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Write Python in n8n Code nodes (native Python, `language` pythonNative, n8n 2.x). Use when the user explicitly wants Python in a Code node, when migrating old Pyodide/"Python (Beta)" code that used _input/_json/_node/_now, or when a Python Code node fails with NameError, "Security violations detected", "Import of standard library module … is disallowed", "__build_class__ not found", "A 'json' property isn't a dictionary", or "Python runner unavailable". Covers the only two variables (_items/_item), dict-only access, imports blocked by default, the sandbox's denied builtins, accepted return shapes, and how errors interact with onError. JavaScript is the default for Code nodes — native Python has no n8n helpers and, by default, no imports. EXCEPTION — for Python in the AI-agent-callable Custom Code Tool (@n8n/n8n-nodes-langchain.toolCode), use the n8n-code-tool skill instead (input is _query, return must be a string).

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Write JavaScript or Python for the n8n Custom Code Tool (@n8n/n8n-nodes-langchain.toolCode) — the AI-agent-callable tool, NOT the workflow Code node. Use when building a Code Tool attached to an AI Agent, writing code that an LLM will invoke, parsing the `query` input, returning a string result, defining an input schema for structured arguments (specifyInputSchema, jsonSchemaExample, DynamicStructuredTool), or troubleshooting errors like "Wrong output type returned", "No execution data available", "The response property should be a string, but it is an object", "Cannot assign to read only property 'name'", or an AI agent that refuses to call the tool. Covers the critical differences between Code node and Code Tool: return format (string vs `[{json:{...}}]`), unavailability of `$fromAI`/`$input`/`$helpers` in the Code Tool sandbox, naming rules for AI invocation, and when to use `toolWorkflow`/HTTP Request Tool instead.

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Darwin Skill 2.0 (达尔文.skill 2.0): autonomous skill optimizer, v2.0 integrates Microsoft Research SkillLens (arXiv 2605.23899) 9-dim rubric + SkillOpt (arXiv 2605.23904) validation-gated design + human-in-the-loop checkpoints. Evaluates SKILL.md files using a 9-dimension rubric (structure + effectiveness + meta-skill blacklists), runs hill-climbing with git version control, spawns independent judge agents for blind evaluation, validates improvements through test prompts with auto-break on diminishing returns, and generates visual result cards. Use when user mentions "优化skill", "skill评分", "自动优化", "auto optimize", "skill质量检查", "达尔文", "darwin", "帮我改改skill", "skill怎么样", "提升skill质量", "skill review", "skill打分".

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This skill is designed to help users automatically extract reviews from Google Maps via the Google Maps Reviews API. Agent should proactively apply this skill when users request to find reviews for local businesses (e.g., coffee shops, clinics), monitor customer feedback for a specific brand or location, analyze sentiment of reviews for competitors, extract reviews for a chain of stores or services, track reputation of a local restaurant, gather user testimonials for a specific venue, conduct market research on service quality of local businesses, monitor reviews for a new retail location, collect feedback on public attractions or parks, identify common complaints for a specific service provider, research the best-rated places in a city, analyze recurring themes in reviews for a specific industry.

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This skill should be used when the user wants to "deploy an agent", "deploy my ADK agent", "set up CI/CD", "configure secrets", "troubleshoot a deployment", or needs guidance on Agent Runtime, Cloud Run, or GKE deployment targets, or binding an agent to an Agent Gateway. Covers deployment workflows, service accounts, rollback, and production infrastructure. Applies to any framework agents-cli deploys (ADK, LangChain, ...). Part of the agents-cli skills suite. Do NOT use for agent API code patterns (ADK: use google-agents-cli-adk-code), evaluation (use google-agents-cli-eval), or project scaffolding (use google-agents-cli-scaffold).

