976 件 ・ 関連度順
概要と使いどころ
Comprehensive REST API design review with automated linting, breaking-change detection, and design scorecards. Catches inconsistent conventions, missing versioning, and design smells before APIs ship. Use when reviewing a PR that adds or changes API endpoints, auditing an existing API for v2 migration, or establishing API standards for a team.
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。
Code review through the lens of real engineers' documented philosophies (Torvalds, Thompson, Carmack, Kent Beck, Jobs, Cagan). Complements abstract-role adversarial review with named, sourced perspectives. Use when automated review findings feel generic, when a PR has architectural or UX impact, or when the author wants pre-submit hardening beyond standard checks.
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。
Critical-path smoke gate before QA hand-off — runs the automated suite. A failed check means the build is not QA-ready.
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。
QA test plan for a sprint — classifies stories by Logic/Integration/Visual/UI, covers automated tests, manual cases, smoke scope.
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 OpenWork inference model aliases, openwork model overlays, discounts, validation, and automated base model refreshes from models.dev. Use when adding, removing, discounting, auditing, or updating OpenWork models, including requests like "update the models" that should trigger the GitHub update-models workflow and report when its PR merges.
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。
Hummingbot trading bot framework - automated trading strategies, market making, arbitrage, connectors for crypto exchanges. Use when working with algorithmic trading, crypto trading bots, or exchange 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。
Validate the staging NemoClaw Brev Launchable through its web journey or a deployed environment. Use for advisory validation outside automated E2E.
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。
Publish or update a NemoClaw pull request and follow its CI and automated reviews to completion.
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。
Identify repeated work from recorded activity or starred examples and assess which steps could be automated.
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。
Remediates Google Cloud Security Command Center findings, including IAM permission fixes, cloud resource misconfigurations, vulnerabilities, and Toxic Combinations. Use when asked to fix, remediate, or mitigate a Security Command Center finding or address attack paths. Don't use for general IAM policy querying without a Security Command Center finding. For runtime threat detections, this skill provides containment and investigation guidance rather than automated configuration 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。
Inspects Filestore capacity and utilization on Google Cloud, evaluates storage scaling rules, and performs capacity autoscaling (scale UP for low free space or scale DOWN for cost optimization). Use when monitoring Filestore instance headroom, resizing instance shares, configuring automated growth/shrink thresholds (custom thresholds apply globally across projects in session memory), or preventing out-of-space outages. Don't use for Cloud Storage (GCS) buckets, Persistent Disk block storage, or NetApp Volumes.
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。
Manages clusters, instances, and backups for AlloyDB for PostgreSQL, and integrates with AlloyDB Model Context Protocol (MCP) tools for automated database operations. Use when creating, configuring, or administering AlloyDB databases. Do NOT use for general PostgreSQL instances (e.g. Cloud SQL) or other GCP databases.
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。
Test LangBot WebUI and core product flows with an automated browser and backend logs. Use when validating the configured LangBot frontend, pipeline Debug Chat, model provider setup and test buttons, bot and knowledge-base UI flows, or troubleshooting failed LangBot end-to-end tests.
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。
Develop, debug, and test LangBot plugins. Use when creating new LangBot plugins, fixing plugin bugs, setting up a LangBot test environment, or testing plugins via WebSocket. Covers plugin component architecture (EventListener, Command, Tool), the plugin SDK API (invoke_llm, get_llm_models, send_message, plugin storage), common pitfalls, and automated WebSocket-based testing. Triggers on "langbot plugin", "lbp", "GroupChatSummary", "plugin debug", "langbot 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。
This skill should be used for advanced LLM evaluation: LLM-as-judge systems, direct scoring, pairwise comparison, rubric calibration, evaluator bias mitigation, confidence scoring, and automated quality assessment.
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。
Periodically check WandB metrics during training to catch problems early (NaN, loss divergence, idle GPUs). Avoids wasting GPU hours on broken runs. Use when training is running and you want automated health checks.
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。
Automatically creates user-facing changelogs from git commits by analyzing commit history, categorizing changes, and transforming technical commits into clear, customer-friendly release notes. Turns hours of manual changelog writing into minutes of automated 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。
Automated PR review and CI auto-fix for GitHub and GitLab using the Composio CLI. Pulls diffs, fetches failing job logs, posts review comments, and loops fix commits until checks go green.
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。
Automatically organizes invoices and receipts for tax preparation by reading messy files, extracting key information, renaming them consistently, and sorting them into logical folders. Turns hours of manual bookkeeping into minutes of automated organization.
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。
Automated code review for pull requests using multiple specialized agents
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。
Provides guidance for automatically evolving and optimizing AI agents across any domain using LLM-driven evolution algorithms. Use when building self-improving agents, optimizing agent prompts and skills against benchmarks, or implementing automated agent evaluation loops.
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 when the user wants to build tool/scripts or achieve a task where using data from the Hugging Face API would help. This is especially useful when chaining or combining API calls or the task will be repeated/automated. This Skill creates a reusable script to fetch, enrich or process data.
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。
Fallback workflow for reliable file creation and verification when automated code execution fails
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。
Fallback workflow for code execution when automated tools fail, using shell heredoc with verification
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。