Skills de Claude Code · página 76

Find Twitter/X influencers to promote a product or brand. Use when asked to find influencers, discover Twitter accounts for partnerships, identify creators in a niche, or build an influencer outreach list.

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Get company logos, brand colors, fonts, and style guides

Scrape competitor ads from Google Ads by domain. Returns ad creatives, formats, and campaign details. Use for competitive ad research and messaging analysis.

AI-agent-powered lead enrichment using Sixtyfour as primary source. Takes an email (+ optional name) and returns comprehensive person + company data with funding, AI/B2B classification, and full error visibility. Higher cost (~$0.20/lead) but simpler architecture.

Multi-provider waterfall lead enrichment. Takes an email (+ optional name) and returns person + company data by cross-referencing cheap APIs first, using expensive AI agents only as fallback. Cost-efficient (~$0.04-$0.10/lead) with confidence scoring and full error visibility.

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Hyperlocal weather data - precipitation, temperature, wind, soil moisture and more

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Identity verification via phone/email OTP and AML screening using Didit API

Analyze images with AI - extract text, describe content, detect objects

Get Instagram profiles, posts, and reels

Prepare for investor calls by pulling upcoming meetings from Google Calendar, deeply researching each investor and their firm (website scraping, portfolio analysis, thesis extraction), checking for competitor conflicts, and outputting an honest prep sheet with compatibility assessments. Use when asked to prep for investor meetings, fundraising calls, VC meetings, or demo day.

Research VCs, angels, and investors - portfolio, thesis, contact info

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Search for jobs matching your skills, experience, and preferences

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AI-powered lead enrichment - find emails, phones, and enrich company/lead data

Enrich leads with email, phone, company data using multiple data sources

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Get LinkedIn profiles, company pages, and posts

Find speakers, hosts, and guest profiles at conferences and events on Luma. Two modes - free direct scrape for hosts, or Apify-powered search for full guest profiles with LinkedIn/Twitter/bio.

Research market trends, size, competitors, and growth opportunities

Scrape competitor ads from Meta's Ad Library (Facebook, Instagram, Messenger, Threads, WhatsApp). Search by company name, Facebook Page URL, or keyword. Returns ad creatives, spend estimates, reach, impressions, and campaign details. Use for competitive ad research, messaging analysis, and creative inspiration.

Multi-platform search - YouTube, Amazon, eBay, Walmart, TikTok, Instagram, and more

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Process PDFs - extract text, tables, and structured data from documents

Generate a single photoreal or designed image with OpenAI gpt-image via fal.ai. Supports gpt-image-1 (default, fixed sizes — the FAL fallback for Higgsfield's `gpt_image_2`) and gpt-image-2 (`openai/gpt-image-2`, custom output sizes up to 3840px). Routes to text-to-image or the edit variant depending on whether a reference image is provided. Use for photoreal character anchors, scene keyframes, and designed sheets (e.g. storyboards) where precise layout and legible text matter.

QC gate for a generated static ad image — verify the file opens, matches the requested dimensions, shows the correct product/subject (right shape, colour, label, logo), and has no garbled text or severe artifacts. Records pass/fail/needs-human in verification.md. Used as the final check in the static ad remix flow before shipping.

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For paid lead-gen and participant-recruitment ads, replaces vanity CPA with true CAC per qualified lead by joining ad-platform data with downstream funnel events, surfaces tracking gaps, and classifies every creative into Scale / Keep / Investigate / Cut.

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Research a company or brand from its website and produce a reusable Brand Core covering products, audience, competitors, positioning, offers, messaging evidence, voice, and visual identity. Use before growth, ad, content, creator, or product work when reliable brand context is missing.

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Given the path to a finished content-goose ad-run folder, extract everything that defines that ad — recipe shot list, VO script, characters, voices, world, atom-skills, master mp4 — and emit a `source-sample.json` in the exact shape the `upload-ad-sample` skill writes to the Goose Ads library. Also links every character and voice to the central character library at `<repo-root>/assets/character-library/` (repo-root derived from the run-dir, not a hardcoded path), and if a character isn't in the library yet, adds it first then links. Use when the user wants to remix one of their existing ads — this skill produces the source JSON that the script-rewriting step and `remix-ad` consume.

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Pre-flight policy check for Meta ads. Takes ad copy plus advertiser context, resolves and fetches the relevant Meta transparency-center policy pages at runtime, and returns a Pass / Fix Required / Block verdict with cited findings and rewrites.

Diagnose Meta Ads campaign performance and account gaps using Meta's actual system mechanics — including customer-journey coverage, Breakdown Effect, Learning Phase, Auction Overlap, Pacing, and Creative Fatigue. Use for performance diagnosis, account audits, full-funnel or TOF/MOF/BOF gap analysis, deciding what to test or create next, and producing novice-friendly recommendations without forcing every campaign or ad into a funnel stage.