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Diagnoses and fixes .NET MAUI development environment issues. Validates .NET SDK, workloads, Java JDK, Android SDK, Xcode, and Windows SDK. All version requirements discovered dynamically from NuGet WorkloadDependencies.json — never hardcoded. Use when: setting up MAUI development, build errors mentioning SDK/workload/JDK/Android, "Android SDK not found", "Java version" errors, "Xcode not found", environment verification after updates, or any MAUI toolchain issues. Do not use for: non-MAUI .NET projects, Xamarin.Forms apps, runtime app crashes unrelated to environment setup, or app store publishing issues. Works on macOS, Windows, and Linux.

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Make a custom AI agent — Python or TypeScript/JavaScript, on a framework or hand-built — report what it did to Failproof AI, and run your own evaluator worker (the "eval pod") that scores those runs. Reach for it on vague phrasing too: "add observability to my agent", "why isn't my agent showing up?", "run an LLM judge on our own infra". Trigger when the user wants to: • plan an integration — which points in the agent loop to record; • instrument — add `failproofai-sdk` (Python) or `@failproofai/sdk` (Node, Bun, Deno, Next.js): turn on an adapter (LangChain/LangGraph, CrewAI, LlamaIndex, Pydantic AI, Vercel AI SDK, Mastra) or wire a hand-built loop; • verify — confirm events are written, or debug an integration that produces nothing; • evaluate — write, deploy or debug an Evaluator worker in Python or TypeScript. NOT for reading telemetry or scores that already landed (that's `fp-cloud-cli`), or deciding what is worth evaluating (that's `failproofai-eval-brainstorm`).

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Security best practices for gh-aw workflows and Go code: template injection prevention, shell script security, supply chain hardening, and static analysis integration.

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Scans a live Kubernetes environment with `mirrord dump` to find an identifier mirrord can filter traffic on: a header, a `baggage` or `tracestate` member, a tenant or user id, a trace id (W3C, B3, X-Ray, Google, Jaeger), a JWT claim, a cookie, a path segment, or a JSON body field that is present on every hop of a request chain, unique to one developer's traffic, and settable by that developer. Runs mirror-only dumps on each service, sends a tagged probe request at the edge or observes real traffic, scores the candidates, and produces the matching `http_filter` (regex, jq on headers, path, method, body, or combinations) plus a per-hop report of where each identifier is dropped. Installs the mirrord CLI through a package manager when it is missing. Use when the user asks what to filter on, whether the cluster already propagates a request id or trace context, how to isolate their own requests on a shared staging cluster, how to filter on a JWT or cookie with mirrord, or wants to inspect live traffic with mirrord dump. Changes no application code: propagation gaps go to the mirrord-header-propagation skill.

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Makes a codebase propagate W3C baggage (the `baggage` header carrying `mirrord-session=<key>`) end to end, so mirrord HTTP filters, preview environments, and queue splitting can route a whole request chain to one developer's session. Detects existing OpenTelemetry, Datadog, or other tracing that can already propagate baggage and enables it; otherwise adds a small propagation layer. Covers inbound/outbound HTTP and gRPC, publishing to and consuming from Kafka, RabbitMQ, SQS/SNS, GCP Pub/Sub, Azure Service Bus, NATS, Redis Pub/Sub, BullMQ and Temporal, per-message context restore in consumers, and storage hand-offs such as a GCS signed URL upload that triggers Pub/Sub or an S3 presigned upload that triggers SQS. Ends with a report of every flow found and which ones still drop the header. Use when the user asks to propagate headers, baggage, tracestate, the mirrord session key, or trace context across services or queues, or when a mirrord filter matches the first service but not downstream services or queue consumers.

