1,277 件 ・ 関連度順
概要と使いどころ
Audit skillsaw for release readiness — test new rules against real repositories, audit core architectural dimensions, independently verify proposed fixes, and ship improvements in clean, focused batches. Use before cutting a release.
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。
Optimize AgentDB with quantization, HNSW tuning, caching, batch ops, and pruning.
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。
Optimize AgentDB performance with quantization (4-32x memory reduction), HNSW indexing (150x faster search), caching, and batch operations. Use when optimizing memory usage, improving search speed, or scaling to millions of vectors.
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。
Grooms a GitHub milestone for parallel execution — batch-grooms ungroomed items, assesses scope gaps, analyzes cross-item dependencies via Impact Radius overlap, builds conflict groups, assigns items to execution waves, and persists the dispatch plan via dispatch_create_plan MCP tool. Calls dispatch_wave_start per wave to register state. Use when preparing a milestone for /work-milestone execution. Pass the milestone number as the first argument. Requires milestone items assigned via /group-items-to-milestone.
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。
Dasel v3 query patterns for Hibernate .hbm.xml mapping files — entity-table binding, Java property-to-column extraction, one-to-many set/list/bag relationship tracing, many-to-one foreign key discovery, batch scanning across 60+ HBM files. Use when querying Hibernate ORM class mappings, extracting schema metadata from Java persistence layer, or auditing entity-column relationships in enterprise legacy codebases.
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 modifying, converting, or transforming structured data with dasel v3 — in-place mutations, format conversion, batch operations, array manipulation, object construction, and merge patterns across JSON, YAML, TOML, XML, CSV, HCL, INI
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。
Convert Chinese provinces, municipalities, autonomous regions, cities, counties, ancient cities, and cultural regions into restrained contemporary posters led by one culturally transformed Chinese character. Supports direct one-shot final image generation and layered production. Use when the user asks for a 中国省域文化海报、城市文化海报、地域文化视觉、极简大字海报、地区系列海报、展览主视觉、出版或社交封面，requests 直接生成、一次成图、不合成、不要后期、direct generation, or wants cultural analysis, art direction, image prompts, rendered poster images, or a coherent batch series for places such as 北京、广东、福建、江南、岭南、巴蜀 or 关中.
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。
Create, schedule, duplicate, inspect, cancel, archive, and troubleshoot Vapi outbound Campaigns. Use for persistent multi-contact calling, CSV or API contact personalization, campaign concurrency, campaign webhooks, pre-dial eligibility, contact outcomes, or rerunning an audience. Do not use for a single call or a simple one-off /call batch.
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。
Create one-off outbound phone calls, web calls, scheduled calls, and simple batch calls using the Vapi API. Use when making or testing individual calls or initiating a bounded /call request programmatically. Use create-campaign for a persistent multi-contact Campaign with lifecycle, reporting, cancellation, duplication, or campaign webhooks.
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。
Manage Alibaba Cloud DNS (Alidns) using the @alicloud/alidns20150109 TypeScript SDK. Use when working with DNS resolution on Alibaba Cloud, including domain management, DNS record CRUD (A, AAAA, CNAME, MX, TXT, SRV, CAA, etc.), DNS load balancing (DNSSLB), custom resolution lines, DNSSEC, domain groups, batch operations, Cloud GTM (Global Traffic Manager), DNS GTM, GTM Classic, recursive DNS, DNS cache, Public DNS (PDNS), DNS over HTTPS (DoH), ISP cache flush, domain statistics, and resource tagging. Covers all 234 APIs of the Alidns 20150109 version.
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。
Codified expertise for production scheduling, job sequencing, line balancing, changeover optimization, and bottleneck resolution in discrete and batch manufacturing. Informed by production schedulers with 15+ years experience. Includes TOC/drum-buffer-rope, SMED, OEE analysis, disruption response frameworks, and ERP/MES interaction patterns. Use when scheduling production, resolving bottlenecks, optimizing changeovers, responding to disruptions, or balancing manufacturing lines.
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。
Advises on setting up LLM-based text classification as a validated measurement design. Covers codebook construction, learning-regime and model choice, prompt construction, validation against human coding with kappa and F1, hybrid human-LLM review, downstream measurement error, and reporting, plus a short resumable batch pattern with a rule-based baseline for repeated free text against a closed codebook. Use when the user wants to classify, code, or label text at scale. Category discovery goes to topic-modeling.
