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229,660 tools. Last updated 2026-06-24 07:06

"A tool for video analysis" matching MCP tools:

  • Generate cinematic video from a text prompt. Uses ByteDance Seedance 2.0 — #1 on the Artificial Analysis text-to-video leaderboard — with synchronized native audio. Async — returns requestId, poll with check_job_status. 480p/720p/1080p, 4-15 seconds, priced per second by resolution (BTC-pegged; native audio free). Pay per request with Bitcoin Lightning — no API key or signup needed. Requires create_payment with toolName='generate_video' and duration, resolution params.
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  • Create a new Avocado AI Flow pre-built with a node-graph pipeline, and return its id and direct URL so the user can open it on the canvas. You design the whole pipeline: pass the nodes and edges and the server validates socket compatibility, aligns video models to the input shape, lays the graph out left-to-right, and adds a caption per step. Edges reference nodes by 0-based index in the `nodes` array. This creates (does not run) the flow — the user runs it from the editor. Use the capability map below to choose node types, models, and handles: You are Avo, a senior creative-workflow designer inside Avocado AI's Flow editor. The user describes a creative goal; you respond with a node-graph proposal that the editor previews on the canvas. Think like a production director: design the FULL pipeline needed to get a polished result, not the minimum number of nodes. DESIGN PRINCIPLES — build capable, complete pipelines: - Match the pipeline's ambition to the request. A throwaway test is 2-3 nodes; a real deliverable (an ad, a UGC video, a product shot, a music video) is usually 5-12 nodes. Use up to 24 when it genuinely helps. - Prefer multi-stage quality: generate → refine (imageEditor) → upscale → animate, rather than a single generate node. Add an upscale step before any final image/video deliverable. - Use BRANCHING and FAN-OUT. One output can feed many nodes: e.g. one hero image → three different video models for variations the user can pick from; one script → both a voiceover and the video prompt. - Use PARALLEL TRACKS that converge: e.g. a voice track and an image track both feeding a lip-sync video; or a music track plus a visuals track. - Use the `llm` node to do creative thinking inside the graph — write or expand a script, brainstorm a prompt, turn a rough idea into a detailed image/video prompt — then wire its text output into the next node. - Pick the BEST model for each step (see the menus below). Don't leave everything on defaults — choosing models is a big part of the value. - Set per-node settings (aspect ratio, resolution, duration, voice, variations) when the request implies them (e.g. 'vertical' → 9:16, 'short' → duration 5, '3 options' → variations 3 or three branches). HARD RULES: - Use only the node types listed below. Never invent new ones. - Every edge must connect compatible socket types (text→text, image→image, audio→audio, video→video). - Give every runnable node a short `stepLabel` ('Step N — …') — it renders as a caption beneath that node. - `stickyNote` is only for standalone notes; never use it to caption a node (use `stepLabel`). Optionally add ONE stickyNote describing the workflow. - Any schema field you don't need must be `null` (numbers like `variations` too). MODEL MENUS (set the node's `model` to one of these ids): image (text-to-image) — `model` ids: • fal-ai/nano-banana-2 — fast, strong all-rounder (default) • fal-ai/gpt-image-2 — best instruction-following & legible text • fal-ai/bytedance/seedream/v5/lite/text-to-image — photoreal • fal-ai/flux-pro/v1.1-ultra — high detail / fidelity • fal-ai/nano-banana-pro — premium quality • fal-ai/recraft/v4/text-to-image — design, brand, vector-style • fal-ai/ideogram/v3 — posters & typography imageEditor (image + prompt → edited image) — `model` ids: • fal-ai/nano-banana-2/edit — default, multi-image (up to 14 inputs) • openai/gpt-image-2/edit — precise instruction edits • fal-ai/bytedance/seedream/v5/lite/edit — photoreal edits • fal-ai/flux-pro/kontext/max/text-to-image — style / context transfer • fal-ai/gemini-25-flash-image/edit — fast edits (the `image` input accepts MULTIPLE connections for compositing/restyle) imageUpscale (image → larger image) — `model` ids: • fal-ai/topaz/upscale/image — best quality (default) • fal-ai/recraft-crisp-upscale, fal-ai/clarity-upscaler, fal-ai/crystal-upscaler llm (text → text) — `model` ids: claude-haiku (default), gpt-4o-mini, kimi-k2, seed-1.8. Put the instruction in `prompt`. voice (text → speech) — pick a `voice` by name: Sarah (cheerful), Roger (deep), Laura (soft), Charlie (warm), George (bold), Callum (energetic), River (calm), Liam (reliable). The script comes from an upstream text/llm node wired into `in` — do NOT put the script in the voice node's prompt. music (text → music) — set `duration` to one of 30,60,90,120,180,240,300 (seconds). Put the music description in `prompt`. videoUpscale (video → sharper video) — add after a video node for final deliverables. No model field. VIDEO node — choose `model` to match the input shape (it drives which input handles the node renders): • Text → video: `kling3-pro`, `sora-2`, `veo3-1-fast`, `seedance-2.0-t2v`. Wire text to `prompt`. • Image → video (I2V): `veo3-1-fast`, `kling3-pro`, `seedance-2.0-i2v`, `hailuo-pro`. Wire the image to `image`. For keyframe models (`kling-o1`, `veo3-1`) wire `start-frame` + `end-frame`. • Lip-sync / talking-head: `fabric` (image + audio, NO prompt — never wire text into Fabric) or `infinitalk` (prompt + image + audio). Wire audio to `audio`. Audio-over-stills narration: `ltx2-audio`. • Multi-image reference / character consistency: `vidu` (≤7), `veo3-1-ref` (≤10), `kling-elements` (2-4 ordered frames), `happy-horse-ref` (≤9). Wire EACH image to the SAME `ref-images` handle (it accepts multiple connections). Never use the plain `image` handle. • Seedance reference (image + video + audio refs): `seedance-2.0-ref` / `seedance-2.0-ref-fast`. Wire to `ref-images` / `ref-videos` / `ref-audio`. • Motion control (drive a character with a motion video): `kling3-motion-control`. Wire character to `image`, motion clip (videoUpload) to `motion-video`. Edge handle hints: - When the target has multiple typed inputs (Video, Image Editor), set `toHandle` explicitly (`prompt`, `image`, `audio`, `ref-images`, `start-frame`, `end-frame`, `motion-video`). The editor otherwise picks the first type-compatible handle, which may be the wrong slot. - Never wire text into Fabric. Never wire a single image into a multi-ref model's `image` slot — use `ref-images`. Available node types (id — purpose — inputs / outputs): - text — Prompt — in: in<text> | out: out<text> - llm — LLM — in: in<text> | out: out<text> - upload — Upload — in: — | out: out<image> - videoUpload — Video Upload — in: — | out: out<video> - image — Image — in: in<text> | out: out<image> - imageEditor — Image Editor — in: prompt<text>, image<image> | out: out<image> - imageUpscale — Image Upscale — in: image<image> | out: out<image> - video — Video — in: prompt<text>, image<image>, start-frame<image>, end-frame<image>, ref-images<image>, ref-videos<video>, ref-audio<audio>, audio<audio>, motion-video<video> | out: out<video> - videoUpscale — Video Upscale — in: video<video> | out: out<video> - voice — Voice — in: in<text> | out: out<audio> - music — Music — in: in<text> | out: out<audio> - stickyNote — Sticky Note — in: in<annotation> | out: out<annotation> Edges reference nodes by index in the `nodes` array (0-based). In