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概要と使いどころ
Create agent skills for Microsoft technologies using Learn MCP tools. Use when users want to create a skill that teaches agents about any Microsoft technology, library, framework, or service (Azure, .NET, M365, VS Code, Bicep, etc.). Investigates topics deeply, then generates a hybrid skill storing essential knowledge locally while enabling dynamic deeper investigation.
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 MCP (Model Context Protocol) server configurations for security issues. Use this skill when: - Reviewing .mcp.json files for security risks - Checking MCP server args for hardcoded secrets or shell injection patterns - Validating that MCP package-runner dependencies use exact reviewed versions, not bare names, @latest, or ranges - Detecting mutable npm/npx, bunx, pnpm dlx, yarn dlx, and npm exec references in MCP configurations - Auditing which MCP servers a project registers and whether they're on an approved list - Checking for environment variable usage vs. hardcoded credentials in MCP configs - Any request like "is my MCP config secure?", "audit my MCP servers", or "check .mcp.json" keywords: [mcp, security, audit, secrets, shell-injection, supply-chain, governance]
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。
Security hardening reviewer for GitHub Actions workflow files (.github/workflows/*.yml). Reasons about the Actions threat model that pattern matchers and general code linters miss — untrusted-input script injection, privileged triggers running fork code, mutable action references, and over-scoped tokens. Use this skill when asked to review, audit, harden, or secure a GitHub Actions workflow, when writing a new workflow, or for any request like "is this workflow safe?", "review my CI for security issues", "why is pull_request_target dangerous here?", "pin my actions", or "lock down GITHUB_TOKEN permissions". Covers script injection via ${{ }} interpolation, pull_request_target / workflow_run privilege escalation, SHA-pinning of third-party actions, least-privilege permissions, GITHUB_ENV/GITHUB_OUTPUT injection, secret exposure, OIDC over long-lived credentials, and self-hosted runner exposure on public repositories.
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。
Pre-breach impact analysis: inventories sensitive data (PII, PHI, PCI-DSS, credentials), traces data flows, scores exposure vectors, and produces a regulatory blast radius report with fine ranges sourced verbatim from GDPR Art. 83, CCPA § 1798.155(a), and HIPAA 45 CFR § 160.404. Cost benchmarks from IBM Cost of a Data Breach Report (annually updated). All citations in references/SOURCES.md for verification. Use when asked: "assess breach impact", "what data could be exposed", "calculate blast radius", "data exposure analysis", "how bad would a breach be", "quantify data risk", "sensitive data inventory", "data flow security audit", "pre-breach assessment", "worst-case breach scenario", "breach readiness", "data risk report", "/data-breach-blast-radius". For any stack handling user data, health records, or financial information. Output labels law-sourced figures (exact) vs heuristic estimates (planning only). Does not replace legal counsel.
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。
Create and open a new desk in the workshop. Sets up the folder structure, initial journal, and desk identity so the next session that sits down finds the trail.
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。
Build an auditable evidence map for a contested technical choice, research synthesis, proposal review, or consequential decision. Use when Copilot must preserve supporting, contradicting, qualifying, and missing evidence with exact source regions instead of collapsing disagreement into prose.
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。
Close defects and incidents with a BUG RECEIPT and VERIFIED, PARTIAL, or BLOCKED status after diagnosis, repair, or recovery.
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。
Performs comprehensive preflight validation of Bicep deployments to Azure, including template syntax validation, what-if analysis, and permission checks. Use this skill before any deployment to Azure to preview changes, identify potential issues, and ensure the deployment will succeed. Activate when users mention deploying to Azure, validating Bicep files, checking deployment permissions, previewing infrastructure changes, running what-if, or preparing for azd provision.
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。
Setup and initialization guide for developing AWS CDK (Cloud Development Kit) applications in Python. This skill enables users to configure environment prerequisites, create new CDK projects, manage dependencies, and deploy to AWS.
