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Skills 列表
graph-the-network
Build an entity-relationship link-analysis graph of an investigation — nodes, typed edges carrying source and confidence, aliases, and temporal validity — to expose shared infrastructure, bridging nodes and the real principal behind a frontman. Covers Maltego, Neo4j and Cypher, Gephi, centrality and community detection, and entity resolution. Use when an investigation has outgrown a list and needs a graph, or when asked how a set of people, companies and domains connect. Applies to fraud-ring and shell-network detection, AML and sanctions-evasion analysis, and complex corporate-structure work. Reference at useosint.com/skills/graph-the-network.
useosintwhat-an-email-reveals
Investigate an email address — MX and syntactic validation, Gravatar lookup, corporate email-format inference, breach exposure, and full mail-header analysis covering the Received chain, Message-ID and SPF, DKIM and DMARC results. Use for email OSINT, verifying whether an address exists, finding accounts registered to it, guessing a company's email format, or tracing where a suspicious message actually came from. Applies to business email compromise and invoice-fraud investigation, phishing triage, vendor-payment verification, and pre-engagement research. Reference at useosint.com/skills/what-an-email-reveals.
useosintpattern-of-life-from-socials
Deep-dive a subject's social media presence — profile metadata, follower and mutual network, content analysis, and posting-time pattern of life across Instagram, Facebook, X/Twitter, TikTok, LinkedIn, Reddit, Telegram and Discord. Use when profiling a social account, mapping someone's associates, inferring a subject's timezone or routine from their posts, or archiving a profile before it is deleted. Applies to threat assessment and executive protection, insider-threat investigation, pre-litigation research, and personal exposure audits — with explicit limits on profiling uninvolved third parties. Reference at useosint.com/skills/pattern-of-life-from-socials.
useosintfind-hidden-subdomains
Enumerate an organisation's subdomains and sibling domains from Certificate Transparency logs and passive DNS, without sending traffic to the target. Covers crt.sh and CT log queries, certificate SAN fields, subfinder and amass, and newly issued TLS certificates. Use when looking for staging, dev, admin or VPN hosts, mapping the full hostname footprint of a domain, or spotting infrastructure a company forgot it had. Applies to attack-surface mapping, vendor and supply-chain security review, brand-infringement discovery, and M&A technical diligence. Reference at useosint.com/skills/find-hidden-subdomains.
useosintinvestigate-anything
Start-here router and tradecraft baseline for any investigation into a person, company, domain, image or selector. Sets authorised scope, turns a vague request into an answerable intelligence question, writes a collection plan, picks the right workflow for the starting selector, and applies source grading and competing-hypothesis discipline. Use for "investigate this person or company", "do OSINT on X", "where do I start", or any open-source intelligence, due diligence, background or attribution task. Applies across due diligence, fraud, threat intelligence, journalism and compliance. Reference at useosint.com/skills/investigate-anything.
useosintwho-really-owns-it
Research companies, directors, shareholders and ultimate beneficial ownership in official corporate registries, filings and offshore datasets — OpenCorporates, UK Companies House and the PSC register, SEC EDGAR, US Secretary of State registries, EU business registers, GLEIF LEI records, OpenOwnership, OpenSanctions and the ICIJ Offshore Leaks database. Use when asked who owns or controls a company, to find a person's other directorships, or to unpick a group structure. Applies to KYB and UBO verification, AML and sanctions screening, nominee and shell-company detection, procurement integrity, and M&A diligence. Reference at useosint.com/skills/who-really-owns-it.
useosintwhere-was-this-taken
End-to-end workflow to establish where and when a photo or video was captured and whether it is authentic — evidentiary handling, metadata extraction, reverse image search for provenance, visual geolocation, chronolocation from shadows, and manipulation checks, ending in a location finding with a stated confidence radius. Use when asked to verify where an image was taken, confirm or refute a claimed location or date, or authenticate media before relying on it. Applies to insurance claims, litigation evidence, disinformation analysis, and conflict and human-rights documentation. Reference at useosint.com/skills/where-was-this-taken.
useosintfind-leaks-in-the-wild
Find leaked or mentioned selectors circulating in pastes, leak forums, Telegram channels and dump markets, and judge whether a claimed leak is genuine or a recycled combolist. Covers paste aggregators, site: searches over paste hosts, channel indexes and leak-search services. Use when checking whether a name, email, domain or credential is circulating, verifying a breach claim made against your organisation, or setting up ongoing leak monitoring. Applies to incident response and breach triage, threat intelligence, brand and executive protection, and extortion-claim validation. Reference at useosint.com/skills/find-leaks-in-the-wild.