the examples below, any field not shown is `null`. EXAMPLES — study the PATTERNS (multi-stage, fan-out, parallel tracks), copy the handle names exactly: Example 1 — UGC talking-head with scripted voice + final upscale: nodes=[ {type:"llm",stepLabel:"Step 1 — Write a punchy 15s script",prompt:"Write a 15-second energetic UGC script for the product.",model:"claude-haiku"}, {type:"voice",stepLabel:"Step 2 — Voiceover",voice:"George"}, {type:"upload",stepLabel:"Step 3 — Upload character photo"}, {type:"video",stepLabel:"Step 4 — Lip-sync video",model:"fabric"}, {type:"videoUpscale",stepLabel:"Step 5 — Upscale to deliver"} ] edges=[ {fromIndex:0,toIndex:1,fromHandle:"out",toHandle:"in"}, {fromIndex:1,toIndex:3,fromHandle:"out",toHandle:"audio"}, {fromIndex:2,toIndex:3,fromHandle:"out",toHandle:"image"}, {fromIndex:3,toIndex:4,fromHandle:"out",toHandle:"video"} ] Example 2 — Text → image → refine → upscale (quality chain): nodes=[ {type:"text",stepLabel:"Step 1 — Prompt",prompt:"A cinematic product shot of a matte-black bottle on wet stone, golden hour"}, {type:"image",stepLabel:"Step 2 — Generate hero",model:"fal-ai/flux-pro/v1.1-ultra",aspectRatio:"4:3"}, {type:"imageEditor",stepLabel:"Step 3 — Add brand label",prompt:"Add a minimal embossed logo on the bottle",model:"fal-ai/nano-banana-2/edit"}, {type:"imageUpscale",stepLabel:"Step 4 — Upscale",model:"fal-ai/topaz/upscale/image"} ] edges=[ {fromIndex:0,toIndex:1,fromHandle:"out",toHandle:"in"}, {fromIndex:1,toIndex:2,fromHandle:"out",toHandle:"image"}, {fromIndex:2,toIndex:3,fromHandle:"out",toHandle:"image"} ] Example 3 — Fan-out: one image → three video variations (different models): nodes=[ {type:"upload",stepLabel:"Step 1 — Source image"}, {type:"text",stepLabel:"Step 2 — Motion brief",prompt:"Slow cinematic push-in, gentle parallax"}, {type:"video",stepLabel:"Variation A — Veo",model:"veo3-1-fast",aspectRatio:"9:16",duration:"5"}, {type:"video",stepLabel:"Variation B — Kling",model:"kling3-pro",aspectRatio:"9:16",duration:"5"}, {type:"video",stepLabel:"Variation C — Seedance",model:"seedance-2.0-i2v",aspectRatio:"9:16",duration:"5"} ] edges=[ {fromIndex:0,toIndex:2,fromHandle:"out",toHandle:"image"}, {fromIndex:0,toIndex:3,fromHandle:"out",toHandle:"image"}, {fromIndex:0,toIndex:4,fromHandle:"out",toHandle:"image"}, {fromIndex:1,toIndex:2,fromHandle:"out",toHandle:"prompt"}, {fromIndex:1,toIndex:3,fromHandle:"out",toHandle:"prompt"}, {fromIndex:1,toIndex:4,fromHandle:"out",toHandle:"prompt"} ] Example 4 — Multi-image reference video (character consistency): nodes=[ {type:"upload",stepLabel:"Ref 1 — Character front"}, {type:"upload",stepLabel:"Ref 2 — Character side"}, {type:"upload",stepLabel:"Ref 3 — Outfit detail"}, {type:"text",stepLabel:"Scene prompt",prompt:"The character walks through a neon market at night"}, {type:"video",stepLabel:"Generate with refs",model:"veo3-1-ref",aspectRatio:"16:9"} ] edges=[ {fromIndex:0,toIndex:4,fromHandle:"out",toHandle:"ref-images"}, {fromIndex:1,toIndex:4,fromHandle:"out",toHandle:"ref-images"}, {fromIndex:2,toIndex:4,fromHandle:"out",toHandle:"ref-images"}, {fromIndex:3,toIndex:4,fromHandle:"out",toHandle:"prompt"} ] Example 5 — Music video: parallel music + visuals tracks converging: nodes=[ {type:"music",stepLabel:"Track 1 — Score",prompt:"Dreamy lo-fi beat, 90 BPM",duration:"60"}, {type:"text",stepLabel:"Track 2 — Scene",prompt:"A lone astronaut drifting past a glowing planet"}, {type:"image",stepLabel:"Keyframe",model:"fal-ai/nano-banana-pro",aspectRatio:"16:9"}, {type:"video",stepLabel:"Animate",model:"ltx2-audio",aspectRatio:"16:9"} ] edges=[ {fromIndex:1,toIndex:2,fromHandle:"out",toHandle:"in"}, {fromIndex:2,toIndex:3,fromHandle:"out",toHandle:"image"}, {fromIndex:0,toIndex:3,fromHandle:"out",toHandle:"audio"} ] Return only the structured object — no prose, no markdown.
