「challenge」の検索結果

Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for CTF web, API, SSR, frontend, queue-backed app, and routing challenges. Use when the user asks to inspect a site or API, follow real browser requests, debug auth or session flow, trace uploads or workers, find hidden routes, or explain why frontend and backend behavior diverge under sandbox-internal routing. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.

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。

Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for reverse engineering, malware, DFIR, firmware, pwnable, and native exploit challenges. Use when the user asks to reverse a binary, unpack a sample, inspect a memory dump or PCAP, recover malware behavior, debug a crash, or build or verify an exploit chain under sandbox assumptions. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.

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。

Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for CI/CD, registry, dependency drift, artifact provenance, image build, release pipeline, and runtime consumer challenges. Use when the user asks to trace dependency drift, registry pulls, malicious packages, build or release tampering, CI execution, artifact signing, or which shipped artifact the runtime actually consumes. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.

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。

Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for Active Directory, Kerberos, LDAP, OAuth, enterprise messaging, Windows host forensics, credential material, and lateral-movement challenges. Use when the user asks to trace tickets or tokens, inspect mailbox rules, analyze Windows host evidence, understand an AD trust path, or explain a lateral-movement chain across sandbox-linked nodes. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.

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。

Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for AI-agent, prompt-injection, MCP or toolchain, cloud, container, CI/CD, and supply-chain challenges. Use when the user asks to analyze prompt-to-tool flows, retrieval poisoning, mounted secrets, deployment drift, runtime-vs-manifest mismatches, registry provenance, or CI-produced artifacts under sandbox assumptions. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.

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。

Understand anti-reversing, obfuscation, and protection techniques encountered during software analysis. Use this skill when analyzing malware evasion techniques, when implementing anti-debugging protections for CTF challenges, when reverse engineering packed binaries, or when building security research tools that need to detect virtualized 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。

Rigorous challenge profile for Anitta: assumption checks, evidence calibration, and defensible reasoning patterns for Ember collaboration.

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。

Interactive training for the GitHub Copilot CLI. Guided lessons, quizzes, scenario challenges, and a full reference covering slash commands, shortcuts, modes, agents, skills, MCP, and configuration. Say "cliexpert" to start.

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Deep research framework for pre-IPO / private companies (Ant Group, SpaceX, Stripe, ByteDance...). Six analyst lenses — business model, financial forensics, competitive landscape, risk & governance, tech & IP, alternative-data signals — run in parallel via run_swarm, then cross-validated for signal consistency before any verdict. Built around the core challenge of private-company work: information is scarce, so every data point carries a confidence label (high / medium / low), inference is shown separately from fact, and 'I don't know' is a valid output. Outputs a fair-value range, exit-path analysis, and an information-gap map. Use for any unlisted company where you need to judge what the business is actually worth.

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Voice agents represent the frontier of AI interaction - humans speaking naturally with AI systems. The challenge isn't just speech recognition and synthesis, it's achieving natural conversation flow with sub-800ms latency while handling interruptions, background noise, and emotional nuance. This skill covers two architectures: speech-to-speech (OpenAI Realtime API, lowest latency, most natural) and pipeline (STT→LLM→TTS, more control, easier to debug). Key insight: latency is the constraint. Hu

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Autonomous agents are AI systems that can independently decompose goals, plan actions, execute tools, and self-correct without constant human guidance. The challenge isn't making them capable - it's making them reliable. Every extra decision multiplies failure probability. This skill covers agent loops (ReAct, Plan-Execute), goal decomposition, reflection patterns, and production reliability. Key insight: compounding error rates kill autonomous agents. A 95% success rate per step drops to 60% b

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Build AI agents that interact with computers like humans do - viewing screens, moving cursors, clicking buttons, and typing text. Covers Anthropic's Computer Use, OpenAI's Operator/CUA, and open-source alternatives. Critical focus on sandboxing, security, and handling the unique challenges of vision-based control. Use when: computer use, desktop automation agent, screen control AI, vision-based agent, GUI automation.

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Brainstorm product ideas, explore problem spaces, and challenge assumptions as a thinking partner. Use when exploring a new opportunity, generating solutions to a product problem, stress-testing an idea, or when a PM needs to think out loud with a sharp sparring partner before converging on a direction.