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Recreate a static graphic ad (Pinterest pin, IG/FB feed image, poster) from a reference image, swapping in a new brand's product and new copy while keeping the reference's layout, composition, and visual energy. ALWAYS generated with GPT Image 2 in edit-the-reference mode (fal-ai/gpt-image-1/edit-image, a billed FAL generation); the HTML/goose-graphics overlay is only an optional text-finishing step, never the generator. The static-graphics counterpart to the video remix-ad skill; this is what the app calls when a user picks a reference ad and wants it for their own product.

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Best practices for Remotion - Video creation in React

Create polished terminal GIF recordings using VHS (Video Hardware Software) by Charmbracelet. Use when asked to create terminal demos, CLI gifs, command-line recordings, or animated terminal screenshots for documentation, READMEs, or marketing.

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Portable visual skill pack for the Agent Skills ecosystem (Claude Code, Claude Desktop, Claude Cowork, Claude Design, Goose, Cursor, Codex). Discovers community-published styles + formats via the gooseworks CLI, runs an extract-style workflow on reference images, and exports rendered PNGs via Playwright.

Generates Instagram Reels where product image cuts are synced to audio beats. Accepts audio as a local file, URL, or search query. Uses librosa for beat detection, FFmpeg Ken Burns for scene animation, and Pillow for text overlays. No AI video generation — fully free, fast, and scalable.

Generates Instagram-ready product reels from any e-commerce product page URL. Scrapes product images, classifies by type, generates AI-animated clips via Higgsfield API, creates text overlays with style presets, and composes a 15-20 second reel with music. Supports model-based and product-only reels.

Creates talking head videos from any source material (docs, changelogs, blog posts, notes, transcripts). Produces multi-scene videos with avatar narration over screenshots/images using HeyGen v2 API. Supports Quick Shot and Full Producer modes.

Repurposes long-form video (podcasts, interviews, talks) into short-form vertical clips for Instagram Reels, TikTok, and YouTube Shorts. Handles transcription, moment selection, clip extraction, speaker-tracked reframing (16:9 to 9:16), and animated captions.

Takes an existing screen recording or demo video and adds professional zoom/pan effects synchronized to the narration. Uses transcript-driven zoom targeting and Remotion for rendering. Optionally replaces audio with a soundtrack.

Maintain a brand kit — the canonical brand context an ad or content pipeline reads (positioning, audience, voice, standing instructions, brand-type, value-props, colors), plus manage the product list and attach product photos. Use when someone says "update my brand kit", "set my brand voice/audience", "add a product to my brand", or hands you a folder of product shots to attach. Platform-agnostic: it teaches the field model, partial-update/clear semantics, override behavior, caps and validation, and the hero-image and product-matching rules — independent of any specific backend.

Generate or edit an image via any FAL image model (nano-banana edit, gpt-image, flux, ...), ROUTED THROUGH THE fal-proxy so it bills the Ads agent. image_urls must be public URLs (orchestrator hosts local product refs via MCP upload->presign). The recipe names the model + prompt. Use for keyframes, flat-cover transforms, product hero edits. (For the OpenAI gpt-image family specifically, create-image-gpt-image-fal also exists.)

Generate an instrumental music bed via ElevenLabs Music, ROUTED THROUGH THE elevenlabs-proxy so it bills the Ads agent. Trims any sparse intro, loudnorm, fades the tail. Prompt + length from the template recipe. Use for the music layer of any video-ad format.

Image-to-video (or text-to-video) via any FAL video model (Kling, Seedance, Veo), ROUTED THROUGH THE GooseWorks fal-proxy so the call bills the Ads agent. The template recipe names the model + params; image_url inputs must be public URLs (the orchestrator hosts local frames via MCP get_upload_url -> get_download_url). Returns the result video URL and downloads it. Use for the generative base clip of any video-ad format.

Generate a voiceover (VO) clip via ElevenLabs text-to-speech, ROUTED THROUGH THE elevenlabs-proxy so it bills the Ads agent. Voice id + script text come from the template recipe. Use for the spoken narration of VO-driven video-ad formats (cgi-app-sizzle, flat-vector-explainer, hypermotion). Never call ElevenLabs directly — the proxy attribution is required.

Shared helper that routes ALL paid media generation (FAL image/video, ElevenLabs music) through the GooseWorks proxies so every call bills the Ads agent — never a provider SDK's default host. Host-swaps the FAL queue URLs, loads the agent token from ~/.gooseworks/credentials.json, and returns the result CDN URL. Every video-ad media capability imports this; templates never call a provider directly.

