「ats」の検索結果

自媒体创作者在进行全网内容分发时，使用此技能可智能筛选优质选题、AI生成多版本文章，并一键自动适配格式发布至微信公众号、知乎、掘金等6大平台，轻松实现从创作到推送的全流程自动化，大幅提升多平台运营效率！

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。

软件开发工程师、产品经理等求职者，在针对特定职位描述投递或跨行转岗时，可一键深度分析岗位需求，自动提取ATS关键词并重组个人经验，快速生成高命中率的定制简历，大幅提升面试邀约率。

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。

Helps you build and check a color system for your project. It generates palettes, names semantic tokens, converts between formats and measures contrast.

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 professional documents after tool failures using shell_agent for complex formats or write_file for simple text/markdown

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。

Graceful degradation workflow for continuing tasks when web search tools fail, using internal knowledge with verification caveats

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。

Read how a game actually works so a mod can hook it. Decompile .NET/Mono (ILSpy), IL2CPP (Cpp2IL, Il2CppDumper), Java (Vineflower) and native code (Ghidra, IDA, via MCP servers); dump data and asset formats; reverse-engineer a binary file format and prove it with a round trip; read live memory (Cheat Engine, Frida, x64dbg); find render passes (RenderDoc). Use when a mod needs game internals, e.g. "how does the boss AI work", "find the damage function", "what format is this .sld/.pak/.dat", "where is the player position in memory".

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。

Writes and reviews structured Lean 4 proofs and designs Lean libraries following Mathlib conventions. Use when proving theorems in Lean, formalizing mathematics or specifications in Lean 4, defining new types or definitions in a Lean library, reviewing Lean proofs for readability and maintainability, refactoring long tactic proofs into lemmas, filling in sorry placeholders in a Lean development, setting up CI or linters for a Lean project, diagnosing slow proofs or maxHeartbeats timeouts, or writing custom tactics, macros, or linters.

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。

Penetration test and red team report writing methodology. Covers executive summary structuring (risk-led narrative for non-technical readers), technical finding format (title, severity, affected scope, narrative, reproduction steps, impact, remediation, references), CVSS v3.1 / v4.0 scoring with vector justification, OWASP risk rating, evidence hygiene (redacting credentials, hashing client data, time-stamping every action), screenshot and PoC artifact management, finding chain narratives, scope/limitations/assumptions documentation, retest evidence and remediation tracking, deliverable formats (PDF, DOCX, HTML, JSON for SIEM ingestion), client-customer-deliverable separation, and common report mistakes (over-CVSSing, undermining the triager, missing the 'so what'). Use at the end of an engagement when authoring a deliverable, when restructuring a draft for executive readability, or when establishing a reusable report template for a consulting practice.

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。

Comprehensive persistence tradecraft for authorized red team engagements covering Windows and Linux mechanisms. Windows techniques include registry Run/RunOnce keys, scheduled tasks, WMI event subscriptions, DLL search order hijacking, COM object hijacking, Startup folder drops, service creation, Security Support Provider (SSP) DLL injection, and Active Directory persistence (AdminSDHolder abuse, DCShadow, Golden Ticket, Silver Ticket, Skeleton Key, SID History injection). Linux techniques include cron and at jobs, systemd timers and services, SSH authorized_keys injection, shell profile backdoors (.bashrc/.bash_profile), PAM module backdoors, LD_PRELOAD hijacking, kernel module rootkits, web shells, and Git hook abuse. Provides operator-ready command sequences for SharPersist, Impacket ticketer, schtasks, sc.exe, crontab, and systemctl with OPSEC considerations for each method. Maps to MITRE ATT&CK T1547 (Boot or Logon Autostart), T1053 (Scheduled Task/Job), T1546 (Event Triggered Execution), T1556 (Modify Authentication Process), and sub-techniques. Includes detection indicators and a rapid engagement cheatsheet.

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。

Comprehensive lateral movement tradecraft for authorized red team engagements covering credential-based movement (pass-the-hash, pass-the-ticket, overpass-the-hash), NTLM relay attacks (ntlmrelayx with PetitPotam, DFSCoerce, PrinterBug coercion), remote execution protocols (WMI, WinRM, DCOM, PsExec and alternatives), RDP session hijacking, and network pivoting through tunneling tools (chisel, ligolo-ng, SSH tunnels, SOCKS proxies). Provides operator-ready command sequences for mimikatz, crackmapexec/netexec, impacket suite, and evil-winrm with emphasis on OPSEC considerations, SMB signing bypass, and detection evasion. Maps to MITRE ATT&CK T1021 (Remote Services), T1550 (Use Alternate Authentication Material), and sub-techniques. Includes defender-perspective detection guidance for blue team awareness and a rapid engagement cheatsheet for common lateral movement scenarios encountered during internal penetration tests and assumed-breach exercises.

