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Methodology for detecting client SOC patches, attacker activity, and security-state changes that occur DURING a red-team engagement — and converting those observations into deliverable findings. Built from authorized red-team work where the client patched a confirmed SQLi within 30 minutes of detection AND an external attacker locked multiple new accounts during a single test session. Use when (a) running ANY active engagement against a monitored target, (b) a previously-confirmed finding stops reproducing, (c) baseline timing shifts unexpectedly, or (d) you notice response patterns changing during testing.

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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/).

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Draft a new LinkedIn post from scratch using one of 20 2026 hook formulas (anaphora, R.I.P., time-anchor, curiosity-gap, contrarian, controlled A/B, false-binary, and more) plus a founders-edition angle library, picked by engagement goal (comments, reposts, likes, saves). Runs the humanizer pass and schedules via Publora on approval. Use to write a post, find a hook or proven format, or get founder-specific angles. Not for reviewing existing drafts (use linkedin-humanizer --mode audit).

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Track which of your LinkedIn comments earned author replies. Flags the 6-24h warm-reply window where thread momentum peaks, classifies threads as hot/warm/cool/dormant, and routes warm ones to linkedin-reply-handler for follow-up drafts. Powered by Apify, no LinkedIn login. Triggers on "what threads need follow-up", "author replied", "monitor my comments". Not for analyzing likers on a post (use linkedin-engager-analytics).

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Plan, draft, audit, and publish LinkedIn posts and comments. Use when the user wants to write a viral LinkedIn post, draft a comment or reply on any LinkedIn post URL, audit a draft against 2026 algorithm heuristics, remove AI tells, extract hook formulas from viral posts, or plan a week of content. Powered by the Publora API for publishing. User provides post/comment URLs, skill drafts content, user approves, then publishes.

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VS-Enhanced Academic Style Auditor - Academic Writing Quality Analysis Identifies 24+ writing patterns that reduce scholarly quality, adapted from Wikipedia AI Cleanup guidelines Use when: checking drafts before submission, improving academic writing quality, preparing for style improvement Triggers: writing quality, style audit, pattern check, writing review, academic style check

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Generate a complete academic literature survey from scratch using multi-agent orchestration. Searches academic databases (OpenAlex, CrossRef, Unpaywall), downloads PDFs, builds BibTeX, drafts a LaTeX review, compiles it, reviews for quality, and revises based on feedback — all automated. Use this skill whenever the user asks to "generate a literature review", "write a survey paper", "review recent papers on [topic]", "create a survey of [field]", "综述", "文献综述", "survey papers in top journals", or wants a multi-agent pipeline to produce a publishable-quality literature review. Also trigger when the user wants to search multiple journals for papers on a topic and synthesize findings into a structured document. Works for any academic field but optimized for economics journals.

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How to work in a Writing Pipeline project (the `writing-pipeline` starter pack): a three-stage drafting flow, ideas → drafts → published. Read when the project has these folders, OR when asked to capture an idea, start or revise a draft, review a piece before it ships, or publish it. Carries the stage flow and review behaviors so that guidance does not live inside template bodies or folder descriptions. Complements the platform `open-knowledge` skill; does not replace it.

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Runs your conversion data through different attribution models side by side — last click, first click, linear, time decay, position based, and data-driven. Shows you how credit shifts between campaigns depending on the model so you can make better budget decisions instead of over-investing in last-touch campaigns. Platform: Google and Meta.

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Track how AI assistants describe your brand over time and catch wrong, outdated, or damaging claims. Claude builds your monitoring prompt set, compares runs week over week, and drafts the correction plan when answers drift. Platform: AI visibility.

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Catches unusual performance changes across your accounts — CPC spikes, CVR drops, spend surges, impression collapses, CTR shifts — and flags them with context about what likely changed. The goal is to catch problems in hours instead of discovering them days later during a routine check. Platform: Google and Meta.

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When your CPA spikes, Claude breaks down exactly what caused it. It looks across your campaign data and isolates the contributing factors — audience fatigue, bid landscape shifts, creative decay, landing page conversion drops, budget distribution changes, or new competitor activity. Platform: Google and Meta.

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Activate this skill for ANY future-oriented question. Triggers include: "Will [X]?", "Who will win [X]?", "What happens to [X]?", "Can [X] succeed?", "What's the future of X?", foresight analysis, scenario planning, STEEEP analysis, futures cone, prediction requests, or any question about a future outcome. Year is NOT required — the engine infers the horizon. Also activate when the user says "predict", "forecast", "what are the odds", "scenario analysis", or asks about competitive races, technology adoption, geopolitical shifts, or market dominance. REQUIRES web search to be enabled — if web search is unavailable, tell the user before proceeding.