Assemble a glossy 3D-character animated-explainer video ad (~77s, 9:16) built on an "N types of X" listicle spine — a recurring human protagonist plus a locked cast of N persona characters, one per list item. Given the per-scene i2v clips + a per-scene target-duration table + a narration track, it trims each clip to its scene window, re-encodes every segment to identical 1080x1920/30fps/libx264/yuv420p (decrease+pad, never crop) so the concat demuxer never drops frames, concats, and muxes audio — in RESTYLE mode the source ad's VO+music mix is reused verbatim, in ORIGINAL mode fresh per-scene VO (loudnorm I=-14) is mixed under an optional music bed (loudnorm I=-26). A static-still fallback loops a scene's keyframe when its clip is missing/failed, so the master always assembles; libass captions are burned last. FREE deterministic assembly (Python + ffmpeg, no bash, no paid calls); the recipe supplies the clips, keyframes, VO or source audio, and caption table and gates the paid cast-anchor/keyframe/Kling-i2v/VO/music calls to their own capabilities. Use for the 3d-character-explainer listicle format.

Assemble a premium 3D product-showcase ad from a config — four beat clips (an orbiting hero rotation, a macro push-in, a physics reveal, a typographic close) normalized to the brand-color canvas, hard-concatenated in order, closed on a deterministic Playwright brand end card, and mixed under one instrumental bed at loudnorm I=-16 (music-only, no VO). Ships the runnable build_endcard.py + build_masters.py; the rotation/macro clips are create-video-fal i2v seeded on a create-image-fal styled hero, the reveal is Veo3 i2v, and the bed is create-music-elevenlabs. Use for the 3d-product-showcase format.

Assemble an absurdist animated-explainer video ad (~38s, 9:16) from per-scene i2v clips + their measured VO windows — retime each clip to its VO, re-encode every segment to identical 30fps/libx264/yuv420p so the concat demuxer never drops frames, concat, build a REAL-product PIL end card (never AI) with a slow Ken-Burns, mix VO (loudnorm I=-14) under music (loudnorm I=-26, volume 0.62, amix normalize=0), and burn libass captions last. FREE deterministic assembly (bash-free, Python + ffmpeg + PIL); the recipe supplies the clips, VO, music, product photo, palette, and caption table and gates the paid keyframe/clip/VO/music calls to their own capabilities. Use for the absurdist-explainer format.

Assemble a viral iOS "AirDrop" notification-carousel video ad (≈6–8s, 9:16) from a brand line plus 6–16 real product photos — a native AirDrop share-sheet card ("Brand would like to share a ___ · Decline / Accept") springs up and its preview window CYCLES through the products, landing on a range/lineup payoff with an Accept tap; a chime + soft per-swap ticks track the swaps. DETERMINISTIC assembly — an HTML card (real DOM text) rendered to PNG via headless Chrome, chroma-keyed, its magenta window refilled per-product in PIL, then animated + audio-synthed with FFmpeg. FREE (no paid model calls); the recipe supplies the brand line, product images, and payoff and gates the only optional paid step (a hero shot when the brand has NO usable photo → create-image-fal). Use for the airdrop-notification-carousel format.

Render a 'brand identity reveal' video from a config — a single poster frame in a real, softly-lit space (real wall, soft-focus plant in the corner, dappled leaf shadow, illuminated poster) whose artwork HARD-CUTS through ~10 on-brand poster mockups (hero product, IG post, hanging banners, sticker sheet, logo lockup, poster, two lifestyle stills, packaging, big icon) then holds on a brand end card. The environment plate is one create-image-fal generation; the mockups are real-DOM HTML frame-stepped via Playwright, perspective-composited into the detected frame quad with the plate's real leaf-shadow multiplied back onto each poster (reads as behind glass), sequenced by FFmpeg. Deterministic assembly, FREE (the plate comes from create-image-fal, the bed from create-music-elevenlabs), music bed only and approved brand copy only. Use for the brand-identity-reveal format.

Assemble a cartoon / animated / hand-crafted music-video ad from a config — a sung song carries the whole narrative while N per-bar i2v clips (one recurring animated character, one look pack) are each cut to their BAR window from librosa beat-tracking and hard-concatenated on the bar, VEED-whisper white bold-sans captions in the BOTTOM third (Alignment 2, above the logo bug, no pill) burned from the song's word timings re-spelled against the locked lyrics, a persistent brand logo bug held over the body (suppressed on the end card), and closed on a solid-brand-color PIL end card with the song still playing under it — never AI-rendered text. This is the FREE deterministic assembly stage (cut-to-bar + hard concat + logo bug + captions + end card + song mux); the song, character, keyframes, and clips come from create-music-elevenlabs / create-image-fal / create-video-fal. Use for the cartoon-music-video format.

