450 件（github のリポジトリ） ・ 人気順
概要と使いどころ
Enforce output quality, evidence verification, and quality gates across security audits. Use this skill when you perform SAST, SCA, threat modeling, or security code reviews. Use this skill to verify code locations and taint traces for all findings. Use this skill to prevent the suppression of valid security findings. Use this skill to evaluate reports against quality thresholds (score ≥ 8/10) before delivery.
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。
Creates, runs, and analyzes Arize experiments for evaluating and comparing model performance. Covers experiment CRUD, exporting runs, comparing results, and evaluation workflows using the ax CLI. Use when the user mentions create experiment, run experiment, compare models, model performance, evaluate AI, experiment results, benchmark, A/B test models, or measure accuracy.
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。
Fetches real-time Azure retail pricing using the Azure Retail Prices API (prices.azure.com) and estimates Copilot Studio agent credit consumption. Use when the user asks about the cost of any Azure service, wants to compare SKU prices, needs pricing data for a cost estimate, mentions Azure pricing, Azure costs, Azure billing, or asks about Copilot Studio pricing, Copilot Credits, or agent usage estimation. Covers compute, storage, networking, databases, AI, Copilot Studio, and all other Azure service families.
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。
Check any AI agent codebase against the OWASP Agentic Security Initiative (ASI) Top 10 risks. Use this skill when: - Evaluating an agent system's security posture before production deployment - Running a compliance check against OWASP ASI 2026 standards - Mapping existing security controls to the 10 agentic risks - Generating a compliance report for security review or audit - Comparing agent framework security features against the standard - Any request like "is my agent OWASP compliant?", "check ASI compliance", or "agentic security audit"
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。
Adds Arize AX tracing to an LLM application for the first time. Follows a two-phase agent-assisted flow to analyze the codebase then implement instrumentation after user confirmation. Use when the user wants to instrument their app, add tracing from scratch, set up LLM observability, integrate OpenTelemetry or openinference, or get started with Arize tracing.
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。
Creates, manages, and queries Arize datasets and examples. Covers dataset CRUD, appending examples, exporting data, and file-based dataset creation using the ax CLI. Use when the user needs test data, evaluation examples, or mentions create dataset, list datasets, export dataset, append examples, dataset version, golden dataset, or test set.
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。
Design and implement Arduino integration with Azure IoT Hub and IoT Edge, including secure provisioning, resilient telemetry, command handling, and production guardrails.
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。
Handles LLM-as-judge evaluation workflows on Arize including creating/updating evaluators, running evaluations on spans or experiments, managing tasks, trigger-run operations, column mapping, and continuous monitoring. Use when the user mentions create evaluator, LLM judge, hallucination, faithfulness, correctness, relevance, run eval, score spans, score experiment, trigger-run, column mapping, continuous monitoring, or improve evaluator prompt.
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。
Creates, reads, updates, and deletes Arize AI integrations that store LLM provider credentials used by evaluators and other Arize features. Supports any LLM provider (e.g. OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, Vertex AI, Gemini, NVIDIA NIM). Use when the user mentions AI integration, LLM provider credentials, create integration, list integrations, update credentials, delete integration, or connecting an LLM provider to Arize.
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 shares ad campaign performance data and asks what to cut, scale, or test. Trigger for prompts like "analyze my ad campaigns", "where am I wasting ad spend", "reallocate my ad budget", "which ads are actually working", or "ROAS analysis". Do not trigger for campaign planning or creative generation without performance 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。
Analyze AWS resources used in the app (IaC files and/or resources in a target account/region) and optimize costs - creating GitHub issues for identified optimizations.
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 Azure Container Registry via the az acr CLI including registries, images, cloud builds, ACR Tasks, authentication, tokens, geo-replication, and networking. Use when working with ACR, az acr commands, pushing/importing/purging container images in Azure, or when the user mentions Azure Container Registry.
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。
Creates and manages annotation configs (categorical, continuous, freeform label schemas) and annotation queues (human review workflows) on Arize. Applies human annotations to project spans via the Python SDK. Use when the user mentions annotation config, annotation queue, label schema, human feedback, bulk annotate spans, update_annotations, labeling queue, annotate record, or human 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。
Find, evaluate, and assemble the smallest compatible set of AI Agent Skills for an end-to-end natural-language goal. Use when a user wants Skills for a multi-step workflow, asks which Skills fit a project, needs an installed-Skill audit or conflict check, has low Skill recall, wants indirect helpers such as humanizers or compliance checks, or wants a project-specific Skill Stack with controlled installation. Search local Skills, registries, GitHub, and OpenCLI; compare adoption, verified fit, safety, and overlap. Do not use for locating one known or common Skill; use the generic find-skills workflow.
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。
Aspire skill covering the Aspire CLI, AppHost orchestration, service discovery, integrations, MCP server, VS Code extension, Dev Containers, GitHub Codespaces, templates, dashboard, and deployment. Use when the user asks to create, run, debug, configure, deploy, or troubleshoot an Aspire distributed application.
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 when asked to edit patch release notes for GitHub Enterprise Server.
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。
Route gh-aw workflow design/create/debug/upgrade requests to the right prompts.
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 creating a Java SDK surface-area E2E integration test backed by a replay proxy YAML snapshot
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。
Conventions for editing Bazel files in the github/codeql repository: the shared `misc/bazel` helpers, `codeql_platform_select` and the `{CODEQL_PLATFORM}` packaging placeholder, adding `MODULE.bazel` dependencies, and the `semmle_code` stub that keeps the standalone build working. Use when editing any `BUILD.bazel`, `*.bzl`, `MODULE.bazel` or `.bazelrc` here, and before validating such an edit.
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。
Maintain model-routing audit golden fixtures and expected outputs.
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。
Design rules for the docs site and landing page (docs/). Use before any visual change there — layout, widths, spacing, colour, typography, header navigation, or new page chrome.
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 a readable six-panel repository statistics infographic from validated JSON, with exact arithmetic and independent raw GitHub/Git reconciliation.
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。
Cross-platform path handling and command 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。
Standard recovery patterns for all squad agents. When something fails, adapt — don't just report the failure.
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。