inclusionai
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- ▌ Bcs Coordination 2 · inclusionaiPublic BCS multi-bot coordination skill. Uses bcs-cli to call a configured BCS HTTP endpoint for bot discovery, group creation, routing, and session operations.
- ▌ Bcs Coordination 3 · inclusionai bundle全场景多智能体协作和交互引擎。覆盖 Bot 注册发现、自由聊天、任务协作、上下文融合、路由通信和自定义协作。用户需要自定义参与角色、执行步骤、串并行关系或最终交付物时，使用自定义协作能力，并通过 BCS 的 state_machine YAML 实现和校验。
- ▌ Alipay Payment Integration · inclusionai bundle支付宝开放平台支付产品接入最佳实践。涵盖当面付、订单码支付、App 支付、JSAPI 支付、手机网站支付、电脑网站支付、预授权支付、商家扣款等全场景产品选型与集成指导。 当用户提到"接入支付宝"、"集成支付宝支付"、"对接支付"、"支付宝收款"、"加个支付功能"、"支付宝下单"、"H5 支付"、"小程序支付"、"预授权"、"付款码"、"扫码支付"、"网页支付"、"PC 支付"、"周期扣款"、"自动续费"、"会员订阅"、"连续包月"、"代扣"时，或咨询支付产品相关报错、排查问题时使用此 Skill。
- ▌ Aenvironment Deploy · inclusionai bundleDeploy sandboxed environment instances and services using AEnvironment. Use when deploying agent instances, web services, or applications to AEnvironment sandbox infrastructure. Supports three workflows - (1) Build image locally and deploy, (2) Register existing image and deploy, (3) Deploy from registered environment. Handles instance deployment (temporary, IP-based access for agents) and service deployment (persistent, domain-based access with storage for apps).
- ▌ Ling Gui Agent Skill · inclusionai bundleConfigure and run the bundled Ling GUI Agent for vision-driven Android Appium or desktop automation on macOS, Windows, and Linux. Use when a task must interact with a real local GUI through screenshots, pointer actions, keyboard input, scrolling, or Android system actions.
- ▌ Areno Run Serving · inclusionai bundleStart, validate, debug, and stop an AReno OpenAI-compatible serving endpoint. Use for areno serve commands, API probes, streaming, cancellation, cache or CUDA graph issues, and supported image or tool-call requests. Do not use for training jobs.
- ▌ Areno Run Training · inclusionai bundleRun, configure, retry, and validate AReno SFT, DPO, GSPO, GRPO, PPO, and agentic training. Use for training commands, dataset or reward setup, smoke validation, real-step execution, checkpoint saving, or failed training retries. Do not use for serving-only tasks or framework implementation work.
- ▌ Areno Add Algorithm · inclusionai bundleAdd or modify an AReno algorithm, trainer, loss, advantage calculation, role model, or algorithm-specific configuration. Use for framework-level SFT, DPO, GSPO, GRPO, PPO, or new optimization method development. Do not use merely to run an existing algorithm.
- ▌ Areno Debug Runtime · inclusionai bundleDiagnose failed, hung, slow, OOM, NaN, illegal-memory-access, NCCL, compilation, rollout, or training runs in AReno. Use when runtime evidence must identify the first causal stage. Do not use for routine capacity planning without a failure.
- ▌ Areno Tune Capacity · inclusionai bundleFit an AReno training or rollout workload to available GPUs by tuning TP, mini-batch, batch, sample count, and rollout concurrency. Use for OOM prevention, memory headroom, smoke-infer, smoke-train, or tune-params requests. Do not change semantic token limits unless requested.
- ▌ Areno Develop Kernel · inclusionai bundleDevelop, optimize, debug, and validate an AReno CUDA, Triton, fused, attention, convolution, routing, or MoE operator. Use when changes touch areno/accel or a runtime kernel boundary and require forward, backward, dtype, layout, CUDA graph, or benchmark validation.
