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「workflows」の検索結果

3,190 件 ・ 関連度順

概要と使いどころ

Set up authorized C2 simulation workflows and measure defensive detection outcomes.

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。

0x-Professor/Agent-Skills-Hub112026年2月27日 更新

Audit and optimize a skill system with evidence. Use for skill architecture, token or context waste, role and prompt boundaries, routing hits or misfires, plugin packaging, registry/docs/source drift, duplicate workflows, or deciding whether a reusable change belongs in a skill. Runs deterministic checks first and applies only authorized, minimal 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。

Dirtytrii/codex-skills112026年10月9日 更新

Operate the WeChat Official Account AI-application workflow for articles, weekly digests, rich formatting, draft-box updates, and local handoff. Use for Agents, MCP, Skills, tool calling, workflows, and open-source AI updates; exclude Xiaohongshu and Xianyu.

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。

Dirtytrii/codex-skills112026年10月9日 更新

Run authorized Xiaohongshu browser workflows for login checks, creator preview fill, publish blockers, final posting, search, export, or approved engagement. Prefer native signed-in Chrome; keep Python/CDP for deterministic batch fallback.

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。

Dirtytrii/codex-skills112026年10月9日 更新

GStack developer-experience review for implemented repositories and workflows, focused on setup friction, command reliability, docs gaps, and maintainability.

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。

Dirtytrii/codex-skills112026年10月9日 更新

GStack land-and-deploy method for explicit landing and deployment workflows with tests, release notes, rollout gates, and rollback planning.

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。

Dirtytrii/codex-skills112026年10月9日 更新

Choose the narrowest reliable browser surface across Codex Browser, signed-in Chrome, Playwright CLI, and platform scripts. Use for browser automation, logged-in workflows, UI inspection, screenshots, form filling, publish previews, or frontend QA.

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。

Dirtytrii/codex-skills112026年10月9日 更新

Rules, conventions, and constraints for formatting git commit messages and committing at logical boundaries. Trigger when: - Drafting, revising, or validating git commit messages. - Pausing at commit boundaries under the CORE or CONTINUE workflows. - Evaluating whether a changeset should be split into multiple commits. - Prompt contains keywords: commit message, git commit, conventional commits, commit hygiene, commit guidelines, logical boundary, spaghetti diff, atomic commit, commit boundary.

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。

nrdxp/predicate102026年9月1日 更新

Add, change, or debug external API integrations, vendor SDK adapters, and bridges to legacy business workflows. Use when an Action or domain service needs an outer technical dependency.

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。

maiobarbero/laravel-boost-ddd102026年9月29日 更新

Create, revise, and validate publication-ready academic paper figures and tables. Use for LaTeX tables, related-work comparison tables, result tables, notation/dataset/taxonomy tables, precise source-data-driven experiment plots from CSV/JSON/logs, generated conceptual figures such as system overviews/pipelines/architectures/threat models, captions, artifact specs, source-data traceability, and paper-ready PDF/SVG/PNG/LaTeX exports. Do not use for prose-only paper writing, self-review, reviewer response, rebuttal drafting, or external literature-management workflows.

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。

DELONG-L/Academic-Paper-Skills102026年10月11日 更新

rupet

無料

Use ruPet as a practical companion for Ruflo and ruvnet tool workflows, or improve ruPet creation and repair prompts. Use for requests that name ruPet or ask for its tool-aware guidance; ordinary tasks and merely displaying the pet do not need this skill.

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。

ruvnet/ruPet102026年10月10日 更新

Audit a codebase or subsystem for architecture simplification - shallow or pass-through modules, scattered concepts, naming drift, sibling workflows that disagree, weak test seams. Use when the user asks what to simplify or restructure. Not for a narrow fix or for implementing an already chosen design.

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。

macintog/codex-spine102026年10月9日 更新

Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations.

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。

Bang-isme/CodexAI---Skills102026年10月5日 更新

Use Exasol document-file virtual schemas for federated read-only access to object and file storage — S3, Google Cloud Storage, Azure Blob Storage, and Azure Data Lake Storage Gen2 document files. Covers document-file adapter family selection, the EDML `MAPPING` definition, `CREATE VIRTUAL SCHEMA` usage, refresh workflows, and query-side troubleshooting.

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。

exasol-labs/exasol-agent-skills102026年10月14日 更新

Use Exasol Cloud Storage Extension workflows for moving structured object-storage files through extension UDFs. Covers setup prerequisites, the fixed `CLOUD_STORAGE_EXTENSION.IMPORT_PATH` and `CLOUD_STORAGE_EXTENSION.EXPORT_PATH` entrypoints used with `FROM SCRIPT` and `INTO SCRIPT`, Parquet, Avro, ORC, and Delta files on S3, Google Cloud Storage, Azure Blob Storage, Azure Data Lake, HDFS, and Alluxio, connection-object credential patterns, and routing away from native IMPORT or EXPORT when the extension path is the right fit.

