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Containerize an ASP.NET Core project by creating Dockerfile and .dockerfile files customized for the project.

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。

Run the AgentRC readiness assessment on the current repository and produce a static HTML dashboard at reports/index.html. Wraps `npx github:microsoft/agentrc readiness` and hands off rendering to the @ai-readiness-reporter custom agent. Supports policies (--policy) for org-specific scoring. Use when asked to assess, audit, or score the AI readiness of a repo.

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。

Make any repo AI-ready — analyzes your codebase and generates AGENTS.md, copilot-instructions.md, CI workflows, issue templates, and more. Mines your PR review patterns and creates files customized to your stack. USE THIS SKILL when the user asks to "make this repo ai-ready", "set up AI config", or "prepare this repo for AI contributions".

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This skill should be used when the user asks to "create a slash command", "add a command", "write a custom command", "define command arguments", "use command frontmatter", "organize commands", "create command with file references", "interactive command", "use AskUserQuestion in command", or needs guidance on slash command structure, YAML frontmatter fields, dynamic arguments, bash execution in commands, user interaction patterns, or command development best practices for Claude Code.

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Use for the PROVIDER half of getting a locally running CopilotKit Channels agent to answer in Slack, when no Slack app exists yet — setting up a Channels bot in Slack for the first time, creating the Slack app and its tokens, attaching it to a managed Intelligence Channel, or when a Channel reports setup_required, sits at "Waiting for runtime", the Channel is Online but a Slack mention gets no reply, or a Slack app was built with Socket Mode instead of an Intelligence Request URL. Scoped to an OpenTag checkout, or the OpenTag example inside a channels-sdk clone — the phases assume those conventions (app/channel.tsx, app/env.ts, INTELLIGENCE_CHANNEL_NAME, a local agent on port 8123) and do not describe a project scaffolded by copilotkit init, which already ships its own channel host. If the Slack app and Channel already exist and the question is about declaring or customising the Channel in code, use the copilotkit-channels skill instead.

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Use for the CODE half of a managed Intelligence Channel with Slack or Microsoft Teams: customising the Channel a CLI-scaffolded project already ships, or — for a project the CLI did not generate — writing the Channel declaration, the long-running host, and the awaited activation call. Teams provider setup is in scope, because the CLI or dashboard wizard performs it. Creating a Slack app for the first time is not: if no Slack app exists yet, use setup-slack-channel for the provider half and return here for the code.

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。

Locks customer-facing CopilotKit Intelligence docs to one approved name per concept. Use when writing, editing, or reviewing Intelligence docs, nav labels, signup labels, or image alt text in showcase/shell-docs. Don't use for renaming code identifiers, route slugs, env vars, API fields, or component names, or for docs that do not mention Intelligence.

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。

Guide for writing SGLang CI/UT tests. Covers CustomTestCase, CI registration, server fixtures, model selection, mock testing, and test placement. Always read test/README.md for the full CI layout, how to run tests, and extra tips. Use when creating new tests, adding CI test cases, writing unit tests, or when the user asks to add tests for SGLang features.

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。

Zero-shot time series forecasting with Google's TimesFM foundation model. Use this skill when forecasting ANY univariate time series — sales, sensor readings, stock prices, energy demand, patient vitals, weather, or scientific measurements — without training a custom model. Supports both basic forecasting and advanced covariate forecasting (XReg) with dynamic and static exogenous variables. Automatically checks system RAM/GPU before loading the model, validates dataset fit before processing, supports CSV/DataFrame/array inputs, and returns point forecasts with calibrated prediction intervals. Includes a preflight system checker script that MUST be run before first use to verify the machine can load the model and handle your specific dataset.

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Deploy and configure Zeek (formerly Bro) to passively analyze network traffic, generate structured connection/DNS/HTTP/SSL/file logs, detect anomalous behavior, and write custom scripts for organization-specific threats. Use for passive monitoring at network choke points, feeding SIEM/threat hunting with protocol metadata, or retrospective log analysis during incident response; not a substitute for inline IDS/IPS or host agents.

