after creating a new batch of inboxes via /zapmail-domain-setup-public, or when managing an existing Smartlead account at scale. Triggers on "turn on warmup", "set signatures", "tag inboxes", "inbox health", "set up new inboxes".

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。

Add full internationalization (i18n) to a Next.js project using next-intl. Supports 14+ languages, SEO-friendly locale routing, hreflang sitemaps, and bulk translation. Use when the user asks to "internationalize", "add i18n", "add translations", "multi-language", "localize", "add language support", or "translate my site".

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。

Perform bulk code refactoring operations like renaming variables/functions across files, replacing patterns, and updating API calls. Use when users request renaming identifiers, replacing deprecated code patterns, updating method calls, or making consistent changes across multiple locations.

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。

Detect and investigate bulk registration abuse on SaaS platforms. Given access to a user database (or exported CSV/JSON), run a multi-dimensional anomaly analysis — email domain clustering, registration tempo, UA fingerprinting, session structure, usage patterns, and credit consumption — to produce a scored abuse report with actionable recommendations. Use when investigating suspicious sign-up spikes, credit fraud, free-tier abuse, or account farming.

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。