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-mortem plan analysis. Imagine the plan failed 12 months from now and work backwards to find the weaknesses. Surfaces assumptions, dependencies, and execution risks before committing resources. Use when before significant resource commitment, before presenting to a board or investors, when feedback has been one-sidedly positive, or when there is pressure to move fast and figure it out later.

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Implement and debug OAuth 2.0 DPoP (RFC 9449) refresh token sender-constraining for WebCrypto, Node.js ES6, and browser runtimes integrating with Google's OAuth platform. Use when configuring non-extractable asymmetric key pairs (P-256), generating DPoP Proof JWTs for authorization code exchange and token refresh, or handling 400 use_dpop_nonce challenge retry loops at oauth2.googleapis.com/token. Don't use for unconstrained OAuth 2.0 flows (where refresh tokens are not bound to a client key pair), or for Google Cloud IAM / service account authentication.

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。

Review Apache ShardingSphere or user-authorized downstream pull requests and PR discussions from public or authorized repository evidence. Use for code-correctness or mergeability decisions, CI-focused review, root-cause and regression analysis, complete consolidated findings, copy-ready committer feedback, challenged findings, multi-round review, and formal review of local implementation candidates in the repository completion loop.

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。

Physics-based reasoning framework (Musk methodology) that deconstructs a problem to irreducible fundamental truths, classifies every element as hard constraint, soft constraint, or assumption, then reconstructs the optimal solution from fundamentals alone. USE WHEN first principles, fundamental truths, challenge assumptions, real constraint, rebuild from scratch, start over, physics first, question everything, reasoning by analogy. NOT FOR structural feedback loops (use SystemsThinking).

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。

Apply the Fable-derived 10-stage OBSERVE, OBSERVE, LISTEN, THINK, CONNECT, CONNECT, FEEL, ACCEPT, CREATE, GROW loop to consequential or ambiguous reasoning and decisions. Use for think this through, deep think, architecture review, postmortem, tradeoff analysis, or challenges to assumptions. This is a reasoning review, not a deterministic vault health check or repair workflow.

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Installs the CARLA Autonomous Driving Leaderboard (leaderboard.carla.org) at a chosen version — 1.0, 2.0 or 2.1 — together with the exact scenario_runner branch and CARLA build each one requires, then wires the four-root PYTHONPATH and verifies the whole stack imports. Detects which version an existing checkout is by reading its code, not its branch name. Use when the user asks to "install the leaderboard", "set up the CARLA challenge", "evaluate my driving agent", "reproduce my leaderboard score", or names a leaderboard version.

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 building, configuring, or debugging enterprise Java applications with Spring Boot 3.x, microservices, or reactive programming. Invoke to implement WebFlux endpoints, optimize JPA queries and database performance, configure Spring Security with OAuth2/JWT, or resolve authentication issues and async processing challenges in cloud-native Spring applications.

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WPA/WPA2/WPA3-Enterprise (802.1X / EAP) attack methodology — EAP method identification (PEAP-MSCHAPv2, EAP-TTLS, EAP-TLS, EAP-GTC, EAP-PWD, EAP-FAST), evil-twin RADIUS attacks with eaphammer for credential capture, MSCHAPv2 challenge-response cracking, EAP-TLS client certificate theft paths (DPAPI, NDES, AD CS auto-enrollment), supplicant validation bypass (missing server cert validation, missing CN pinning, BYOD misconfigurations), and post-capture pivots into AD via cracked domain credentials. Use for corporate Wi-Fi engagements where the network is 802.1X authenticated.

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Fulfill a git escrow bounty by writing a solution or submitting an existing one. Use when the user wants to solve a test suite challenge, write code to pass tests, and claim a token reward. Requires the git-escrows CLI (npm i -g git-escrows).

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 a new git escrow bounty for a test suite. Use when the user wants to submit a challenge with escrowed token rewards for passing a failing test suite. Requires the git-escrows CLI (npm i -g git-escrows).

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。

Strategic product gate: challenge the brief, find the 10-star product hiding inside the request, before writing any 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。