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Mobile app pentest for bug bounty (Android APK + iOS IPA) — runtime-first workflow: install app, proxy through Burp/mitmproxy, drive the UI, capture packets, then test the API exactly like a web target; escalate to decompile (apktool/jadx) and Frida/objection only when traffic is SSL-pinned, encrypted, or absent. Covers APK/IPA decompile for hardcoded secrets + hidden API endpoints + base URLs the web app never exposes, exported-activity and deeplink intent injection, WebView addJavascriptInterface bridge abuse, SSL pinning bypass (objection patchapk / Frida CertificatePinner + checkServerTrusted hooks), OkHttp interceptor chain to recover request signing, JNI native-lib triage, and the quick apktool/grep secret + endpoint sweep. Use when the program scope includes a mobile app, when web recon dries up and you need a fresh attack surface, or when traffic is pinned and you must MitM it.

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Security payloads, bypass tables, wordlists, gf pattern names, always-rejected bug list, and conditionally-valid-with-chain table. Use when you need specific payloads for XSS/SSRF/SQLi/XXE/NoSQLi/command injection/SSTI/IDOR/path-traversal/HTTP smuggling/WebSocket/MFA bypass, bypass techniques, or to check if a finding is submittable. Also use when asked about what NOT to submit.

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Finding validation before writing any report — 7-Question Gate (all 7 questions), 4 pre-submission gates, always-rejected list, conditionally valid with chain table, CVSS 3.1 quick reference, severity decision guide, report title formula, 60-second pre-submit checklist. Use BEFORE writing any report. One wrong answer = kill the finding and move on. Saves N/A ratio.

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Post-access cloud exploitation for AWS, GCP, and Azure — what to do AFTER you obtain credentials or reach a metadata endpoint. Covers IAM enumeration and privilege escalation (iam:PassRole, CreatePolicyVersion, AssumeRole chains, GCP service-account impersonation, Azure managed-identity abuse), IMDSv1/v2 metadata credential theft, STS token abuse, S3/GCS/Blob bucket takeover and object exfil, Lambda/Cloud Functions env-var secrets, cross-account and cross-service pivoting, and turning leaked keys into demonstrated impact (read PII, assume admin, exfil data). Assumes authorized scope only. Use when you have AWS/GCP/Azure keys, an SSRF hitting 169.254.169.254 / metadata.google.internal, a leaked service-account JSON, or a token, and need to escalate and prove impact. For finding buckets/origins first, use cloud-recon; for the SSRF entry point, see web2-vuln-classes. 中文触发词：云渗透、AWS提权、IAM枚举、元数据凭证、云安全审计

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Password spray methodology for bug bounty — when to do it vs web-vuln hunting, the wordlist-gen + breach-check + osint-employees + spray pipeline, mode selection (http-form / oauth / o365 / okta), rate-limit + lockout tactics, BBP legal guardrails, success detection, and the spray → authenticated /hunt chain pattern. Use when assessing whether credential attack is worth running on a target, picking the right mode, or recovering from common pitfalls.

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Scan AI agent skills, plugins, MCP servers, and agent tooling for prompt injection, unsafe commands, secret exposure, and supply-chain risks before installing or trusting them.

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VMware vSphere / vCenter Server external attack matrix — version fingerprinting, the high-impact CVE chain (CVE-2021-21972 vRealize unauth file upload, CVE-2021-21985 vSAN plugin RCE, CVE-2022-22954 Workspace ONE SSTI, CVE-2023-20887 Aria RCE, CVE-2024-37085 ESXi AD bypass, CVE-2023-34048 vCenter DCERPC OOB write APT-exploited), default credentials, SSO configuration disclosure, vmdir LDAP enumeration, ESXi Open SLP RCE history. ONLY for vCenter / Workspace ONE / Aria instances exposed to the internet — internal-network vCenter is out of scope per the external-only boundary. Use when recon shows port 443 with vCenter banner, `/ui` redirect, `/websso/SAML2/Metadata`, or VMware product fingerprints.

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Finding validation before writing any report — 7-Question Gate (all 7 questions), 4 pre-submission gates, always-rejected list, conditionally valid with chain table, CVSS 3.1 quick reference, severity decision guide, report title formula, 60-second pre-submit checklist. Use BEFORE writing any report. One wrong answer = kill the finding and move on. Saves N/A ratio.