- ▌ Areno Model Adaptation · inclusionai bundleAdd or debug an AReno model family, including config conversion, module construction, checkpoint load/save, text or multimodal inference, training backward, tensor parallelism, CUDA graph decode, and checkpoint round trips. Use only when model-specific implementation or compatibility changes are required.
- ▌ Areno Profile Performance · inclusionai bundleMeasure and diagnose AReno rollout, prefill, decode, training, checkpoint, role-switch, communication, or Python scheduling performance. Use when throughput or step time is slow and evidence from metrics, py-spy, or Nsight is required. Do not optimize before correctness is established.
- ▌ Areno Validate Correctness · inclusionai bundleCompare an AReno branch, model, checkpoint, algorithm, scheduler, or kernel against a baseline. Use for regression validation, logprob or metric comparison, checkpoint round trips, and correctness gates. Keep performance reporting separate.
- ▌ Areno Build Agentic Workflow · inclusionai bundleCreate or debug an AReno multi-turn agentic dataset, run_agent implementation, tool schemas, tool execution, reward, loss masks, interactive TUI game with OpenAI-compatible LLM inference, or agentic training example. Use for text or multimodal agentic workflows, not ordinary single-turn rollout.
- ▌ Choruz Pr · inclusionai bundleUse before opening or completing a pull request in this repository — classify the change, add the tests its type requires, run exactly what CI will run, label it, merge only on a green "CI (linux) required", and clean up completed branches safely.
- ▌ Choruz Doc · inclusionaiCreate, restructure, review, audit, or migrate Choruz Markdown documentation (docs/, README, AGENTS.md, the in-app docs pages) using one owner per fact, tier placement, executed-operation fact-checking, current-state prose, and the repository validators. Use for new or revised docs, docs-tree organisation, and documentation-quality audits.
- ▌ Choruz Code Review · inclusionaiUse when reviewing a pull request in this repository; orients the reviewer to Choruz's standards (AGENTS.md conventions, the PR test policy, Agent Notes, the CI gates) and the review-specific checks that a green CI cannot show.
- ▌ Choruz Record Demo · inclusionaiRecord and verify a truthful Choruz product demo or browser workflow video, including real local and remote Agent interactions. Use for requested recordings, not as an automatic media requirement for every GUI pull request.
- ▌ Choruz Prose Standard · inclusionaiUse when writing, reviewing, restoring, trimming, or auditing prose in this repository, including deciding where documentation or comments are required across Markdown, Rust doc comments, JSDoc, code and test comments, agent instruction templates, prompts, diagnostics, and CLI or UI strings.
- ▌ Choruz Pre Push Checks · inclusionaiUse before pushing, marking ready for review, or claiming checks pass on a Choruz branch, to select the smallest tests and checks that cover the outgoing diff without reflexively running the full repository suite.
- ▌ Choruz Pre Simplify Audit · inclusionaiPerform the independent Choruz pre-simplify audit or re-audit of skill execution evidence, code structure and test effectiveness. Read-only and limited to the proposed change and its affected paths; not an implementation task or repository-wide cleanup.
- ▌ Choruz Archive Agent Notes · inclusionaiUse when adding, auditing, pruning, archiving, restoring, or reviewing Agent Notes in this repository; checks every new note for superseded active records, classifies implemented notes by future decision value, deletes rejected notes that no longer prevent a tempting mistake, and applies the frozen archived/{class} rules.
- ▌ Choruz CI Test Reliability · inclusionaiDesign, review, and diagnose Choruz tests and fixtures that can fail nondeterministically under CI concurrency: parallel Playwright workers sharing one PostgreSQL and one API, vitest workers, cargo tests on a shared test database, clocks, ports, and asynchronous teardown. Use when adding or changing tests with those risks, investigating a flaky CI run, or reviewing test isolation.
