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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。

Use this skill whenever the user needs ANY mailbox/email operation — checking, reading, searching, sending, replying, forwarding, organizing or deleting email, managing threads, connecting a personal mailbox, or registering a new mailbox. This skill is the single entry point for email tasks and orchestrates qwenpawmail-mcp for nine supported personal-mail domains.

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。

Re-encode verbose prose into a dense telegraphic register — punctuation as connectives, label frames, verbless assertions — without losing normativity or precision. Use when compressing system prompts, tool/function descriptions, skill bodies, or agent instructions; reducing token count or context bloat; making documentation token-efficient for LLM input; or rewriting text in compressed notation.

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 command injection against Modbus TCP/RTU in ICS/SCADA environments by monitoring unauthorized writes, anomalous function codes, malformed frames, and deviations from communication baselines using ICS-aware IDS and deep packet inspection. Use when deploying IDS for Modbus OT networks, investigating unauthorized PLC register/coil changes, or responding to FrostyGoop-style Modbus attacks.

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 anomalies in Modbus/TCP and Modbus RTU industrial traffic via function code monitoring, register range validation, timing analysis, and deep packet inspection, using Zeek's Modbus analyzer, Suricata IDS with OT rules, and Python Markov chain models of normal transaction sequences. Use for deploying Modbus IDS in OT environments, baselining polling patterns, investigating suspicious Modbus traffic, or building function code allowlists.

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 domain permutations with dnstwist and check DNS resolution to detect typosquatting, homograph phishing, and brand impersonation domains registered against your organization. Use when asked to monitor for lookalike domains, investigate a phishing domain, or assess brand-impersonation risk.

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 automated adversary infrastructure tracking system in Python (dnspython, python-whois, shodan, networkx) that pivots across passive DNS, certificate transparency logs, WHOIS records, and IP enrichment to map threat-actor C2 networks and flag newly registered domains matching known patterns. Use when pivoting from known indicators to discover related C2 infrastructure or maintaining a continuously updated map of a threat actor's network.

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。

Scaffold the co-located feature structure in frontend/src. Use when creating a new page, feature, view (tab), or component folder, when a feature needs a shell with tabs, or when moving existing code out of src/container into src/pages. Generates the full folder tree (components/hooks/store/types/utils/constants/__tests__/README) and registers the page's routes with one command.

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 the user's own gbrain over MCP so other devices, desktop apps and cloud agents can reach it. `gbrain mcp expose` installs and signs in Tailscale, publishes the running `gbrain serve --http` on the tailnet (HTTPS, tailnet-only by default; Funnel only when a client lives in a vendor cloud), keeps the server alive as a user service, and hands back the MCP URL. Then register one least-privilege client per consumer, choose native OAuth/PKCE or a private machine handoff for that client, and verify the connection inside the intended harness.

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。

Generic framework for converting external events (SMS, meetings, social mentions) into brain-ingestible signals. Define a transform function, register a webhook URL, and incoming events get processed through the brain pipeline.

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。

Ghostwrite content in a specific person's voice from a VALIDATED voice profile — tweets, replies, short posts, launch copy, recruiting blurbs, emails. Loads the subject's voice profile (people/<slug>-voice) plus first-party context from the brain, drafts 2-3 options in-register, then runs a hard voice-fidelity self-check before showing anything. Includes the profile BUILDER: if no validated profile exists, drafting hard-stops and this skill walks the corpus-to-fingerprint build instead. Never auto-posts.

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。

Turns a task the owner keeps doing by hand into a named, reusable skill they can trigger by name or put on a schedule. Watches them do it once or listens to them describe it, works out what varies and what stays fixed, writes the skill with approval checkpoints in the right places, registers it with the router, and shares it with the team. This is how a business gets a workflow nobody shipped for them. Use this whenever the owner describes something repetitive they wish were automatic — including phrasings like "I do this every week," "can you remember how to do this," "make this a thing I can just ask for," "build me an agent," "automate this for me," "turn this into a workflow," or "I want this to happen every Monday." Reach for it when they describe a routine, even without asking for automation.

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, assess, and mitigate operational risks. Trigger with "what are the risks", "risk assessment", "risk register", "what could go wrong", or when the user is evaluating risks associated with a project, vendor, process, or decision.

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。

Register Angular Table v9 instances with injectTanStackTableDevtools inside injection context. Load for reactive table registration, required options.key, enabled or undefined tables, cleanup, Angular isDevMode gating, or explicit production exports.

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。

Register TanStack Table targets and inspect options, state, features, columns, rows, and row models with @tanstack/table-devtools. Load for missing connections, required unique table options.key, target replacement/cleanup, or an explicit request for production Devtools entrypoints.

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。

/em:postmortem — Honest analysis of what went wrong. Use after a failed launch, missed quarter, or bad hire to run a blameless 5-Whys retrospective with a change register — e.g. dissecting why the Q3 release slipped six weeks.

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。

ISO/IEC 42001:2023 AI Management System (AIMS) specialist for compliance teams running internal audits. Three decisions: (1) Where are the gaps against Clauses 4-10 and what do we close first? (2) What goes in the AI risk register and which Annex A controls treat each risk? (3) What's the 12-month internal audit plan that satisfies Clause 9.2? Use when preparing for certification, scoping internal audit cycles, or onboarding AI systems into an existing ISMS (27001) / QMS (13485) program. NOT an executive AI strategy skill (see chief-ai-officer-advisor). NOT EU AI Act compliance (see compliance-team-eu-ai-act).

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, scaffold, refactor, and troubleshoot ChatGPT Apps SDK applications that combine an MCP server and widget UI. Use when Codex needs to design tools, register UI resources, wire the MCP Apps bridge or ChatGPT compatibility APIs, apply Apps SDK metadata or CSP or domain settings, or produce a docs-aligned project scaffold. Prefer a docs-first workflow by invoking the openai-docs skill or OpenAI developer docs MCP tools before generating 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。

Persistent file-based planning for multi-step AI-agent work. Keeps task_plan.md, findings.md, and progress.md on disk; agent instructions read selected project planning context when invoked. Automatic recovery reads project planning files only. Explicit session-catchup.py --metadata reads same-project local agent session records and emits aggregate counts only; --replay may emit bounded nonce-framed excerpts. This adapter registers no lifecycle or Stop hook, never requests continuation, and never runs commands declared in Markdown. The skill has no network upload path. Use for research or work needing 5+ tool calls.

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。

Persistent file-based planning for multi-step AI-agent work. Keeps task_plan.md, findings.md, and progress.md on disk; Kiro skill instructions and steering state read selected project planning context. Recovery reads project planning files and their timestamps only, not agent transcript stores. This adapter registers no Stop hook, never requests continuation, and never runs commands declared in Markdown. The skill has no network upload path. Use for research or work needing 5+ tool calls.

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。

Track, categorize and prioritize technical debt across the codebase — scans for debt indicators, maintains a register.

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。

Retune a skill corpus for a new model, measurement-first: mine the run archive for a baseline, establish a noise floor, audit the corpus adversarially, then cut in measured passes until a pre-registered bar clears. Requires a benchmark harness that can A/B two builds of the corpus; refuses without one.

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 when creating or modifying a Handsontable cell type that composes an editor, renderer, and validator into a reusable configuration object registered by name

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。

Configures Cloud Monitoring PromQL-based Service Level Objective (SLO) alerting policies on Google Cloud for resources registered in App Hub or individually specified. Generates Terraform output. Use when the user asks to configure an SLO or Service Level Objective. Don't use for standard alerting policies.

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。