322 件 ・ 関連度順
概要と使いどころ
Fine-tune LLMs and VLMs using Unsloth on HF Jobs (Hugging Face on-demand cloud GPUs). Use when users want to fine-tune language models, train VLMs (Vision Language Models), do continued pretraining, domain adaptation, or run UV scripts on HF Jobs. Triggers on requests involving Unsloth training, HF Jobs GPU training, Qwen3-VL fine-tuning, Gemma VLM training, or LoRA fine-tuning on cloud GPUs.
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。
GStack plan-tune method for calibrating how many questions to ask, autonomy level, stop conditions, and decision style for a workstream or user preference.
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。
Komponiert video-synchronisierte Hintergrundmusik aus einem Storyline-JSON per lokaler Waveform-Synthese (numpy + ffmpeg). Stile: Chiptune, Ambient, Electronic. Deterministisch, offline, kein Cloud-Dienst.
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 prepare an OpenAmer-specific fine-tune from the collected brain data: data curation, ChatML JSONL, training, evaluation. 'The organism becomes its own brain'.
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。
Curate Busabase training examples, create immutable dataset snapshots, run reproducible LoRA or QLoRA fine-tunes on a local Apple Silicon Mac with MLX-LM, compare the untouched baseline and adapter on locked evaluations, and register approved adapters. Use when the user wants to train, fine-tune, evaluate, compare, promote, or manage a local language model with Busabase as the workflow source of truth. Do not use for RAG-only knowledge retrieval, cloud training, or training a foundation model from scratch.
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。
How to author, edit, and adapt PostHog Signals scouts — the scheduled agents that scan a project and emit findings into the Signals inbox. Use when a user wants to customize a canonical scout for their own setup (narrow its scope, retune its thresholds, add disqualifiers), tweak a scout's schedule or dry-run posture, or write a brand-new scout from scratch for a specific use case (a custom event, a product surface no canonical scout covers). Covers the scout SKILL.md anatomy, the emit contract, the dedupe + scratchpad-memory conventions, the per-team skills-store path vs the canonical in-repo path, and the emit-and-inspect test loop (with dry-run as an optional safety net). Trigger on "write/edit/customize a signals scout", "new scout for X", "tune my scout schedule", "make a scout that watches <event>".
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。
NVIDIA DGX Spark User Guide リファレンス。GB10 Grace Blackwell Superchip ハードウェア仕様、first-boot / UEFI 設定、Spark Stacking クラスタ、 DGX OS / NGC / container runtime ソフトウェアスタック、 PXE / cloud-init プロビジョニング、fleet lifecycle 運用、 apt / fwupdmgr 更新、system recovery、PSIRT サポート、 vLLM / TensorRT-LLM / Ollama / ComfyUI / NIM / NeMo fine-tune / NCCL 等の build.nvidia.com/spark playbook、複数 Spark 接続・Tailscale・VS Code、 NVIDIA Developer Forums 由来の known issues / troubleshooting。
Self-tuning question sensitivity + developer psychographic for gstack (v1: observational). Review which AskUserQuestion prompts fire across gstack skills, set per-question preferences (never-ask / always-ask / ask-only-for-one-way), inspect the dual-track profile (what you declared vs what your behavior suggests), and enable/disable question tuning. Conversational interface — no CLI syntax required. Use when asked to "tune questions", "stop asking me that", "too many questions", "show my profile", "what questions have I been asked", "show my vibe", "developer profile", or "turn off question tuning". (gstack) Proactively suggest when the user says the same gstack question has come up before, or when they explicitly override a recommendation for the Nth time.
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。
A Vedic astrology (Jyotish) analyzer based on the Indian Jyotish tradition, using the Sidereal zodiac to read birth charts. Covers 27 Nakshatras (Lunar Mansions), the Vimshottari Dasha (Major Period) system, and the Navagraha (Nine Planets). Triggered when users mention "Vedic astrology," "Jyotish," "Vedic," "Nakshatra," "Dasha," or "Indian astrology." Pure LLM reasoning for interpretation (precise charts require an astronomical engine). No external API required. Not applicable for: Western astrology horoscopes, BaZi, tarot, Zi Wei Dou Shu, or other domains → use the fortune-hub router 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。
奇门遁甲排盘分析器，基于洛书九宫四层盘面体系（天盘九星、地盘三奇六仪、人盘八门、神盘八神）， 支持时家奇门排盘，用于择时决策和事项预测。当用户提及「奇门遁甲」「奇门」「遁甲」「择时」 「奇门排盘」「奇门预测」时触发。排盘为确定性计算 + LLM 综合解读，无外部 API 依赖。 不适用于：梅花易数、六爻易经、风水分析、八字命理、塔罗占卜等其他领域 → 建议使用 fortune-hub 路由。
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。
六爻易经占卜器，基于京房纳甲体系，模拟铜钱起卦，完成纳甲装卦（天干地支、世应、六亲、六神）， 通过用神旺衰和生克制化断卦。当用户提及「六爻」「易经占卜」「铜钱起卦」「纳甲」「帮我起一卦」 「六爻预测」时触发。装卦为确定性计算 + LLM 综合断卦，无外部 API 依赖。 不适用于：梅花易数、奇门遁甲、星座运势、塔罗占卜、八字命理等其他领域 → 建议使用 fortune-hub 路由。
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。
风水分析顾问，融合八宅风水和玄空飞星两大理气派体系，通过出生年份计算本命卦， 结合房屋坐向排布飞星盘，给出吉凶方位和空间布局建议。当用户提及「风水」「八宅」 「飞星」「本命卦」「方位布局」「家居风水」「办公室风水」时触发。 计算为确定性公式 + LLM 综合解读，无外部 API 依赖。 不适用于：八字命理、紫微斗数、塔罗占卜、奇门遁甲等其他领域 → 建议使用 fortune-hub 路由。
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 prompts and offer depth / token-budget options BEFORE answering. Use this skill when the user wants to control token usage, tune response depth, choose between short and long answers, or optimize their prompt. Triggers on: "tokens", "token budget", "depth", "consumption", "short vs long answer", "how many tokens", "save tokens", "answer at 50%", "give me the short version", "I want to control how much you use", "tune your response", "presupuesto de tokens", "profundidad", "responde al 50%", "dame la versión corta", or any equivalent phrasing in English or Spanish. If the user wants to control length, detail or depth -- even without mentioning tokens explicitly -- this skill applies.