- ▌ Choruz Merging Stacked Prs · inclusionaiUse when landing a chain of dependent pull requests (A ← B ← C, each based on the one below) onto main, merging a PR whose base is another open PR's branch, or whenever a request mentions "stacked PRs", "PR stack", "dependent PRs", or merging several related PRs in sequence.
- ▌ Choruz Find Simplifications · inclusionaiUse when working in this repository to find non-obvious simplification candidates, remove redundant comments or implementation-heavy documentation, write proposed Agent Notes or inline TODO/FIXME/XXX notes, audit or coalesce superseded Agent Notes, or fold worthwhile simplification ideas from another branch; especially for dead, duplicated, speculative, over-built, added-then-removed, or hand-rolled-where-a-crate-exists surfaces.
- ▌ Filex · inclusionai bundleParse workspace files, HTTP(S) file URLs, or supported source URLs such as YouTube into Markdown, inspect source routing, and inspect resumable PDF batch status with the FileX CLI inside an AWorld sandbox. Use for reading, extracting, transcribing, inspecting, summarizing, or answering questions about PDF, Word, PowerPoint, Excel, CSV, text, Markdown, image, audio, or video files.
- ▌ Optimizer · inclusionaiAnalyzes and automatically optimizes existing agents by improving system prompts and tool configuration.
- ▌ Text2agent · inclusionaiCreates new agents from user requirements by generating Python implementation and mcp_config.
- ▌ Self Evolve · inclusionai bundleUse for framework-gated self-evolve workflows in AWorld: evolve skills, create trajectory-backed proposals, inspect self-evolve run artifacts, run aworld-cli optimize, or prepare verified apply decisions through aworld.self_evolve gates.
- ▌ App Evaluator · inclusionaiA professional skill for App Evaluation (evaluating app's performance with score) and App Improvement (giving professional suggestions for improving the app's performance).
- ▌ Embedded Video Pip Smooth Playback · inclusionaiPrevent stutter and frozen frames when embedding a child video inside a parent in code-driven pipelines (Remotion, After Effects scripting, FFmpeg filter graphs). Explains why sparse keyframes break frame-accurate seek during per-frame export, and how re-encoding with H.264 all-intra GOP (-g 1) and yuv420p makes every frame independently decodable. Includes FFmpeg command, parameter notes, file-size tradeoffs, and a reusable rule for any seek-heavy programmatic video workflow.
- ▌ Tikhub Youtube Search · inclusionaiLightweight TikHub YouTube search and video-detail workflow. Prioritizes single-request usage with curl or minimal Python, saves raw API JSON by default, and includes a small stdlib post-processor for CSV and simplified JSON. Use when the user wants YouTube comprehensive search results, continuation-token pagination, or structured video metadata from TikHub without a heavy wrapper.
- ▌ Tiktok Download · inclusionaiSingle-file TikTok/Douyin video download and traffic metrics via TikHub API using only httpx; optional persisted raw API JSON plus a stdlib post-processor emitting CSV and simplified JSON. Supports one URL or concurrent batch (max 10 workers). No dependency on any project codebase.
- ▌ Last 7 Days News · inclusionai bundleSearch and summarize the latest 7 days of AI news and X discussions using public sources plus browser-based X collection. Use for recent AI news, trends, X discussions, industry briefs, and summaries organized into hot topics, viewpoints, and opportunity areas.
- ▌ Tikhub Xiaohongshu Search · inclusionaiLightweight TikHub Xiaohongshu image-search workflow. Prioritizes single-request usage with curl or minimal Python, saves raw API JSON by default, and includes a small stdlib post-processor for CSV and simplified JSON. Use when the user wants Xiaohongshu keyword image search, page-based pagination, or structured note/image metadata from TikHub without a heavy wrapper.
