Agent skill

Videodb

by sickn33 in sickn33/agentic-awesome-skills

Video and audio perception, indexing, and editing. An agent skill from sickn33/agentic-awesome-skills.

MITAuto-check: notesMedia & Creative

Install Videodb

skills CLI
$ npx skills add sickn33/agentic-awesome-skills --skill videodb -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install sickn33/agentic-awesome-skills videodb --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/sickn33/agentic-awesome-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/videodb .claude/skills/videodb && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
videodb
GitHub stars
47k
Used in
2 other repos
Token cost
~3.5k tokens
SKILL.md length
1,057 words
Files
12 (incl. scripts)
Skills in repo
1,493
Repo updated
First seen
Licence
MIT

At a glance

Video and audio perception, indexing, and editing. An agent skill from sickn33/agentic-awesome-skills.

  • Works in 5 steps: Desktop Perception → Video ingest + stream → Index + search (timestamps + evidence) → …
  • Tasks that involve Transcription
  • SKILL.md covers When to Use, 1) Desktop Perception, 2) Video ingest + stream and 3) Index + search (timestamps…, plus 11 more sections
  • Runs Python scripts from its folder; calls python and pip; reaches youtube.com; needs VIDEO_DB_API_KEY

What it does

Videodb is an agent skill from sickn33/agentic-awesome-skills. Video and audio perception, indexing, and editing. Ingest files/URLs/live streams, build visual/spoken indexes, search with timestamps, edit timelines, add overlays/subtitles, generate media, and create real-time alerts.

Its SKILL.md is about 3.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 13 other files, including scripts (for example `reference/api-reference.md`, `reference/capture-reference.md` and `reference/capture.md`).

It sits in Media & Creative, covering Transcription. The repository describes itself as: AAS Core is the local, agent-first control plane for complete catalog discovery, agent-owned selection, stack validation, and planning, backed by 2,400+ agentic skills. Includes… The licence is MIT.

When your agent uses it

  • Tasks that involve Transcription

Example prompts

  • “/videodb”

Requirements

  • Python 3
  • A credential in VIDEO_DB_API_KEY
  • Pre-approved tools (allowed-tools): Read, Grep, Glob, Bash(python:*)

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Desktop Perception
  2. Video ingest + stream
  3. Index + search (timestamps + evidence)
  4. Timeline editing + generation
  5. Live streams (RTSP) + monitoring

What it can do on your machine

Read from SKILL.md and the folder at commit 680176d. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Grep
    • Glob
    • Bash(python:*)

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python
    • pip

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • youtube.com

    Also links to:

    • github.com
    • console.videodb.io

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • VIDEO_DB_API_KEY

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Videodb loads about 3.5k tokens when it runs. Until then it costs about 57 tokens; SKILL.md has 1,057 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~57
When it runs · the whole SKILL.md, loaded when a task matches
~3.5k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NoteMentions a .env fileSKILL.md:79
    load_dotenv(".env")
  • NoteMentions a .env fileSKILL.md:87
    2. Project's `.env` file in current directory
  • NoteMentions a .env fileSKILL.md:98
    load_dotenv(".env")
  • NoteMentions a .env fileSKILL.md:128
    - **Project `.env` file**: Save `VIDEO_DB_API_KEY=your-key` in the project's `.env` file

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from sickn33/agentic-awesome-skills at commit 680176d, republished under its MIT licence (© sickn33). 1,057 words, ~3,534 tokens.

Download SKILL.mdSave it as .claude/skills/videodb/SKILL.md (or your agent's skills folder). This skill also uses 11 other files; get the full folder from GitHub.
name
videodb
description
Video and audio perception, indexing, and editing. Ingest files/URLs/live streams, build visual/spoken indexes, search with timestamps, edit timelines, add overlays/subtitles, generate media, and create real-time alerts.
allowed-tools
Read, Grep, Glob, Bash(python:*)
category
media
risk
safe
source
community
tags
[video, editing, transcription, subtitles, search, streaming, ai-generation, media, live-streams, desktop-capture]
date_added
2026-02-27
argument-hint
[task description]

VideoDB Skill

Perception + memory + actions for video, live streams, and desktop sessions.

Use this skill when you need to:

When to Use

  • You need video or audio perception, indexing, search, or timeline editing from files, URLs, desktop sessions, or live streams.
  • The task involves timestamps, searchable evidence, subtitles, clips, overlays, or real-time monitoring alerts.
  • You want one workflow that combines ingestion, understanding, retrieval, and media actions.