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。

LoRaWAN and sub-GHz (433 / 868 / 915 MHz) attack methodology — LoRaWAN ABP/OTAA join attack, network/session key reuse, frame counter replay, downlink injection on TTN/Helium-style networks, sub-GHz protocol replay (KeeLoq garage doors, fixed-code remotes, TPMS spoofing, smart plug telemetry), HackRF / RTL-SDR / Flipper Zero workflows, signal analysis with Inspectrum / Universal Radio Hacker, and reconstruction of proprietary packet formats. Use for LoRaWAN deployments (smart cities, asset tracking, industrial telemetry), or any wireless device using the unlicensed 433/868/915 MHz bands (garage openers, doorbells, IoT sensors, RC equipment).

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 designing, reviewing, or debugging how an agent's context window gets filled, pruned, or shared — choosing what loads at boot versus on demand, sizing an install or an always-loaded file, fixing an agent that drifts, repeats itself, or forgets constraints mid-task, planning compaction or summarization, deciding single-agent versus subagents, engineering handoffs between agents, or picking a tool loadout. NOT for rewording a prompt's tone, choosing which model to pin, or debugging business logic — those are adjacent moments this skill does not serve. Historical 2024–2025 snapshot; not normative for present-day frontier models — see the Status section.

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 classifying a slice closeout (auto-continue / human gate / park), routing a real decision to a human, or designing a human queue/dashboard surface. Treats humans as durable network participants with attention surfaces, queues, and decision records — escalation lands as a durable attention item, not a chat message. Approval is NOT required for every clean closeout; the default RSI conveyor continues unless an explicit human gate is reached.

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 an agent is preparing or performing an OpenRig CLI/daemon upgrade and must preserve live seats, verify each mutation, or reconcile managed plugin and skill files without overwriting local work.

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。

Capture conversations and decisions into structured Notion pages; use when turning chats/notes into wiki entries, how-tos, decisions, or FAQs with proper linking.

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。

Validate whether an analysis is accurate, well-supported, and ready to share or use for a decision. Use when reviewing methodology, calculations, comparisons, visuals, caveats, or conclusions.

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 polished analytical reports for executive, product, business, or technical audiences. Use when the task needs a durable answer-first narrative with evidence-backed findings, visuals or tables, caveats, and source context.

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。

Resize a Canva design into multiple social media formats (Facebook post, Facebook story, Instagram post, Instagram story, LinkedIn post). Use this skill when users want to resize Canva designs specifically for multiple social media platforms in one operation, rather than resizing to a single format manually.

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 a user wants to see their logo, design, or sketch on a product or scene mockup — mugs, t-shirts, business cards, hats, phone screens, posters, billboards, or similar. Triggers on "create mockups", "show my logo on products", or any logo upload with a request to visualize it on items. Access: 🔐 Signed-In required | Gen AI: ✅ Adobe Firefly via `image_generate` used for design creation, sketch polishing, and mockup scene generation

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。

Calculate TAM, SAM, and SOM with explicit assumptions, methods, and caveats. Use when sizing a market for a product idea, business case, or executive 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。

Repository-grounded threat modeling that enumerates trust boundaries, assets, attacker capabilities, abuse paths, and mitigations, and writes a concise Markdown threat model. Use when the user asks to threat model a codebase or path, enumerate threats or abuse paths, or perform AppSec threat modeling. Do NOT use for general architecture summaries, code review, security best practices (use security-best-practices), or non-security design work.

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 a user asks to debug or fix failing GitHub PR checks that run in GitHub Actions. Uses `gh` to inspect checks and logs, summarize failure context, draft a fix plan, and implement only after explicit approval. Treats external providers (for example Buildkite) as out of scope and reports only the details URL. Do NOT use for addressing PR review comments (use gh-address-comments) or general CI outside GitHub Actions.

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。

The first security skill to install after setting up OpenClaw — powered by Tencent Zhuque Lab. Works like an antivirus for your AI environment: audits installed skills, scans skills before installation, and performs a full OpenClaw security health check to prevent data leaks and privacy risks. Backed by Tencent Zhuque Lab A.I.G (AI-Infra-Guard). Use when the user asks to start a security health check or security scan for the current OpenClaw environment, such as `开始安全体检`, `做一次安全体检`, `开始安全扫描`, `全面安全检查`, or `检查 OpenClaw 安全`; also use when the user asks to audit a specific skill before installation, review installed skills for supply chain risk, or investigate whether a skill is safe. Do not trigger for general OpenClaw usage, project debugging, environment setup, or normal development requests. Optional cloud mode: set AIG_CLOUD_LOOKUP=off for zero outbound HTTPS; when enabled, only skill_name, source label, and OpenClaw version are sent to A.I.G (never skill bodies, chats, or workspace files).

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, debug, balance, or test combat enemy AI for playable action games. Use for aggro, target selection, navigation, spacing, attack choices, telegraphs, retreats, boss behavior, behavior-state machines, and deterministic AI regression tests.

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。