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Activate this agent for any future-oriented question that requires deep quantitative analysis, historical precedents, and structured scenario planning. Triggers include: "Will [X]?", "Who will win [X]?", "What happens to [X]?", prediction requests with high stakes, foresight analysis, STEEEP scenario planning, futures cone, competitive race analysis, technology adoption curves, geopolitical shifts, or any question about a future outcome that deserves rigorous multi-step analysis. This agent runs a 12-step deterministic pipeline: Claude handles intelligence, Python handles all arithmetic. Year is NOT required — the engine infers the horizon. REQUIRES: Bash tool + Python 3.x. Not compatible with claude.ai web (use Soft Predict Future instead).

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Automate Gmail tasks via Rube MCP (Composio): send/reply, search, labels, drafts, attachments. Always search tools first for current schemas.

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Use this skill when the user is operating the DOCA Firefly Service container on BlueField — picking the four PTP configuration axes (role / profile / domain / interface), wiring the BlueField PHC + host follower + consumer workload pairing, deciding whether PTP-grade time is even needed (vs. chrony / NTP), or debugging a Firefly deployment where PTP isn't syncing or the host clock isn't following. Trigger even when the user does not explicitly mention "DOCA Firefly" or "PTP" — typical implicit phrasings include "container green but PTP never advances past LISTENING", "Firefly says synced but the host clock still drifts", "sync acquired but offset is tens of microseconds", "my Rivermax SMPTE workload needs PTP", or "is chrony good enough". Refuse and route elsewhere for installing DOCA, host-side chrony / ptp4l config bodies, PTP topology / boundary-clock design, building DOCA apps that read the disciplined PHC, or other DOCA services (DMS, Flow-Inspector, HBN) — those belong to other skills.

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Plan vault restructuring from config changes. Compares config.yaml against derivation.md, identifies dimension shifts, shows restructuring plan, executes on approval. Triggers on "/refactor", "restructure vault".

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Analyze how a private SaaS company's ARR valuation multiple changed across funding rounds, and attribute the compression or expansion to rate cycles and macro selloffs, growth deceleration, narrative shifts (including an AI premium), competition, and investor demand, benchmarked against private-market medians and peers. Use this skill whenever the user asks about valuation compression, ARR multiples, round-to-round valuation or multiple changes, down rounds, or wants to compare a VC-backed software company's funding rounds. Research the rounds rather than answering from memory.

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Drafting campaigns and ads as staged drafts, from acquisition and seasonal pushes to lifecycle sends such as win-backs, pre-arrival messages, and presale or last-call notices, choosing audiences and placements by intent, allocating budget across campaigns, and reviewing campaign results with their attribution caveats. Not needed for listing copy (catalog-listings) or overall performance questions (performance-insights).

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Analyzes isoform switching events and functional consequences using IsoformSwitchAnalyzeR. Predicts protein domain changes, NMD sensitivity, ORF alterations, and coding potential shifts between conditions. Use when investigating how splicing changes affect protein function.

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Detect structural macro regime transitions (1-2 year horizon) using cross-asset ratio analysis. Analyze RSP/SPY concentration, yield curve, credit conditions, size factor, equity-bond relationship, and sector rotation to identify regime shifts between Concentration, Broadening, Contraction, Inflationary, and Transitional states. Run when user asks about macro regime, market regime change, structural rotation, or long-term market positioning.

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Use when the user asks to "package the launch assets", "build a press kit", or "prep the store listing and go-live checklist"; produces a tier-scoped launch asset manifest with production status — a press kit spec (factsheet, description, history, features, videos, images, logo and icon, awards, contact), demo script and screenshot specs, a launch FAQ, dual-store listing metadata drafts against the official character budgets (per App Store Connect / Play Console documentation), and a technical go-live checklist manifest (robots flip, sitemap, OG tags, analytics verification — execution stays with technical-seo-checker and serp-markup-builder). Not for the message copy itself — use message-house-builder or content-writer; not for landing page UX — use landing-optimizer; not for keyword research beyond the store surfaces — use keyword-research. 发布资产打包/press kit/商店listing规格/上线检查清单

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Use when the user asks to "write SEO content", "draft a blog post / landing page", "update outdated content", or "fix traffic/ranking decay"; two modes — new drafts pages with keywords, headers, snippets, and evidence boundaries; refresh scores decay, prioritizes update work, and produces a republish plan with GEO guidance. Not for AI-citation/GEO readiness scoring — use geo-content-optimizer; not for publish-gate scoring — use content-quality-auditor. SEO文章写作/内容更新/排名恢复

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Optimize Core Web Vitals (LCP, INP, CLS) for better page experience using field and lab evidence. Use when asked to "improve Core Web Vitals", "fix LCP", "reduce CLS", "optimize INP", "page experience optimization", or "fix layout shifts".

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