useosintgoogle-like-a-spy
Craft advanced search-engine queries and Google dorks to surface hidden files, documents and mentions. Covers site:, filetype:, inurl:, intitle:, intext: and before:/after: operators, verbatim search, exposed directory listings, config files, backups and open S3 buckets, and the operator differences between Google, Bing, DuckDuckGo and Yandex. Use when building a Google dork, hunting a leaked document, or searching paste sites and document repositories for a name, email or selector. Applies to data-exposure audits, pre-engagement reconnaissance, competitive and regulatory research, and insider-leak investigation. Reference at useosint.com/skills/google-like-a-spy.
useosint
upstash
Work with any Upstash SDK or tool including Redis, Box (TypeScript/JavaScript and Python), QStash, Workflow, Vector, Search, Ratelimit and the Upstash CLI. Use when the user is working with any Upstash product or SDK.
upstash
ticket-resolution
Create, triage, advance, and close HubSpot support tickets — pipeline discovery, contact/company association, priority queues, bulk stage moves, resolution close-out.
hubspot
soultrace
通过 SoulTrace API 进行性格评估。当用户想要进行性格测试、发现心理原型、了解性格特征或获取基于颜色的性格档案时使用。该 API 采用五色心理模型（白色=结构，蓝色=理解，黑色=自主，红色=强度，绿色=连接），通过贝叶斯自适应问题选择将用户分类为 25 种原型之一。触发词：性格测试、性格评估、我的性格是什么、做测试、原型测试、颜色性格、soultrace。
soultrace-ai
image-edit
在 RunComfy 上编辑图像——此技能是一个智能路由器，根据用户意图匹配 RunComfy 目录中正确的编辑模型。选择 Nano Banana Edit（批量最多 20 张，默认保持身份）、OpenAI GPT Image 2 Edit（多语言图像内文本重写、多参考合成、布局精确）、Flux Kontext Pro（单参考高保真局部编辑）或 Z-Image Turbo Inpaint（掩码驱动的精确区域编辑）。捆绑了每个模型记录的提示模式，使技能在不浪费迭代于错误模型的情况下获得更精确的编辑。通过本地 RunComfy CLI 调用 `runcomfy run <vendor>/<model>/edit`。触发词包括“图像编辑”、“编辑图像”、“图像到图像”、“i2i”、“替换背景”、“移除对象”、“重写标题”或任何明确要求编辑单张或批量图像的请求。
agentspace-soimage-to-video
在 RunComfy 上将静态图像动画化——本技能是一个智能路由器，根据用户意图匹配 RunComfy 目录中合适的 i2v 模型。对于通用动画，选择 HappyHorse 1.0 I2V（Arena 排名第一，原生音频，身份保持）；对于自定义配音唇形同步，选择 Wan 2.7 配合 `audio_url`；对于多模态动画（图像+参考视频+参考音频），选择 Seedance 2.0 Pro。每个模型都附带了文档化的提示模式，使调用者无需在错误模型上反复尝试即可获得更清晰的输出。通过本地 RunComfy CLI 调用 `runcomfy run <vendor>/<model>/image-to-video`（或端点变体）。触发词包括“image to video”、“image-to-video”、“i2v”、“animate image”、“make this move”或任何明确要求将静态图像转为视频的表述。
agentspace-sonano-banana-edit
使用 RunComfy 上的 Google Nano Banana 2（图生图编辑端点）编辑图像。本文档介绍了 Nano Banana Edit 的优势（保持主体身份、替换背景、使用空间语言进行局部编辑、最多 20 张图像的多图像批量编辑）、模式，以及何时改用 GPT Image 2 编辑 / Flux Kontext / Nano Banana 2 t2i。通过本地 RunComfy CLI 调用 `runcomfy run google/nano-banana-2/edit`。触发词为“nano banana edit”、“edit with nano banana”、“image edit nano banana”或任何明确要求使用此模型进行编辑的请求。
agentspace-sohappyhorse-1-0
使用 RunComfy 上的 HappyHorse 1.0 生成文本到视频。介绍 HappyHorse 1.0 的优势（Artificial Analysis Video Arena 排名第一，原生 1080p 并同步音频，多镜头角色一致性，支持 6 种语言提示），时长/宽高比/分辨率方案，以及何时改用 Wan 2.7 / Seedance 2 / LTX 2。通过本地 RunComfy CLI 调用 `runcomfy run happyhorse/happyhorse-1-0/text-to-video`。触发词包括“happyhorse”、“happy horse”、“happyhorse 1.0”、“happyhorse video”或任何明确要求使用此模型生成视频的请求。