Assemble a 3D-CGI app sizzle — nano-banana CGI plates (blank-glow floating phone + smoky-black studio + amaranth rim-light + placeholder burst shapes) plus PIL compositing of the REAL App Store screenshots onto the bezel + burst-out overlays, driven by Kling 3.0 i2v steady-float per beat with a per-beat Ken-Burns FFmpeg push-in fallback when Kling garbles the UI, then VO/music mix (sidechain duck, loudnorm) + 1.15x speed + anti-AI grain finalize. The on-screen UI, instructor faces, and wordmark are ALWAYS real assets composited via PIL — never AI-rendered. The paid steps (plates, i2v clips, VO, music) are separate capabilities; this ships the config + PIPELINE + FREE assembly and the recipe orchestrates the spend. Use for the cgi-app-sizzle video format.

Assemble a ChatGPT chat-reveal video ad from a thread + timeline JSON — one continuous Playwright recording of a ChatGPT mobile chat (user types with the iOS keyboard up → taps send → keyboard slides down + header cluster swaps in one beat → one gray loading dot → the assistant answer streams in word-by-word) crossfaded into a designed end card, with subliminal ChatGPT SFX and an optional ducked music bed. FREE assembly (Playwright + ffmpeg); the recipe supplies the per-brand thread + timeline + end-card config and gates the paid music call to its own capability. The ChatGPT sibling of render-imessage-chat. Use for the chatgpt-chat format.

Assemble a cinematic live-action-style music-video ad from a config — an original sung anthem carries the whole narrative while N 35mm-film-look i2v clips are each cut to their lyric window and hard-concatenated on the beat as a 3-act arc, the anthem muxed at loudnorm I=-14, cinematic lower-third serif captions built from the song's OWN word timings (never Whisper) with the hook line landing on the chorus drop, and closed on a brand end card composited from the real asset — never AI-rendered text. This is the FREE deterministic assembly stage (cut-to-window + hard concat + anthem mux + captions + end card); the anthem, keyframes, and clips come from create-music-elevenlabs / create-image-fal / create-video-fal. Use for the cinematic-music-video format.

Assemble a cosmic-mythology-voiceover reel from a config — a warm spoken voiceover carries the whole narrative while N curated cosmic stills are weighted beat-synced across the delivered VO duration (cut_dur = VO_dur times weight over the weight sum, so emotional beats hold longer), Ken-Burns-zoomed per still (scale 2x, center crop, zoompan, fade-in first and fade-out last), ffmpeg-concatenated, the VO composited under the picture (libx264 crf18 plus aac), the ONE on-screen hook line faded on over the open with a drawtext alpha window, and Whisper/VEED captions burned along the bottom — never in-world text on a still. This is the FREE deterministic assembly stage (weighted sequence plus Ken-Burns plus concat plus VO composite plus hook overlay plus caption burn); the VO and the stills come from create-vo-elevenlabs and create-image-fal. Use for the cosmic-mythology-voiceover format.

Assemble a creator picture-in-picture product-listicle ad from a config — the creator stays FULL-FRAME the whole beat (voice plus lips generated together per beat, no separate VO, no cut to a full-frame product shot), and on each product beat three persistent overlays ride on top for the WHOLE beat — a title pill top-center, the DEMO in a rounded PiP window top-right (the brand's real UGC clip MUTED, or for a no-UGC brand the product's own autocropped UI still / screen-recording sized to fill the window), and a bottom product card (rounded thumbnail plus 'N · CATEGORY' small-caps plus product NAME in a serif face). Hook plus CTA beats are the creator full-frame with the title pill only. Assembly builds ONE full-1080x1920 transparent overlay PNG per beat, overlays it on the creator clip (cover-scaled to 1080x1920) for the whole beat keeping the native audio, concats all beats, then burns captions LAST as timed PIL PNG overlays (this ffmpeg has no libass) timed deterministically from the known per-beat script. This is the FREE deterministic assembly stage (overlay-PNG build plus cover-scale composite plus concat plus PIL-PNG caption burn); the creator anchor and the N native talking clips come from create-image-fal (Seedream v5 Pro) and create-video-fal (Seedance 2.0). Use for the creator-pip-listicle format.

Assemble an editorial-motion podcast-clip ad from a config — a real clipped podcast MP3 carries the narrative while N flat 2-tone editorial-illustration keyframes are animated NOT by generative i2v but by DETERMINISTIC ffmpeg ken-burns (zoompan) + hard cuts (no crossfades, which expose geometric drift), each beat snapped to its spoken line, the real audio muxed, Whisper-driven captions burned only mid-sentence, and closed on a PIL brand end card — never AI-rendered text. This is the FREE deterministic assembly stage (ffmpeg ken-burns + hard concat + audio mux + captions + end card); the real audio is clipped from source and the keyframes come from create-image-fal. Use for the editorial-motion-podcast format.