Método de revisión con ponderación de gravedad (BLOQUEO, ADVERTENCIA, ACEPTADO) para publicaciones técnicas y de investigación. Útil al revisar hilos de X, anuncios, subtítulos o textos de lanzamiento para evaluar fuerza del gancho, arco del hilo, vocabulario genérico de IA, fidelidad de fuentes, respaldo de afirmaciones, verificación numérica y formato del hilo antes de recomendar su publicación.
Este skill proporciona un método de revisión estructurado y ponderado por gravedad para publicaciones técnicas y de investigación, especialmente en plataformas como X (Twitter). Su objetivo es evaluar la calidad, precisión y conformidad de hilos, anuncios, subtítulos y textos de lanzamiento antes de recomendar su publicación. El flujo de revisión asigna una de tres etiquetas: BLOQUEO (problemas críticos que impiden la publicación), ADVERTENCIA (problemas significativos que requieren corrección) o ACEPTADO (publicación aprobada). La evaluación cubre aspectos clave como la fuerza del gancho inicial, la estructura del arco narrativo, el uso excesivo de vocabulario genérico de IA, la fidelidad a las fuentes originales, el respaldo de afirmaciones con evidencia, la verificación de afirmaciones numéricas y el formato general del hilo. Es útil para equipos de marketing técnico, investigadores y creadores de contenido que buscan mantener altos estándares de precisión y claridad en comunicaciones públicas. Funciona como un checklist sistemático que permite filtrar contenido problemático antes de su publicación, reduciendo riesgos de desinformación o mala interpretación.
npx skills add https://github.com/ChronoAIProject/nyx-skills/tree/main/research-claim-fidelity-reviewerMétodo de revisión con ponderación de gravedad (BLOQUEO, ADVERTENCIA, ACEPTADO) para publicaciones técnicas y de investigación. Útil al revisar hilos de X, anuncios, subtítulos o textos de lanzamiento para evaluar fuerza del gancho, arco del hilo, vocabulario genérico de IA, fidelidad de fuentes, respaldo de afirmaciones, verificación numérica y formato del hilo antes de recomendar su publicación.
This repo contains 9 individual skills — each has its own dedicated page.
Boundary test for inbound Lark attachments — the user sends an image or file alongside this command and the bot reports exactly what it can observe on the chat path (text only, attachment refs, or nothing), without guessing. Detects when the platform wires chat-path attachment visibility so dependent skills can be upgraded.
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.
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.
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.
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.
Extract frames or short clips from videos using ffmpeg.
Summarize or transcribe URLs, YouTube/videos, podcasts, articles, transcripts, PDFs, and local files.
Use when testing, fixing, or extending the OpenClaw Control UI GUI with Vitest + Playwright end-to-end checks, mocked Gateway WebSocket flows, mocked dashboard runs, screenshots/videos, or agent-verifiable browser proof.
Obra superpowers agent skills.
See, Understand, Act on video and audio. See- ingest from local files, URLs, RTSP/live feeds, or live record desktop; return realtime context and playable stream links. Understand- extract frames, build visual/semantic/temporal indexes, and search moments with timestamps and auto-clips. Act- transcode and normalize (codec, fps, resolution, aspect ratio), perform timeline edits (subtitles, text/image overlays, branding, audio overlays, dubbing, translation), generate media assets (image, audio...
End-to-end marketing campaign planning and execution. Covers audience research, positioning, campaign angle definition, landing page copy, email sequences, social posts, ad copy, short-form video scripts, and content calendars. Use as the orchestration layer for multi-channel product launches. Use when planning or executing a multi-channel product launch, or producing landing page, email, social, or ad copy.