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。
Advises on setting up and validating LLM text classification: codebook, learning regime and model choice, prompts, validation against human coding (kappa, F1), hybrid review, measurement error, and reporting, plus a short resumable batch pattern with a rule-based baseline. Use to classify, code, or label text at scale; category discovery goes to topic-modeling.
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。
Value investing analysis using Graham (NCAV/net-net/defensive-investor) and Buffett (economic moat/ROE/FCF) methodologies. Covers single-stock diagnostics and batch screening for both Graham cigar-butt and Buffett quality-compounder criteria. Runs cross-statement reconciliation before scoring. Data from Longbridge CLI first, MCP fallback, WebSearch only for genuine gaps. Triggers: "格雷厄姆", "巴菲特", "捡烟蒂", "烟蒂股", "NCAV", "净流动资产", "护城河", "价值投资", "安全边际", "深度价值", "撿煙蒂", "煙蒂股", "淨流動資產", "護城河", "安全邊際", "Graham", "Buffett", "cigar butt", "net-net", "NCAV screen", "moat", "value investing", "margin of safety", "deep value", "quality compounder", "價值投資", "深度價值", "防御型投资者", "防禦型投資者"
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。
Optimize AgentDB performance with quantization (4-32x memory reduction), HNSW indexing (150x faster search), caching, and batch operations. Use when optimizing memory usage, improving search speed, or scaling to millions of vectors.
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。
Analyze issues to identify the next work item and update focus.md. Enforces issue-first workflow and confidence-based batch limits.
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 operating ProjectClownfish cluster workflows in this repo: reviewing GitHub Actions run artifacts, tuning worker/applicator guardrails, importing ghcrawl clusters, dispatching canaries, scaling batches, or deciding whether autonomous write-mode cluster cleanup is safe to ramp.
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 wants to run a diffusers pipeline from a terminal (one-off generation, batch jobs, smoke-testing a new model), run on HF Sandbox hardware via `--remote`, introspect a pipeline's input schema before calling it, or attach a LoRA at inference time. Prefer this over writing ad-hoc Python scripts for generation tasks.
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。
Evaluate an open source project's AGENTS.md and produce a corpus entry for the /agents-md directory. Use when adding a project to the directory, refreshing an existing entry, or running a batch of candidate repositories.
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 designing UI with OpenPencil — creating layouts via op CLI, batch design DSL, sandboxed JS scripts, or MCP tools. Covers PenNode schema, semantic roles, typography, color, spacing, and common component patterns.
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。
YouTube Marketing MCP — 21-command suite for YouTube creators. Covers SEO, scripts, hooks, thumbnails, analytics, content calendar, Shorts, batch updates, WordPress publishing, and plugin demo workflows. Triggers on any /youtube command or YouTube-related marketing request. Always pull live data before generating recommendations.
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。
Generate, rank, and gate a reusable hook bank — sourced pains × named hook formula families, scored on clarity/specificity/curiosity/proof-backing, gated at the 10/16 ad threshold, delivered in 3 lengths with per-hook provenance and downstream routing. Use when "hook bank", "generate hooks", "hook generator", "write hooks for", "ad hooks", "scroll stoppers", "opening lines", "hook ideas", "first 3 seconds", "hook matrix", "I need 50 hooks", or any request to batch-produce attention-openers for ads, social, or video.
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。
Plan and batch-produce an entire email system for a product. Maps every lifecycle touchpoint (onboarding, activation, conversion, retention, transactional, win-back), generates all emails with quality gates, outputs Loops-ready copy. Use when "create all emails", "email system", "build email sequences", "lifecycle emails", "onboarding sequence", "set up transactional emails", "plan all the emails for [product]", or any request to systematically produce a complete set of emails for a platform.
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。
Build a complete cold email outreach system — ICP definition, sequence architecture, personalization strategy, and batch-produced email sequences with CAN-SPAM/deliverability compliance. Use when "cold outreach", "cold email sequence", "outbound campaign", "prospecting emails", "sales outreach", "build outreach sequence", or any request to create systematic cold email campaigns for lead generation.
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。