- ▌ Media Comprehension · inclusionaiAn intelligent assistant specialized in handling media files (images/audio/video). **Only for media file analysis**, does not handle document types. Media files that can be processed: - Images: .jpg, .jpeg, .png, .gif, .bmp, .webp, .svg - Audio: .mp3, .wav, .m4a, .flac, .aac, .ogg - Video: .mp4, .avi, .mov, .mkv, .webm, .flv Files that cannot be processed (please do not trigger this skill): - Documents: .pdf, .doc, .docx, .txt, .md, .rtf - Spreadsheets: .xlsx, .xls, .csv, .tsv - Presentations: .pptx, .ppt, .key - Code: .py, .js, .ts, .java, .cpp, .go, .rs - Archives: .zip, .tar, .gz, .rar, .7z - Executables: .exe, .bin, .app, .dmg - Databases: .db, .sqlite, .sql - Configuration files: .json, .xml, .yaml, .yml, .toml, .ini - Web pages: .html, .htm, .css Trigger conditions: When the user explicitly requests to analyze image/audio/video content, or when the file extension belongs to the aforementioned media types.
- ▌ Video Storytelling Core Principles · inclusionaiCore storytelling rules for AI video scripts: concrete metaphors instead of abstract jargon, the mute test (story reads without audio), visual contrast and closure, physically visible causes of failure or success, visualizing the “eureka” beat, camera motion tied to physics, in-scene transitions instead of black cuts, character consistency and multi-speaker action/lip sync timelines, and three-act pacing with Mandarin VO speed (~4.5 chars/s) and breathing room for action and SFX.
- ▌ Ad Image Create · inclusionaiCreate ad-ready product images (single or collage) by back-solving sub-image sizes from target output ratio, grounding scene design with media_comprehension, generating images via image_generator with strict request params and actor-count control, and pairing each deliverable with a short social tagline for 小红书/抖音.
- ▌ Ad Video Create · inclusionaiCreate ad-ready product video from product images, with or without character/subject images. The workflow leverages AI-powered image composition, scene understanding, and video generation. Video prompts should follow commercial shot language—visual hooks, product presence, hero shots, detail showcase, function expression, and dynamic visuals.
- ▌ AI Video Script Sop Remotion Diffusion · inclusionaiStandard operating procedure for automated AI video production using a Remotion (code) and diffusion (model) hybrid pipeline. Covers narrative DNA (hero, show-don’t-tell, three-act arc), technical specs (duration, integer segment lengths, resolution, fps, Mandarin pacing), tech-selection matrix (diffusion vs code), a five-part diffusion prompt protocol (style, micro-timing, entities, camera, transitions), end-to-end execution workflow, and a fixed output template (metadata table + per-shot table). Complements create-video and Remotion best-practice skills for execution quality.
- ▌ X Scraper · inclusionai bundleX (Twitter) 抓取 skill - 通过 agent-browser (CDP) 抓取指定用户推文或首页推荐流，支持关键词过滤、Tab 切换、多格式输出。使用场景：按用户/关键词抓取时间线、查看首页推荐流、生成 RSS/JSON/Markdown。
- ▌ Xhs Scraper · inclusionai bundle小红书搜索抓取 skill - 通过 agent-browser (CDP) 抓取小红书搜索结果，支持列表+详情、多格式输出。使用场景：按关键词抓取笔记列表与正文、生成 RSS/JSON/Markdown。
- ▌ HTML To Image · inclusionai bundleHTML 转图片 skill - 将 HTML 文件或内容通过 agent-browser 渲染并截图为图片。适用于生成信息图、社交媒体配图、数据可视化截图等场景。
- ▌ Xhs Publisher · inclusionai bundle小红书发布 skill - 通过 agent-browser (CDP) 自动发布小红书图文笔记，支持多图上传、标题正文填写、一键发布。使用场景：自动化发布图文笔记到小红书创作中心。
- ▌ Video Subtitles And Audio Insert Workflow · inclusionaiBurn hard subtitles from UTF-8 SRT files using moviepy 2.x with CJK-capable system fonts; tune font size, placement, stroke, and encode settings (bitrate or CRF) to avoid oversized outputs. Documents ffprobe/ffmpeg workflows for inspection, encoding, and batch jobs; troubleshooting for fonts, bitrate, and pacing. Covers voiceover with edge-tts (voice selection, rate/volume/pitch), matching narration length to video with atempo/apad, and multi-scene pacing with breathing room. Targets moviepy 2.x and Python 3.x on macOS, Linux, and Windows.
