1.2.2

avd — agent-video-downloader

yt-dlp for cloud AI agents. One command downloads videos from TikTok, Instagram, Douyin, Rednote (Xiaohongshu), Reddit, X.com — no browser, no cookies, no login. Built for Claude / Cursor / Cline / GLM / GPT agents that need video bytes in task workflows.

Install:

pip install agent-video-downloader
avd agent-setup

Live on PyPI: https://pypi.org/project/agent-video-downloader/

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Quickstart — one command for AI agents

pip install agent-video-downloader
avd agent-setup
avd download 'https://www.tiktok.com/@anyuser/video/<numeric-id>'

avd agent-setup auto-installs ffmpeg, all Python deps, and the XHS-Downloader repo (for Rednote). It's idempotent — safe to re-run anytime. Zero manual steps for an AI agent.

For the full agent usage guide (8 steps, decision tree, MCP server config, env vars):

avd agent-instructions

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Why

yt-dlp is broken from datacenter IPs for TikTok, Twitter, Reddit, Instagram, Douyin. Cloud CLI agents (Claude Code, GLM CLI, Cursor, Cline) that need to download videos for tasks (transcription, OCR, content analysis, archival) have no reliable path. avd fixes that with direct-API fallback chains that work from cloud IPs without login.

All six platforms download real video bytes (verified live 2026-10-03 from a Hong Kong datacenter IP, total 1.2 GB downloaded through avd itself):

Real-world batch test — 21/24 videos downloaded via avd itself

A 24-URL batch (4 per platform minimum, large videos first) was run through avd itself to validate the system on real public content rather than curated samples:

• TikTok: 4/4 ✅
• Twitter: 4/4 ✅ (largest file: 185 MB 4K video)
• Instagram: 4/4 ✅
• Reddit: 4/4 ✅ (largest file: 283 MB / 372 s interview)
• Douyin: 4/4 ✅
• Rednote: 1/4 ⚠️ (1 verified image; 3 bot-walled without cookie — documented limitation)

Total: 1.2 GB of real video content downloaded through avd itself.

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Commands

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Install

From PyPI (recommended)

pip install agent-video-downloader
avd agent-setup

From source (development)

git clone https://github.com/hamza140202/agent-video-downloader
cd agent-video-downloader
pip install -e .[dev]
avd agent-setup

System requirements

• Python 3.10+ (tested on 3.10, 3.11, 3.12, 3.13)
• ffmpeg / ffprobe (auto-installed by avd agent-setup on Debian/Ubuntu; manual on other systems)
• git (for cloning XHS-Downloader on first Rednote download)

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Configuration (env vars)

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Architecture (4 plain-Python agents, no LLM in runtime loop)

URL → Orchestrator → [TikTok|Twitter|Reddit|Instagram|Rednote|Douyin] extractors (fallback chain)
                     → Verifier (6-layer: size, magic bytes, ffprobe, duration, streams, moov)
                     → Truth Agent (cross-check vs source platform: oEmbed / syndication / RSS / OG)
                     → verified MP4 + manifest

• Orchestrator — owns the extractor registry, drives the fallback chain, persists job state to SQLite
• Verifier — 6-layer integrity check (size + magic bytes + ffprobe + duration + streams + moov atom)
• Truth Agent — cross-references downloaded metadata against source platform
• Tester — runs end-to-end on tests/sample_urls.json

Per-platform fallback chains (slot-based state machine, ytagent doctrine):

• TikTok: TikWM → embed/v2 → tiklydown → oEmbed
• Twitter/X: fxtwitter → syndication → unrollnow → vxtwitter
• Reddit: rapidsave.com/info + v.redd.it CMAF/DASH direct + ffmpeg mux → rapidsave server-side mux → yt-dlp+OAuth → RSS image
• Instagram: yt-dlp+facebookexternalhit UA → embed/captioned+fb-UA → embed+android-UA → embed+ios-UA → ddinstagram mirror
• Douyin: api.douyin.wtf demo → self-hosted DTK sidecar → yt-dlp
• Rednote: XHS-Downloader (curl_cffi) → curl_cffi direct → yt-dlp

Full design: docs/architecture.md · Full research: docs/research-report.md

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Documentation

For users

• README.md — this file (install + quickstart + commands)
• Run avd agent-instructions — interactive step-by-step usage guide

For developers / agents modifying the code

• CLAUDE.md — project memory (read first if modifying)
• AGENTS.md — agent contracts + perfection prompting rules
• TECHSTACK.md — every dependency, every version, why
• PHASES.md — development phases with exit criteria
• PLAN.md — concrete execution plan with task IDs
• SKILLS.md — per-agent skill spec sheets

Deep technical references

• docs/research-report.md — live-verified endpoint research per platform
• docs/architecture.md — system design with ASCII diagram
• docs/endpoint-matrix.md — living endpoint table

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License

MIT. See LICENSE.

Repo

• Primary: https://github.com/hamza140202/agent-video-downloader
• PyPI: https://pypi.org/project/agent-video-downloader/
• Issues: file on GitHub with the metadata.extractor_chain and metadata.slots_tried from your run's manifest attached

Changelog

v1.2.0 (2026-10-03) — PyPI release

• One-command install: pip install agent-video-downloader && avd agent-setup
• New avd agent-setup command (auto-install ffmpeg, deps, XHS-Downloader)
• New avd agent-instructions command (8-step AI agent usage guide)
• Auto-bootstrap on first Rednote download (no manual setup)
• Reddit extractor fix: probe BOTH CMAF and DASH format ladders
• Rednote extractor fix: parse XHS-Downloader stdout for actual success
• Verifier: adaptive min_size_bytes (50KB images / 5KB audio / 1MB video)
• Verifier: skip slow integrity_decode for files > 50 MB
• Real-world batch test: 21/24 videos downloaded via avd itself (1.2 GB)
• Published to PyPI: https://pypi.org/project/agent-video-downloader/1.2.0/

v1.1.0 (2026-10-03) — all 6 platforms real downloads

• Replaced honest-empties with verified-working methods per ytagent doctrine
• TikTok via TikWM (2 MB MP4 verified)
• Twitter via fxtwitter (156 MB 4K MP4 verified)
• Reddit via rapidsave.com + v.redd.it CMAF + ffmpeg mux (6.1 MB verified)
• Instagram via yt-dlp + facebookexternalhit UA (8.4 MB verified)
• Douyin via api.douyin.wtf public demo (3.6 MB verified)
• Rednote via XHS-Downloader (curl_cffi) (8.4 MB verified)
• Truth Agent: Twitter returned verified verdict

v1.0.0 (2026-10-03) — initial release

• Multi-agent architecture (Orchestrator + Verifier + Truth + Tester)
• 6 platform extractors with fallback chains
• MCP server (stdio JSON-RPC 2.0)
• SQLite jobs table with resume / DLQ replay
• 30/30 unit tests pass