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。
Self-tuning question sensitivity + developer psychographic for gstack (v1: observational). (gstack)
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。
Read and manage the user's Threads account: profile, posts, feed, saved posts, activity, insights, social graph, search, trends, and a specific post by URL or ID. Can tune feed ranking and publish posts on request.
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。
Health-check the user's Claude Code setup and fix issues: diagnose installation health — what the `claude doctor` terminal diagnostics cover — from local data (duplicate or leftover installs, PATH, unparseable settings files, broken or colliding agent definitions, skills whose frontmatter fails to parse); find unused skills, MCP servers, and plugins versus their context cost and disable dead weight; deduplicate local CLAUDE.md files against checked-in ones; trim checked-in CLAUDE.md files by cutting content a session could derive from the codebase (directory layouts, tech-stack lists, architecture overviews) while keeping gotchas, rationale, and non-standard conventions; migrate always-loaded CLAUDE.md guidance into lazy skills and nested CLAUDE.md files; flag slow hooks and context-heavy extensions; check the installed version is current; make auto mode the default permission mode; and pre-approve frequently denied read-only commands. Use when the user asks for a doctor run, checkup, audit, tune-up, or cleanup of their Claude Code setup or configuration.
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 this skill to search live software / tech / data / engineering job listings across many countries and markets (and remote) via the freehire.me aggregator's public API, or to look up a specific posting. It aggregates roles from ~50 ATS platforms into one schema, so a single skill covers many markets — but its faceted filtering (skills, category, seniority) is tuned tech-first, so scope triggers to technical roles. Trigger phrases: find a tech job, software job search, developer jobs, engineering vacancies, data/ML jobs, DevOps roles, remote developer jobs, "are there any <tech role> jobs in <place>", look up this freehire job posting.
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。
Professional editing of a course that already exists. Use when the user wants to revise, improve, restructure or polish pages the course already has — fix a page, tune a layout, repair a quiz, reword narration, reorder the deck, or raise the quality of the whole course. Not for building a new course from scratch.
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。
Export a promoted fine-tuned model in the right deployment format — merged safetensors, LoRA-only, GGUF with imatrix, or FP8. Use after a checkpoint passes promotion, when choosing a quantization format for a target device, or when an exported model fails its smoke test.
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。
Decide whether to fine-tune at all, and route to the right method (SFT, DPO/ORPO/KTO, GRPO/RLVR, continued pretraining) and base model. Use when starting any fine-tuning effort, when unsure whether RAG or prompting would suffice, or when choosing between preference-optimization and reinforcement methods.
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。
Align a fine-tuned model with preference data using DPO, ORPO, KTO, or SimPO. Use when preference pairs or thumbs-up/down feedback exist, when choosing between preference-optimization methods, or when a DPO run needs hyperparameters or debugging.
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 and improve GitHub Codespaces efficiency. Use this skill when a user wants faster Codespaces startup, lower Codespaces spend, slim devcontainers, right-size machines, tune idle timeout, or scope prebuilds to branches with sustained usage.
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 this skill whenever the user mentions IP geolocation feeds, RFC 8805, geofeeds, or wants help creating, tuning, validating, or publishing a self-published IP geolocation feed in CSV format. Intended user audience is a network operator, ISP, mobile carrier, cloud provider, hosting company, IXP, or satellite provider asking about IP geolocation accuracy, or geofeed authoring best practices. Helps create, refine, and improve CSV-format IP geolocation feeds with opinionated recommendations beyond RFC 8805 compliance. Do NOT use for private or internal IP address management — applies only to publicly routable IP addresses.
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。
Writes and tunes Falco rule syntax for container escape detection - conditions, macros, lists, priorities, and output fields - covering host filesystem mounts, sensitive host path access, kernel module loading, and privileged capability abuse, including how to drive down false positives. Use when authoring or tuning a specific Falco rule for breakout behaviour, or triaging a noisy escape-related Falco alert. Keywords: Falco rule, macro, list, condition, priority, falco_rules.local.yaml, tuning, false positive. Do not use for deploying and operating Falco itself - use detecting-container-runtime-threats-with-falco; for tool-agnostic escape signals use detecting-container-escape-attempts.
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。