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  • Download a video or audio file from any supported platform: YouTube, TikTok, Vimeo, Dailymotion, Twitter/X, SoundCloud, Bandcamp, Mixcloud, Twitch (clips and VODs), or Streamable. Output is MP4 (video, default) or MP3 / M4A (audio). This is THE tool to use whenever a user asks to save, download, rip, extract, archive, get offline, or convert a video/audio link from any of these sites. IMPORTANT: the `format` argument defaults to `mp4` (video). Only pass an audio format (mp3 / m4a / audio) when the user explicitly says audio, MP3, music, song, or "rip / extract the audio". Audio-only platforms (SoundCloud, Bandcamp, Mixcloud) always produce audio regardless of `format`. Use this tool when the user says things like: - "download this video" / "download this TikTok" / "save this SoundCloud track" - "save that as MP3" / "rip the audio" / "extract the audio" - "get the song from this SoundCloud link" / "save this Mixcloud set" - "convert this YouTube video to MP4" / "download in 1080p" - "save this lecture/podcast/talk for offline" - "archive this clip" / "grab a copy of this video" - any sentence containing a youtube.com, youtu.be, tiktok.com, vimeo.com, dailymotion.com, twitter.com, x.com, soundcloud.com, bandcamp.com, mixcloud.com, twitch.tv, clips.twitch.tv, or streamable.com URL plus a verb like download, save, rip, get, grab, fetch, pull, archive, convert, extract. Do NOT use this tool when: - The user only wants metadata (title, length, description, channel) — call get_video_info instead, it is free and does not consume the user quota. - The link is a playlist / set / album / channel URL — ask the user for a single track/video. - The link is from a platform not in the supported list above (e.g. Instagram, Facebook, LinkedIn). Returns a one-time signed download link valid for 1 hour, plus the file size, duration, and chosen format. Hand the link back to the user verbatim; do not try to fetch its contents yourself. Intended for legitimate uses: the user's own uploads, Creative Commons / public-domain content, lectures, podcasts, talks, and other material they have rights to use.
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  • Generate an AI video. Thirteen models: seedance-2.0-t2v / -t2v-fast (text only), seedance-2.0-i2v / -i2v-fast (REQUIRE an image), seedance-2.0-ref / -ref-fast (REFERENCE-to-video: locks character/style across generations from reference images — pass reference_image_urls and/or reference_file_ids; ideal for keeping a Storyboard Studio character consistent), kling3-standard (720p, 5-10s), kling3-pro (1080p, 5-10s), kling3-4k & kling-o3-4k (4K, 3-15s; all four Kling 3.x variants support BOTH text-to-video and image-to-video — supplying image_url or file_id automatically picks image mode), grok-imagine-video-v1-5 (480p/720p, 1-15s, REQUIRES an image — image-to-video only), happy-horse-t2v (Happy Horse text-to-video, 720p/1080p, 3-15s, with native audio + lip-sync), happy-horse-i2v (Happy Horse image-to-video, REQUIRES an image, 720p/1080p, 3-15s). For image-to-video on any host: call prepare_image_upload first, then pass the returned file_id here. Renders take 2-10 minutes; the inline result card polls for completion. Pricing is per-second, varies by model and resolution.
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  • Get the full analysis (incl. scene breakdown) for a video — owned or public/competitor. Pass `platform` and `post_id` separately (the native post_id from analyze_post or list_videos — not the composite `id` field). Deep analysis runs async (~30-60s): right after analyze_post this returns {"status": "pending", "retry_after_seconds": N} — that is expected, not an error. Wait that long and call again until you get the full analysis. A genuine 404 means the post was never analyzed — call analyze_post(url) first.
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  • Analyze a single TikTok, YouTube, or Instagram post by URL — adds it to your library and runs deep video analysis. Returns immediately with the post's platform + post_id; deep analysis runs async (~30-60s). Then call get_video_analysis(platform, post_id) to read it — while it runs you get {"status": "pending"}, so wait ~20s and retry until the full result comes back ('pending' is expected, not a failure). Only posts within the creator's recent media (roughly their last ~75 posts) can be fetched. Rate limit: 30 calls/hour.
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  • Create and manage cinematic AI video renders through the Future Video Studio Agent API.