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Security payloads, bypass tables, wordlists, gf pattern names, always-rejected bug list, and conditionally-valid-with-chain table. Use when you need specific payloads for XSS/SSRF/SQLi/XXE/NoSQLi/command injection/SSTI/IDOR/path-traversal/HTTP smuggling/WebSocket/MFA bypass, or bypass techniques. Submittability and the always-rejected / what-NOT-to-submit decision are owned by triage-validation.

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Okta-as-IdP red-team attack chain — tenant discovery, user enumeration (multiple vectors), authentication flow analysis (factors enumeration, push-notification fatigue, SMS bypass), password spray with lockout discipline, Okta-specific phishing primitives (kits, FastPass abuse, OIDC redirect_uri tampering), MFA enumeration, post-compromise admin API surface. Many enterprise orgs use Okta instead of (or alongside) Entra ID. Distinct endpoints, distinct rate-limiting, distinct factor flows. Use when recon shows `<tenant>.okta.com`, `<tenant>.okta-emea.com`, `<tenant>.oktapreview.com`, or autodiscover-style records pointing at Okta IdP.

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Microsoft 365 / Entra ID red-team attack chain — current 2026 reality. AADSTS code reference, user enumeration vectors (with hardening status), Smart Lockout math, Conditional Access bypass options, ROPC + SAML SSO browser flow, Burp/Playwright templates. Built from authorized red-team work where ROPC spray surfaced pre-existing lockouts and CA-blocked credentials, plus real-time external attacker activity correlation. Use for any M365/Entra credential attack, password spray, user enumeration, CA-bypass exploration, or active-attacker-detection scenario.

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End-to-end iOS red-team pipeline — IPA acquisition (App Store extraction, TestFlight, enterprise/ad-hoc sideload), class-dump/Hopper/Ghidra static analysis, Info.plist + entitlements + Keychain secret extraction, App Transport Security (ATS) misconfig + certificate-pinning bypass (frida-ios-dump, objection, SSL Kill Switch 2), URL-scheme / Universal Link hijack, exported-service enumeration, Frida runtime instrumentation. Companion to apk-redteam-pipeline for the iOS side of a mobile app catalogue. Use when target has an iOS app (App Store listing, TestFlight link, enterprise MDM distribution), when an IPA URL is found hosted on a web server, or when post-recon mentions "iOS app" / "mobile app" in scope alongside an Apple developer account.

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Hunting skill for xxe vulnerabilities. Built from 10 public bug bounty reports including SVG-upload XXE, Office-doc (PPTX/DOCX) XXE, SOAP XXE, SAML AssertionConsumer XXE, blind OOB XXE via DTD callback, parameter-entity XXE, XXE-to-LFI, XXE-to-SSRF, and XXE-to-RCE chains (Adobe Commerce CosmicSting CVE-2024-34102). Use when hunting XXE on any target — emphasis on OOB-Or-It-Didn't-Happen Gate for blind cases.

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Hunt Microsoft SharePoint Server (2013/2016/2019/Subscription Edition) on-prem farms — anonymous endpoint enumeration, version disclosure, legacy SOAP login bypass (Authentication.asmx), ToolShell precondition chain (CVE-2025-53770), SafeControl reflection enumeration via Picker.aspx, NTLM Type-2 AD topology disclosure, custom-branding module discovery, EoL farm permanent-CVE-window exploitation, FormDigest anonymous issuance, file-extension blocklist NOT-an-oracle pattern, custom-zone Forms auth bridging on-prem AD. Use when target has SharePoint headers (SPRequestGuid, X-MS-InvokeApp, X-SharePointHealthScore, MicrosoftSharePointTeamServices) or paths (/_layouts/15/, /_vti_bin/, /_api/, /_catalogs/).

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。