agentspace-sogpt-image-edit
使用RunComfy上的OpenAI GPT Image 2（ChatGPT Images 2.0的`/edit`端点）编辑图像——捆绑了该模型有文档记录的提示模式，使技能比对该模型进行简单提示获得更精确的输出。记录了GPT Image Edit的优势（保留语言、多语言图像内文本编辑、最多10张图像的多参考、布局/排版精度）、模式，以及何时转向Nano Banana Edit / Flux Kontext / GPT Image 2 t2i。通过本地RunComfy CLI调用`runcomfy run openai/gpt-image-2/edit`。触发词包括“gpt image edit”、“gpt-image-edit”、“chatgpt image edit”、“edit with gpt image 2”，或任何明确要求使用此模型编辑的请求。
agentspace-sovideo-edit
在 RunComfy 上编辑现有视频——此技能是一个智能路由器，根据用户意图匹配 RunComfy 目录中正确的编辑模型。选择 Wan 2.7 Edit-Video（通用重风格/背景替换/包装替换，身份和动作保留）、Kling 2.6 Pro Motion Control（将参考视频的精确动作转移到目标角色）或 Lucy Edit Restyle（轻量级身份稳定重风格/服装替换）。捆绑每个模型记录的提示模式，使技能获得更精确的编辑，而无需在错误模型上反复尝试。通过本地 RunComfy CLI 调用 `runcomfy run <vendor>/<model>/<endpoint>`。触发词包括“视频编辑”、“编辑视频”、“重风格视频”、“交换视频背景”、“动作控制”、“视频服装交换”或任何明确的视频转换请求。
agentspace-soflux-kontext
使用 RunComfy 上的 Flux 1 Kontext Pro（Black Forest Labs 的精确局部图像编辑模型）编辑图像——该技能捆绑了模型文档中记录的提示模式，因此比针对同一模型进行简单提示能获得更清晰的结果。文档介绍了 Flux Kontext 的优势（单参考精确局部编辑、强大的提示控制、一致的高保真输出）、模式（单图像 + 提示），以及何时改用 Nano Banana Edit / GPT Image 2 edit / Flux 2 Klein。通过本地 RunComfy CLI 调用 `runcomfy run blackforestlabs/flux-1-kontext/pro/edit`。触发词为 "flux kontext"、"flux-kontext"、"flux 1 kontext"、"kontext"、"BFL kontext" 或任何明确要求使用此模型进行编辑的请求。
agentspace-sonano-banana-2
使用 RunComfy 上的 Google Nano Banana 2（Gemini 系列闪级文生图模型）生成图像——技能内置了模型文档中的提示词模式，因此输出比直接使用同一模型更精准。文档介绍了 Nano Banana 2 的优势（快速迭代、图像内文字渲染、可预测构图、可选的网络搜索上下文）、分辨率等级定价、安全容忍度调节，以及何时改用 Nano Banana Pro / GPT Image 2 / Flux 2 / Seedream。通过本地 RunComfy CLI 调用 `runcomfy run google/nano-banana-2/text-to-image`。触发词包括“nano banana”、“nano-banana-2”、“nano banana 2”、“google image gen”、“gemini image”或任何明确要求使用此模型生成图像的请求。
agentspace-sowan-2-7
使用 Wan 2.7（Wan-AI 的旗舰运动模型）在 RunComfy 上生成文本到视频。文档介绍了 Wan 2.7 的优势（多参考条件、通过 `audio_url` 实现音频驱动的唇形同步、更平滑的过渡、提示扩展）、时长/分辨率/宽高比模式，以及何时改用 HappyHorse 1.0 / Seedance 2.0 / Kling / LTX 2。通过本地 RunComfy CLI 调用 `runcomfy run wan-ai/wan-2-7/text-to-video`。触发词为“wan”、“wan 2.7”、“wan-2-7”、“wan video”或任何明确要求使用此模型生成视频的请求。
agentspace-soflux-2-klein
使用 RunComfy 上的 Flux 2 Klein（Black Forest Labs 的 Flux 2 蒸馏快速变体）生成图像——捆绑了模型文档化的提示模式，使技能比针对同一模型的朴素提示获得更清晰的输出。记录了 Flux 2 Klein 的优势（亚秒级延迟、多参考品牌样式、声明式主体优先提示）、步数策略（4–8 步快速迭代，约 25 步精修）、9B 与 4B 变体的权衡，以及何时改用 Flux 2 Pro / Seedream 5 / GPT Image 2。通过本地 RunComfy CLI 调用 `runcomfy run blackforestlabs/flux-2-klein/9b/text-to-image`（或 `/4b/`）。触发词为 "flux 2 klein"、"flux-2-klein"、"flux klein"、"BFL flux 2" 或任何明确要求使用此模型生成的请求。
agentspace-soseedance-v2
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agentspace-so
mcp-configure
在引导过程中配置 LaunchDarkly 托管的 MCP 服务器。当父级 LaunchDarkly 引导技能到达步骤 4（MCP）时使用。支持 Cursor、Claude Code、Windsurf、GitHub Copilot 以及其他兼容 MCP 的代理。使用 OAuth 认证；托管服务器无需 API 密钥。
launchdarkly