  • [Analysis] Update an OctoPerf BenchReport's editable metadata: name, description and tags. Partial — any parameter left null keeps its existing value. The `items` list (polymorphic widgets), `configs` set and `benchResultIds` are NOT changed by this tool; use `patch_bench_report` to restructure the report. Returns the updated report's id, name, description, benchResultIds, tags, lastModified and a `url` deep-link to the analysis page.
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  • Retrieve the final output of a completed async job. Call ONLY after check_job_status returns status='completed' — calling on a non-completed job returns an error. Returns JSON whose shape depends on jobType: video/video-image → { videoUrl, duration }; image-3d → { modelUrl } (GLB format); transcription → { text, language, segments }; epub-audiobook → { audioUrl, chapters }; ai-call → { transcript, duration, summary }. All URLs are temporary (valid ~1 hour) — download immediately. This tool is free and does not require payment. Do NOT use for synchronous tools — those return results directly.
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  • Prepare a model for an animated walkthrough / video export by verifying the manifest is complete, then starting a secondary Model Derivative job that produces OBJ geometry (suitable for ingestion into offline rendering pipelines, Blender, or Unreal Engine). Also returns the list of available named views so the operator can stitch them into a camera path. Does NOT itself produce an mp4 — video encoding happens in the downstream UE/Twinmotion pipeline. When to use: when a user wants a walkthrough/flythrough video of a BIM model (e.g. 'make a 30-second tour of Tower A') — this tool gets the geometry into a UE-ingestible form (.obj, plus suggests FBX/glTF/USD naming like TowerA_walkthrough.fbx for the exported asset) and enumerates named views to guide camera path authoring. When NOT to use: not to actually encode video (no runtime renderer in this worker — output must be finished in Unreal/Twinmotion/Blender), not before tm_import_rvt, not if the manifest is still 'inprogress' (the tool will short-circuit and return status='pending'). Not for still images (use tm_render_image) or clash animations (use navisworks-mcp). APS scopes required: data:read data:write viewables:read. Write scopes are needed because this kicks off a new Model Derivative translation job (OBJ + thumbnail). Rate limits: APS default ~50 req/min; Model Derivative translation jobs ~60 req/min. OBJ derivatives of large BIM models can be multi-GB and take 10–45 min — rely on manifest polling with exponential backoff, not re-calling this tool. Errors: 401/403 = token/scope (data:write commonly missing); 404 = URN not found; 409 = OBJ derivative already queued (treat as success); 422 = input format does not support OBJ output (some IFC variants / proprietary formats — fall back to FBX/glTF via a different derivative format); 429 = back off 60s; 5xx = APS upstream. Side effects: STARTS a new translation job on an existing URN (consumes APS cloud credits). Writes usage_log. NOT idempotent per-call (each call creates a new job record), but APS will dedupe identical output requests internally if manifest already contains the derivative.
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  • Read **text content** of an attached file. Works for: .txt, .md, .json, code files, and PDFs (after files.ingest extracts text). DO NOT call on binary files — for IMAGES use `files.get_base64`, for AUDIO/VIDEO it cannot be transcribed via this tool, and for non-PDF DOCUMENTS run `files.ingest` first, THEN files.read. Calling on a binary mime-type returns an error — saves you a turn to read the routing hint before deciding.
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  • Read **text content** of an attached file. Works for: .txt, .md, .json, code files, and PDFs (after files.ingest extracts text). DO NOT call on binary files — for IMAGES use `files.get_base64`, for AUDIO/VIDEO it cannot be transcribed via this tool, and for non-PDF DOCUMENTS run `files.ingest` first, THEN files.read. Calling on a binary mime-type returns an error — saves you a turn to read the routing hint before deciding.
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  • MANDATORY first step whenever the user attached an image in chat (or pointed at a local file on disk) and wants edit_image or image-to-video generation. Returns a signed PUT URL plus a file_id. After this tool: either (a) the inline upload widget will let the user drop the file and auto-continue (Claude.ai web), or (b) you run a curl PUT yourself if you have shell access (Claude Desktop / Claude Code) — the response text contains a ready-to-run curl command. Then call edit_image or generate_video with file_id=<returned id>. edit_image and generate_video do NOT accept base64 — calling them with raw image bytes WILL fail. This tool is the only working path for chat attachments. Set `purpose` to 'edit' or 'video' so the upload widget points the user at the right downstream tool.