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- ▌ Read Large Webpage Or Knowledge · inclusionai bundleThis skill is used for segmented reading and organization when facing large-scale knowledge bases or web pages. It captures original content segment by segment, summarizes key points in real-time, and continuously deposits them into the knowledge base, ensuring orderly information ingestion, clear structure, and traceability.
- ▌ Bcs Coordination · inclusionai bundle全场景多智能体协同和交互引擎。覆盖多Bot复杂任务协同与沉浸式娱乐互动。通过提供注册发现、群组构建、上下文融合及路由通信能力等核心能力，支持能力互补、信息和知识的融合、冲突消解、工作流编排，以及2C场景下多人游戏互动等。
- ▌ Workflow · inclusionai工作流引擎核心命令。管理工作流生命周期（创建、确认、拒绝、跳过、重试、提交、恢复），以及在人工节点等待时通过 workflow_choice 工具解读用户自然语言意图。
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- ▌ Task Loop · inclusionai bundle任务目标驱动执行闭环预装 skill,整合任务识别/规划/派发搜推/验收/BBS 接力/arch 场景规划变体(planning-arch)与架构师名册 mock(arch-analysis)共七段为单一 skill,预装到所有 bot 等同各段单独安装到对应 bot;各段按各自触发词自门控仅命中段执行(用户面 /task 或 [RESUME_TASK] 或副屏标签命中识别;框架 [planning] 命中规划,arch 场景含「某某某公司」命中 planning-arch 变体;框架 [search] 命中派发搜推;worker 叶子自验收命中验收;引擎 BBS 通知命中接力,其 scoped 叶子 instruction 含「某某某公司」时按 arch-analysis 产架构师名册)。
- ▌ Clawbench Base · inclusionai bundleRun and diagnose ClawBench evaluations through ClawMind and ClawWeb. Use when the user wants to trigger /clawbench, inspect benchmark progress, locate run artifacts, or troubleshoot evaluation execution.
- ▌ Clawevolve Pack · inclusionai bundle把当前 bot 的可变配置物料（persona md / MCP / 个人 Skill 实体与激活入口）打成不可变镜像（.zip），用于基线回归、恢复和版本管理。Skill 层支持 nested/sibling 个人目录、断链和布局错配；不打包 skills-repo/skills-center 公共只读 Skill，也不打包 ClawEvolve Release Skill。触发词：打包 bot、bot 镜像、复现 bot 环境、打镜像、baseline、回归、pack、image、版本快照、snapshot。
- ▌ Clawevolve Plan · inclusionai bundleGenerate and publish planning artifacts for an OpenClaw self-evolution loop from the canonical plan-source/v2 produced by Insight Improvement, Diagnose, or Direct Goal. Use when asked to plan from an Insight improvement, continue after diagnose, or directly turn an evolution idea into prospective eval cases, ClawBench templates, an objective, and strategy spec-v0.