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。

exasol-labs/exasol-agent-skills102026年10月14日 更新

Use Exasol `EXPORT` and `EXPORT INTO` SQL plus `exapump export` local file workflows for moving data out of Exasol. Covers native CSV/FBV export, local CSV/Parquet exports with exapump, `CREATE CONNECTION` connection objects for export, FTP, SFTP, HTTP, HTTPS, and cloud targets on S3, Azure Blob Storage, and Google Cloud Storage (GCS), reject limits, and export credential 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。

exasol-labs/exasol-agent-skills102026年10月14日 更新

Set up notebook-connector configuration for Exasol AI workflows through the Secrets Python API. Covers secure config store (`scs`) creation, the `AILabConfig` and `StorageBackend` key sources, backend-specific config values such as `db_host_name`, `db_schema`, `storage_backend`, and `huggingface_token`, Python validation, and handoff to downstream notebook-connector 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。

exasol-labs/exasol-agent-skills102026年10月14日 更新

Build, install, validate, and debug custom Exasol virtual schema adapters. Covers source-specific JDBC dialect implementation with `virtual-schema-common-jdbc` including `SqlDialect`, metadata reader behavior, type mapping, and pushdown capabilities, custom document-file adapter code boundaries, custom adapter properties, JAR packaging, BucketFS deployment, adapter script setup, `EXPLAIN VIRTUAL` validation, and adapter-side remote debugging workflows.

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。

exasol-labs/exasol-agent-skills102026年10月14日 更新

convex

無料

Convex is the backend agents get right on the first try: an all-TypeScript reactive platform where the database, server functions, scheduling, file storage, auth, and realtime sync are one type-safe system, every function is a transaction, and `tsc` catches most mistakes before deploy. Ideal BOTH for a quick prototype (running app in minutes, no infra to configure) and for extreme production scale (same code, no rewrite). Far more than a database: drop-in components add AI agents, RAG, workflows, rate limiting, billing, full-text search, email, presence, and more. Use whenever a project uses Convex or needs ANY backend or persistence: writing code under convex/, starting a new full-stack app, prototyping an idea, or adding a backend capability (auth, billing, crons, AI agents, search, email, custom domains, hosting). Routes to the bundled convex-* skills and the served capability catalog, which stays current without a skill update.

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。

waynesutton/agent-ready-component92026年8月28日 更新

Design and build reactive, type-safe, production-grade backends on Convex. Covers schema, queries/mutations/actions, indexes, auth, file storage, scheduling, real-time multiplayer, mobile backends, and LLM/agent workflows on Convex's one-platform stack.

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。

waynesutton/agent-ready-component92026年8月28日 更新

Design and build reactive, type-safe, production-grade backends on Convex. Covers schema, queries/mutations/actions, indexes, auth, file storage, scheduling, real-time multiplayer, mobile backends, and LLM/agent workflows on Convex's one-platform stack.

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。

get-convex/components-submissions-directory92026年10月13日 更新

convex

無料

Convex is the backend agents get right on the first try: an all-TypeScript reactive platform where the database, server functions, scheduling, file storage, auth, and realtime sync are one type-safe system, every function is a transaction, and `tsc` catches most mistakes before deploy. Ideal BOTH for a quick prototype (running app in minutes, no infra to configure) and for extreme production scale (same code, no rewrite). Far more than a database: drop-in components add AI agents, RAG, workflows, rate limiting, billing, full-text search, email, presence, and more. Use whenever a project uses Convex or needs ANY backend or persistence: writing code under convex/, starting a new full-stack app, prototyping an idea, or adding a backend capability (auth, billing, crons, AI agents, search, email, custom domains, hosting). Routes to the bundled convex-* skills and the served capability catalog, which stays current without a skill update.

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。

get-convex/components-submissions-directory92026年10月13日 更新

Scans GitHub Actions workflows and CI/CD pipeline configurations for supply chain attack vectors including unpinned actions, script injection via expressions, dependency confusion, and secrets exposure. Uses PyGithub and YAML parsing for automated audit. Use when hardening CI/CD pipelines or investigating compromised build systems.

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。

andycungkrinx91/konoha92026年10月9日 更新

Build call automation workflows with Azure Communication Services Call Automation Java SDK. Use when implementing IVR systems, call routing, call recording, DTMF recognition, text-to-speech, or AI-powered call flows.

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。

JantonioFC/skillsbank92026年8月4日 更新