「memo」の検索結果

Audits whether a machine-readable regelrecht law model is faithful to the LETTER of the wettekst — and strictly separates the wettekst (leading) from the toelichting (Nota/Memorie van Toelichting; explanatory, not a norm). Runs in critical passes per article/lid and detects four deviation classes: toelichting-bleed (a modeled criterion that the letter only states as an open norm, or not at all), missing verbatim elements (a word/condition such as a "tenzij" or a qualifier dropped from the model), wrong legal_basis anchoring (an endpoint hung on a "kapstok"-article while the operative norm lives elsewhere), and verbatim-drift in text: (an ingetrokken/older redaction). Also detects positief-lid vs uitsluitings-lid conflicts and checks the chapeau for an explicit derogation rule ("zo nodig in afwijking van het eerste lid") before judging precedence. Classifies every finding as modelfout (fix), wettekst-gevolg (report, do not fix), or letter-vs-toelichting-question (jurist decides what is leading + revision signal). Use when the user wants to know if a model is "dicht bij de letter", mentions letter vs toelichting/bedoeling, fidelity, "natuurgetrouw", or before trusting feature outcomes.

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。

Interact with GitHub using the `gh` CLI. Use `gh issue`, `gh pr`, `gh run`, and `gh api` for issues, PRs, CI runs, and advanced queries.

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。

Search and install agent skills from ClawHub, the public skill 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。

Get current weather and forecasts (no API key required).

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。

Automates browser interactions for web testing, form filling, screenshots, and data extraction. Use when the user needs to navigate websites, interact with web pages, fill forms, take screenshots, or extract information from web pages.

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 or update AgentSkills. Use when designing, structuring, or packaging skills with scripts, references, and assets.

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。

Documentation reference for writing Python code using the browser-use open-source library. Use this skill whenever the user needs help with Agent, Browser, or Tools configuration, is writing code that imports from browser_use, asks about @sandbox deployment, supported LLM models, Actor API, custom tools, lifecycle hooks, MCP server setup, or monitoring/observability with Laminar or OpenLIT. Also trigger for questions about browser-use installation, prompting strategies, or sensitive data handling. Do NOT use this for Cloud API/SDK usage or pricing — use the cloud skill instead. Do NOT use this for directly automating a browser via CLI commands — use the browser-use skill instead.

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。

Remote-control tmux sessions for interactive CLIs by sending keystrokes and scraping pane output.

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。

Controls a local browser from a sandboxed remote machine. Use when the agent is running in a sandbox (no GUI) and needs to navigate websites, interact with web pages, fill forms, take screenshots, or expose local dev servers via tunnels.

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。

Summarize or extract text/transcripts from URLs, podcasts, and local files (great fallback for “transcribe this YouTube/video”).

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。

Schedule reminders and recurring tasks.

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。

Documentation reference for using Browser Use Cloud — the hosted API and SDK for browser automation. Use this skill whenever the user needs help with the Cloud REST API (v2 or v3), browser-use-sdk (Python or TypeScript), X-Browser-Use-API-Key authentication, cloud sessions, browser profiles, profile sync, CDP WebSocket connections, stealth browsers, residential proxies, CAPTCHA handling, webhooks, workspaces, skills marketplace, liveUrl streaming, pricing, or integration patterns (chat UI, subagent, adding browser tools to existing agents). Also trigger for questions about n8n/Make/Zapier integration, Playwright/ Puppeteer/Selenium on cloud infrastructure, or 1Password vault integration. Do NOT use this for the open-source Python library (Agent, Browser, Tools config) — use the open-source skill instead.

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。

Work with Effect v4 / effect-smol TypeScript code in this 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。

Optimizes Atlassian Forge apps to reduce platform consumption and avoid unnecessary costs using Atlassian's "Optimise Forge platform costs" guidance. Use when the user asks to optimize Forge app costs, reduce Forge invocations, lower GB-seconds, reduce storage or log usage, tune memory, replace polling, improve scheduled triggers, reduce KVS writes, move work to the frontend, use bridge APIs, batch API calls, add caching, or evaluate Forge Remote trade-offs. By default, perform an audit first and offer to make the recommended changes after presenting the audit. Only modify files immediately when the user explicitly asks the agent to implement or apply 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。

Build structured vendor/tool evaluation matrices with weighted scoring, TCO analysis, and recommendation memos. Covers criteria definition, deal-breaker identification, and negotiation points. Use when selecting SaaS tools, evaluating technology vendors, or making build-vs-buy decisions.

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。

Summarize document-heavy inputs such as memos, policies, PDFs, research notes, proposals, and multi-document packets. Use when users need key points, obligations, questions, and action implications from documents.

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Write one-page executive briefs and decision memos that turn messy inputs into a concise recommendation, options, risks, decision ask, and next steps. Use when leaders need a fast read before approving budget, policy, vendor, headcount, or strategy changes. Do not use for long-form reports, slide design, or generic summarization without a 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。

Malware reverse engineering and suspicious artifact analysis skill for defensive triage, static analysis, dynamic analysis planning, unpacking strategy, indicators of compromise, behavior summaries, YARA/Sigma ideas, and remediation guidance. Use for suspicious binaries, scripts, documents, logs, memory artifacts, sandbox reports, and malware family analysis in isolated environments.

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。

Authorized exploit development and vulnerability research skill for lab environments, CTFs, owned software, crash analysis, memory corruption, exploitability assessment, fuzzing results, proof-of-concept design, and remediation. Use for defensive validation and education; avoid real-world weaponization, stealth, persistence, evasion, or unauthorized targets.

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Digital forensics and incident response triage skill for disk, memory, network, cloud, and endpoint artifacts. Covers Volatility 3, Velociraptor, KAPE, Plaso, Autopsy, Chainsaw, Hayabusa, Zeek, Arkime, EVTX, AWS/Azure/GCP audit logs, and timeline reconstruction. Use to extract IOCs, build incident timelines, and produce defensible analyst reports.

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。

Post-exploitation workflow. Covers privilege escalation (Linux SUID/sudo/kernel, Windows UAC/service/token), persistence assessment, local enumeration, credential harvesting, and pivot preparation. Structured workflows for Linux and Windows targets using impacket, netexec, john, linpeas/winpeas, and standard Kali tools. Includes kernel exploit reference tables, GTFOBins exploitation chains, Potato attack selection, Docker/container escapes, DLL hijacking, SSH key harvesting, credential recovery from memory, and Windows token manipulation. Chains from /pentester or /credential-audit when access is obtained.

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。

Detects code quality vulnerabilities in mobile apps (Android/iOS). Trigger on: SQL injection in SQLite, JavaScript injection in WebViews, intent injection, unsafe deserialization, NSKeyedUnarchiver, NSCoding, Java serialization, Parcelable, buffer overflow, JNI native code, PIE disabled, NX disabled, stack canary absent, RELRO, ARC disabled, third-party library CVE, vulnerable dependency, outdated SDK, targetSdkVersion, update enforcement missing, implicit Intent, URL loading in WebView, object persistence, memory corruption, OWASP dependency check. Covers MASVS-CODE-1/2/3/4.

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。

Extract sensitive training data and internal capabilities from AI models through repeated programmatic querying. Use this skill when testing LLMs and ML models for data privacy leaks, intellectual property exposure, or unintended memorization. Covers membership inference, prompt extraction, training data reconstruction, and API boundary testing.

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。

Execute dynamic instrumentation utilizing Frida to inject custom JavaScript into running iOS applications (IPAs) on jailbroken devices. Hook native functions, bypass SSL Pinning, bypass Jailbreak Detection, and manipulate in-memory data at runtime.

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。