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。
Build accretion/dilution analysis for M&A transactions. Models pro forma EPS impact, synergy sensitivities, and purchase price allocation. Use when evaluating a potential acquisition, preparing merger consequences analysis for a pitch, or advising on deal terms. Triggers on "merger model", "accretion dilution", "M&A model", "pro forma EPS", "merger consequences", or "deal impact analysis".
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 unit economics for PE targets — ARR cohorts, LTV/CAC, net retention, payback periods, revenue quality, and margin waterfall. Essential for software/SaaS, recurring revenue, and subscription businesses. Use when evaluating revenue quality, building a cohort analysis, or assessing customer economics. Triggers on "unit economics", "cohort analysis", "ARR analysis", "LTV CAC", "net retention", "revenue quality", or "customer economics".
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。
Draft process letters and bid instructions for sell-side M&A processes. Covers initial indication of interest (IOI) instructions, final bid procedures, and management meeting logistics. Triggers on "process letter", "bid instructions", "IOI letter", "bid procedures", "final round letter", or "management meeting invite".
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。
Create comprehensive industry and sector landscape reports covering market dynamics, competitive positioning, key players, and thematic trends. Use for client requests, sector initiations, thematic research pieces, or internal knowledge building. Triggers on "sector overview", "industry report", "market landscape", "sector analysis", "industry deep dive", or "thematic research".
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。
Evaluate FX carry trade opportunities by combining spot rates, forward points, interest rate differentials, volatility surface analysis, and historical price trends. Use when analyzing carry trades, comparing FX forward curves, assessing carry-to-vol ratios, or evaluating currency pair opportunities.
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。
Complete, populate and fill out 3-statement financial model templates (Income Statement, Balance Sheet, Cash Flow Statement) . Use when asked to fill out model templates, complete existing model frameworks, populate financial models with data, complete a partially filled IS/BS/CF framework, or link integrated financial statements within an existing template structure. Triggers include requests to fill in, complete, or populate a 3-statement model template
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。
Deep codebase initialization with hierarchical AGENTS.md documentation
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-referential loop until task completion with configurable verification reviewer
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。
YAGNI-ladder coding discipline for writing changes — existence-first, reuse before writing, dependency ladder, shortest correct diff, with non-negotiables that must never be minimized away
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。
Add a new model to the SGLang Cookbook (docs/, Mintlify), config-driven format — instantiate the model-agnostic template into a per-model config (+ benchmarks) JSX under src/snippets/configs/, an MDX page, the docs.json nav entry, NEW-tag hygiene, and the homepage vendor card. Interactive, multi-phase. Run with /cookbook-add-model.
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。
Harmonic Patterns signal engine. Identifies XABCD five-point structures such as Gartley/Bat/Butterfly/Crab based on Fibonacci geometry, and generates trading signals in the PRZ (Potential Reversal Zone).
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 RDP brute force attacks by parsing Windows Security Event Logs (EVTX files, via python-evtx) for failed logon patterns (Event ID 4625, Logon Type 10/3), correlating with successful logons (Event ID 4624), and analyzing NLA failures and source IP frequency. Use when investigating exposed RDP endpoints, building SIEM detection rules for credential guessing, or confirming whether a compromised account followed a brute-force pattern.
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。
Triage npm packages and lockfiles for install-script malware, credential exfiltration, and worming behavior using GuardDog, manual tarball inspection, and dynamic detonation with network/filesystem monitoring. Use when vetting a new dependency, reviewing a package.json/package-lock.json during code review, checking lockfiles against a supply-chain advisory's known-bad versions, or investigating a host suspected of installing a trojanized package.
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 NTLM relay attacks (T1557.001) by correlating Windows Event 4624 LogonType 3 for IP-to-hostname mismatches, identifying Responder/LLMNR poisoning artifacts, auditing SMB/LDAP signing, and flagging NTLMv2-to-NTLMv1 downgrades. Use for hunting credential relay in NTLM-enabled AD, investigating auth-source anomalies, building SIEM correlation rules, or responding to PetitPotam/DFSCoerce/PrinterBug alerts.
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。