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  • Get a presigned PUT URL to upload any file — video, audio, or document (markdown, HTML, DOCX, etc.). The URL expires in 15 minutes. PUT raw file bytes directly to the URL. After upload, pass the object_key to transcode_video (for video) or convert_file (for documents). IMPORTANT: this flow needs direct outbound network access to Botverse's S3 bucket. In sandboxed agent environments (claude.ai, sandboxed desktop apps, Cursor) that route traffic through a proxy allowlist, the PUT is blocked and the upload fails. In those environments do NOT use this tool — use convert_content or transcode_content (inline content, body under 500 KB) for files you already have, or convert_from_url / transcode_from_url for anything available at a public URL. Neither needs an upload step.
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  • List construction projects the user can access within a team. **Use this tool ONLY when the user wants to switch project or has no saved current project.** If `check-current-project` returns a saved facility_key, do NOT call this tool — call the analysis tool directly with no arguments. Required workflow when this tool IS appropriate: 1. Present the returned projects to the user. 2. Wait for the user to select one. 3. Call `set-focus-project` with team_domain and facility_key to persist the selection so future sessions skip this step. 4. Then invoke analysis tools. Args: team_domain: Team domain. Optional; if omitted, falls back to the saved current project, otherwise returns the team list so the caller can pick a team first. Returns: str: Accessible facilities with their keys and names.
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  • Ask a question about one or more videos with visual analysis. Most effective on focused time ranges — use start/end to specify the segment to analyze. BEFORE calling this tool, read the reka://docs/guide resource for recommended workflows. In most cases, you should first: - search_videos to find WHEN something happens, then pass those timestamps here as start/end - segment_video to detect and locate specific objects - get_transcript to read what was said For single-video questions, pass video_id with start/end. For cross-video questions, pass videos — a list of video references with start/end each. For follow-up questions, pass conversation_id from the previous response. You can add start/end to drill into a specific moment while keeping the conversation context. Requires qa_only or full pipeline.
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  • Generate a short video (5-10s) from a text prompt using BytePlus Seedance. Optionally accepts up to 12 image file IDs from the user's attached files (visible in the [ATTACHMENTS] block) as `reference_file_ids` for style and composition. Returns immediately with a job_id; the video is delivered back via continuation when the job completes (~30-90s for fast model, ~2-5min for pro). Reference images are temporarily re-hosted on a third-party CDN (imgbb) for the duration of generation and deleted on completion — don't submit confidential references. Gated behind a workspace opt-in flag.
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  • Browse the Gapup gold-standard content catalogue — video games, films, TV series and music. Returns franchises with their works (title, release year). When to use this tool: an agent needs structured, audited metadata for a cultural franchise, wants to resolve a title to a canonical entity, or browses a domain's catalogue before requesting enrichment. Inputs: a content domain and an optional case-insensitive name filter. Each franchise id can be passed to content_enrichment for its fine-grained tag profile.
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  • Check the status of an analyze_creator (or analyze_post creator-backfill) job by job_id. Note: this tracks the creator-ingest job, not a single post's video analysis. To know when one post is ready, poll get_video_analysis(platform, post_id) — it returns {"status": "pending"} until ready.
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  • Strips the background from a video frame-by-frame using rembg (u2netp) on AetherWave's Python service. Pass a public `videoUrl`. Choose `bgType: "transparent"` for an alpha-channel WebM output (compositing) or `bgType: "color"` with a `customColor` hex for a solid replacement. 2 credits per second. Slowest tool in the surface (per-frame processing); a 6s clip takes ~4 min, a 30s clip ~15-20 min. Works best on subjects with clear edges (people, products). Returns the processed video URL (R2-hosted).
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  • Browse a YouTube channel's content. Returns channel{id, name, handle, subscriberCount, videoCount, isVerified, thumbnails} on every tab. Video/short/playlist tabs also return items[{id, videoUrl, title, author, publishedAt, thumbnails}] and continuationToken. About tab returns the full profile including country, joinedDate, viewCount, and links[]. Best for: auditing a creator's catalog, pulling all videos from a channel, reading channel description. Not recommended for: fetching a single known video. Use stophy_get_video instead.
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