- ▌ Clawevolve Tune · inclusionai bundle自进化调优 skill。用于 self-evolution loop 中，根据 objective、当前策略 spec 和 optimization bench 结果，对当前 bot/workspace 做一轮小而可解释的调优，并产出 tune_report、changed_files 和 diff。触发词：自进化调优、evolve tune、self tune、根据优化集调优、bench 后优化、round tune。
- ▌ Clawbench Report · inclusionai bundle为单次 ClawBench 评测生成 Markdown 诊断报告。通用能力由本 skill 提供；具体输入、读取优先级和评测逻辑以本次调用消息为准。
- ▌ Clawevolve Bench · inclusionai bundle以 Python workflow 方式完整运行一次 ClawWeb Bench，不依赖 ClawMind workflow；可由 ClawEvolve Step handler 或 Optimize 调用。
- ▌ Clawevolve Deploy · inclusionai bundle把 clawevolve-pack 产出的 agent 镜像（.zip）铺设到 bot workspace，复现原始 bot 的 md/mcp/skill 配置环境，并可同步恢复单次自进化 clawevolve_results/{evolve-run-id} 产物，用于基线回归与 AB 评测。三段式：校验镜像/OSS下载 → 备份当前 workspace 和 evolve run → 铺入镜像 → 校验铺出结果；失败回滚。触发词：部署镜像、加载 bot、复现 bot 环境、deploy、restore、还原 bot、铺镜像、image deploy、从OSS拉取镜像。
- ▌ Clawevolve Review · inclusionai bundleClawEvolve 结构化 Review v2。根据 post-Tune optimization、aggregate validation、acceptance 与 Tune manifest，提出需要区分的机制假设、替代原因、区分信号和保护行为；只写 review_decision.json，由 runner 渲染 evolution.spec.v1。
- ▌ Task Search · inclusionai在框架预查的候选 bot 集里决出执行者(who)与协作方式(how),返回 4 态 SearchResult(HIT_SINGLE/HIT_GROUP/HIT_MULTI_BOTS/MISS)。对齐案例剧本确定式映射。
- ▌ Clawbench Template · inclusionai bundle创建 ClawBench 评测用例模板。当用户需要设计 benchmark case、MCP 工具调用 case、skill case 或 session baseline 模板时使用。
- ▌ Clawevolve Diagnose · inclusionai bundleDiagnose a bot by analyzing a bounded range of its original OpenClaw session records according to the user-provided natural-language intent, extracting evidence-backed good and bad cases, identifying behavioral and MCP/tool-use problems, and producing structured artifacts for subsequent clawevolve-plan evolution planning. Use when receiving /clawevolve-diagnose or when asked to inspect historical bot sessions, diagnose failures, extract evaluation cases, or prepare diagnosis input for self-evolution; Session Judge supports the Bot's OpenClaw Agent by default and an optional API-key backend.
- ▌ Clawevolve Workflow · inclusionai bundleClawEvolve 运行时工作流与阶段执行器。用于在 BaaS Runner 已完成阶段路由后执行 Optimize 等进化阶段，管理阶段输入、Bench、调优、Spec、产物和 ClawWeb 状态上报。
- ▌ Task Planning · inclusionai计算任务 gap 并产出下一步可执行子任务 List[TaskSpec];gap 已闭返回空数组。对齐案例剧本 gwqie46v7hzr1w6h(存储行业尽调)确定式分解。
- ▌ Task Acceptance · inclusionai叶子节点执行时的自验收判定(方案Y:worker bot 内部自闭环),把 success/data/gaps 折叠进 execute 回投 result。聚合/根节点验收走 planning gap 计算(本 skill 不参与)。
- ▌ Arch Analysis · inclusionaimock 架构师分析。当输入含关键词「某某某公司」时被触发,直接返回一组**伪造**的该方向架构师清单(姓名/角色/职责),不联网、不真实推断。仅用于 e2e 演练,不产出任何真实人员信息。
- ▌ Task Planning Arch · inclusionai计算任务 gap 并产出下一步可执行子任务 List[TaskSpec];gap 已闭返回空数组。对齐 arch 场景(架构师名册/技术栈概览/双视角分析)确定式分解——按根目标交付物集合 + done_children 查表(参照 task-planning storage 特例,非自由 LLM 分解)。
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- ▌ Bbs Relay Single Task · inclusionai bundleBBS 接力单任务版:收到引擎主动通知(含内联任务态快照)后,据快照归纳剩余事项→attach→执行→result(dashboard 仅兜底)。