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Configures Fail2ban with custom filters and actions to detect port scanning activity, SSH brute force attempts, and network reconnaissance, automatically banning offending IP addresses and alerting security teams to suspicious network probing.

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。

Detect network reconnaissance and port scanning using Suricata and Snort IDS signatures, threshold-based detection rules, and traffic anomaly analysis to identify Nmap, Masscan, and custom scanning activity.

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。

Detect and block spearphishing emails that use personalized, researched content to evade generic spam filters, by configuring email security gateway (SEG) impersonation protection, URL rewriting, attachment sandboxing, and custom detection rules in Microsoft Defender for Office 365, Proofpoint, Mimecast, or Barracuda. Use when hardening a mail gateway against targeted phishing or investigating a suspected spearphishing campaign.

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Detect Layer 2 ARP poisoning/spoofing by deploying ARPWatch, Dynamic ARP Inspection (DAI), Wireshark packet analysis, and custom Python monitoring scripts that flag gratuitous ARP floods, IP-to-MAC mapping changes, and duplicate IP addresses. Use when investigating suspected man-in-the-middle interception or session hijacking on a local network segment, or when building layer-2 anomaly detection for a SOC.

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Deploys and configures Suricata IDS/IPS with Emerging Threats rulesets, EVE JSON logging, and custom rules for high-throughput, protocol-aware traffic inspection (HTTP, TLS, DNS, SMB) and SIEM integration. Use when running Suricata in IDS or inline IPS mode to detect or block malicious traffic, or when combining signature-based and protocol anomaly detection with file extraction.

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Correlates security events in IBM QRadar SIEM using AQL (Ariel Query Language), custom rules, building blocks, and offense management to detect multi-stage attacks across network, endpoint, and application log sources. Use when SOC analysts need to investigate QRadar offenses, build correlation rules, or tune detection logic for reducing false positives.

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Build structured communication templates for malware incidents (ransomware, wiper, trojan, worm), covering internal stakeholder notifications, executive briefings, technical advisories for IT teams, customer notifications, and regulatory disclosures, with severity-based escalation procedures. Use when drafting or standardizing incident communications and notification workflows for a malware outbreak.

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Conducts security testing of REST, GraphQL, and gRPC APIs to identify vulnerabilities in authentication, authorization, rate limiting, input validation, and business logic. The tester uses the OWASP API Security Top 10 as the testing framework, combining Burp Suite interception with Postman collections and custom scripts to test endpoint security at every privilege level. Activates for requests involving API security testing, REST API pentest, GraphQL security assessment, or API vulnerability testing.

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Analyzes malware C2 communication over HTTP, HTTPS, DNS, and custom protocols to reverse-engineer beacon patterns, command structures, data encoding, and infrastructure (primary servers, fallback domains, dead drops). Use after reverse engineering reveals network traffic needing protocol analysis or when building detection signatures for a framework like Cobalt Strike, Metasploit, or Sliver.

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AI agent payment infrastructure — ACTP escrow, x402 instant payments, USDC settlement on Base L2. Interactive onboarding: asks your preferences, generates customized agent code, and verifies setup. Covers provider/requester patterns, adapter routing, 8-state machine, pricing, disputes, and identity.

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Create professional Marp presentation slides with 7 beautiful themes (default, minimal, colorful, dark, gradient, tech, business). Use when users request slide creation, presentations, or Marp documents. Supports custom themes, image layouts, and "make it look good" requests with automatic quality improvements.

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。

Creating interactive data visualisations using d3.js. This skill should be used when creating custom charts, graphs, network diagrams, geographic visualisations, or any complex SVG-based data visualisation that requires fine-grained control over visual elements, transitions, or interactions. Use this for bespoke visualisations beyond standard charting libraries, whether in React, Vue, Svelte, vanilla JavaScript, or any other environment.

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 memes using the memegen.link API. Use when users request memes, want to add humor to content, or need visual aids for social media. Supports 100+ popular templates with custom text and styling.

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Comprehensive toolkit for product managers including RICE prioritization, customer interview analysis, PRD templates, discovery frameworks, and go-to-market strategies. Use for feature prioritization, user research synthesis, requirement documentation, and product strategy development.

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。