對入站 Lark 附件進行邊界測試 — 使用者傳送圖片或檔案並附上此指令時，機器人會精確報告其在聊天路徑上能觀察到的內容（僅文字、附件參考，或無），而不進行猜測。能偵測平台何時啟用聊天路徑的附件可見性，以便依賴此功能的技能可進行升級。
這個技能是一個用於 Lark 平台的邊界測試工具，專門測試入站附件的可見性。當使用者同時傳送圖片或檔案以及此指令時，機器人會直接報告它在聊天路徑上實際觀察到的內容，包括僅有文字、存在附件參考，或完全沒有任何附件資訊。它不會進行任何猜測，而是提供確定性的觀察結果。這對於需要依賴附件可見性來運作的技能（例如檔案處理或圖像分析技能）特別有用，因為它能明確指出平台何時開始將附件資訊傳遞到聊天路徑上。透過使用此技能，開發者可以確認平台行為的變化，並據此升級依賴技能以利用新功能。此技能支援 Lark 平台，並以 CLI 或對話方式觸發。
npx skills add https://github.com/ChronoAIProject/nyx-skills/tree/main/aevatar-attachment-probe對入站 Lark 附件進行邊界測試 — 使用者傳送圖片或檔案並附上此指令時，機器人會精確報告其在聊天路徑上能觀察到的內容（僅文字、附件參考，或無），而不進行猜測。能偵測平台何時啟用聊天路徑的附件可見性，以便依賴此功能的技能可進行升級。
傳送一張圖片或一個檔案，並在訊息中附上 aevatar-attachment-probe 指令。機器人會回覆一份報告，說明它在聊天路徑上觀察到的內容。
此技能會檢查聊天訊息中是否包含附件參考（如圖片或檔案 URL），並根據觀察結果回覆。它不會執行任何額外的處理或分析，僅提供事實性的觀察。
This repo contains 9 individual skills — each has its own dedicated page.
Verify the read-image (vision) path end to end — the user sends an image plus the trigger, a workflow vision step describes it, and the run output proves the model actually saw the image (a real description, not "no image received"). Run it before any image-dependent workflow (petty-cash receipt, invoice OCR).
Use when answering mathematical, conceptual, philosophical, or metaphysical questions through repository-first scientific reasoning, a clause-complete formal bridge, retained exact Lean specializations, reusable library growth, and an ordinary conversational answer; the formal work stays internal and is shown only when the user asks for it.
Send, reply to, react to, read, and find Lark messages and chats through the bot's NyxID-brokered im/v1 APIs — proactively post to a chat or DM, thread-reply, add or remove emoji reactions, read a single message or pull a chat's history over a time window, search or list the chats the bot is in, and download an image/file from a message. Handles the "content must be a JSON string" footgun and receive_id_type selection, and doubles as the im-scope probe — on a scope 403 it reports the exact missing permission instead of failing silently.
Verify-first promotion intelligence for ANY repo or org. Pulls live GitHub state, runs sshx multi-perspective consensus over it, and returns an evidence-backed board of what is genuinely promotable, how items connect, and what is unverifiable. Use when an agent or operator asks "what's worth promoting / what connects / what's real" for a target repo or org.
Method for producing short vertical videos from ChatGPT image generation through a fixed browser tab, local TTS narration, timed subtitle burn-in, cover exports, and a manifest. Use when an operator needs a reproducible image-to-short workflow with pinned session consistency, per-beat visual prompts, 1080x1920 safe-area rules, local ffmpeg/PIL assembly, and private access kept outside the skill.
The manual an AI agent loads to operate Ornn — the model-agnostic skill-lifecycle API (an npm-style registry + CLI for agent skills) — via the NyxID CLI (`nyxid proxy request ornn-api …`). Load and follow this skill WHENEVER the user asks to do anything with Ornn skills or skillsets. Skills: search Ornn or find a skill, pull or install a skill (or a specific version), run a skill, build and upload a skill, publish a new version, make a skill public / private / shared, run or read a security audit, deprecate or delete a version, diff two versions, check usage analytics, bind a skill to a NyxID service, link a skill to GitHub or sync from source, manage npm-style dist-tags, or transfer skill ownership. Skillsets — curated multi-skill bundles with a required master prompt: bundle skills into a set, create or publish a skillset, resolve its closure in one call, export a skillset as a Claude Code marketplace plugin, transfer skillset ownership, or diagnose why a shared skillset isn't visible (visibility derives fr
Runs the petty-cash approval flow end to end yourself — collect Lark DM/sheet/image context, extract receipt details, build the exact approval body, then SUBMIT the Lark approval instance.
Portable checklist for gating public-facing copy before release. Use when captions, posts, manifests, topics, titles, or launch copy must be checked for generic AI wording, leaked internal labels, forbidden experiment or tool names, platform topic allowlists, CTA spam, and unsupported overclaims.
Severity-weighted BLOCK, WARN, OK reviewer method for technical and research posts. Use when reviewing X threads, announcements, captions, or launch copy for hook strength, thread arc, generic AI vocabulary, source fidelity, claim support, numeric-claim verification, and thread format before recommending publish.
ElevenLabs text-to-speech with mac-style say UX.
Oracle CLI second-model review/debug/refactor/design with selected files, dry-run token checks, API or browser engine.
Capture and automate macOS UI with the Peekaboo CLI.
Generate multiple radically different interface designs for a module using parallel sub-agents. Use when user wants to design an API, explore interface options, compare module shapes, or mentions "design it twice".
Build a throwaway prototype to flesh out a design — a runnable terminal app for state/business-logic questions, or several radically different UI variations toggleable from one route.
Interview the user relentlessly about a plan or design until reaching shared understanding, resolving each branch of the decision tree. Use when user wants to stress-test a plan, get grilled on their design, or mentions "grill me".