1) Desktop Perception

  • Start/stop a desktop session capturing screen, mic, and system audio
  • Stream live context and store episodic session memory
  • Run real-time alerts/triggers on what's spoken and what's happening on screen
  • Produce session summaries, a searchable timeline, and playable evidence links

2) Video ingest + stream

  • Ingest a file or URL and return a playable web stream link
  • Transcode/normalize: codec, bitrate, fps, resolution, aspect ratio

3) Index + search (timestamps + evidence)

  • Build visual, spoken, and keyword indexes
  • Search and return exact moments with timestamps and playable evidence
  • Auto-create clips from search results

4) Timeline editing + generation

  • Subtitles: generate, translate, burn-in
  • Overlays: text/image/branding, motion captions
  • Audio: background music, voiceover, dubbing
  • Programmatic composition and exports via timeline operations

5) Live streams (RTSP) + monitoring

  • Connect RTSP/live feeds
  • Run real-time visual and spoken understanding and emit events/alerts for monitoring workflows

Common inputs

  • Local file path, public URL, or RTSP URL
  • Desktop capture request: start / stop / summarize session
  • Desired operations: get context for understanding, transcode spec, index spec, search query, clip ranges, timeline edits, alert rules

Common outputs

  • Stream URL
  • Search results with timestamps and evidence links
  • Generated assets: subtitles, audio, images, clips
  • Event/alert payloads for live streams
  • Desktop session summaries and memory entries

Canonical prompts (examples)

  • "Start desktop capture and alert when a password field appears."
  • "Record my session and produce an actionable summary when it ends."
  • "Ingest this file and return a playable stream link."
  • "Index this folder and find every scene with people, return timestamps."
  • "Generate subtitles, burn them in, and add light background music."
  • "Connect this RTSP URL and alert when a person enters the zone."

Running Python code

Before running any VideoDB code, change to the project directory and load environment variables:

python
from dotenv import load_dotenv
load_dotenv(".env")

import videodb
conn = videodb.connect()

This reads VIDEO_DB_API_KEY from:

  1. Environment (if already exported)
  2. Project's .env file in current directory

If the key is missing, videodb.connect() raises AuthenticationError automatically.

Do NOT write a script file when a short inline command works.

When writing inline Python (python -c "..."), always use properly formatted code — use semicolons to separate statements and keep it readable. For anything longer than ~3 statements, use a heredoc instead:

bash
python << 'EOF'
from dotenv import load_dotenv
load_dotenv(".env")

import videodb
conn = videodb.connect()
coll = conn.get_collection()
print(f"Videos: {len(coll.get_videos())}")
EOF

Setup

When the user asks to "setup videodb" or similar:

1. Install SDK
bash
pip install "videodb[capture]" python-dotenv

If videodb[capture] fails on Linux, install without the capture extra:

bash
pip install videodb python-dotenv
2. Configure API key

The user must set VIDEO_DB_API_KEY using either method:

  • Export in terminal (before starting Claude): export VIDEO_DB_API_KEY=your-key
  • Project .env file: Save VIDEO_DB_API_KEY=your-key in the project's .env file

Get a free API key at https://console.videodb.io (50 free uploads, no credit card).

Do NOT read, write, or handle the API key yourself. Always let the user set it.

Quick Reference

Upload media
python
# URL
video = coll.upload(url="https://example.com/video.mp4")

# YouTube
video = coll.upload(url="https://www.youtube.com/watch?v=VIDEO_ID")

# Local file
video = coll.upload(file_path="/path/to/video.mp4")
Transcript + subtitle
python
# force=True skips the error if the video is already indexed
video.index_spoken_words(force=True)
text = video.get_transcript_text()
stream_url = video.add_subtitle()
Search inside videos
python
from videodb.exceptions import InvalidRequestError

video.index_spoken_words(force=True)

# search() raises InvalidRequestError when no results are found.
# Always wrap in try/except and treat "No results found" as empty.
try:
    results = video.search("product demo")
    shots = results.get_shots()
    stream_url = results.compile()
except InvalidRequestError as e:
    if "No results found" in str(e):
        shots = []
    else:
        raise
python
import re
from videodb import SearchType, IndexType, SceneExtractionType
from videodb.exceptions import InvalidRequestError

# index_scenes() has no force parameter — it raises an error if a scene
# index already exists. Extract the existing index ID from the error.
try:
    scene_index_id = video.index_scenes(
        extraction_type=SceneExtractionType.shot_based,
        prompt="Describe the visual content in this scene.",
    )
except Exception as e:
    match = re.search(r"id\s+([a-f0-9]+)", str(e))
    if match:
        scene_index_id = match.group(1)
    else:
        raise

# Use score_threshold to filter low-relevance noise (recommended: 0.3+)
try:
    results = video.search(
        query="person writing on a whiteboard",
        search_type=SearchType.semantic,
        index_type=IndexType.scene,
        scene_index_id=scene_index_id,
        score_threshold=0.3,
    )
    shots = results.get_shots()
    stream_url = results.compile()
except InvalidRequestError as e:
    if "No results found" in str(e):
        shots = []
    else:
        raise
Timeline editing

Important: Always validate timestamps before building a timeline:

  • start must be >= 0 (negative values are silently accepted but produce broken output)
  • start must be < end
  • end must be <= video.length
python
from videodb.timeline import Timeline
from videodb.asset import VideoAsset, TextAsset, TextStyle

timeline = Timeline(conn)
timeline.add_inline(VideoAsset(asset_id=video.id, start=10, end=30))
timeline.add_overlay(0, TextAsset(text="The End", duration=3, style=TextStyle(fontsize=36)))
stream_url = timeline.generate_stream()
Transcode video (resolution / quality change)
python
from videodb import TranscodeMode, VideoConfig, AudioConfig

# Change resolution, quality, or aspect ratio server-side
job_id = conn.transcode(
    source="https://example.com/video.mp4",
    callback_url="https://example.com/webhook",
    mode=TranscodeMode.economy,
    video_config=VideoConfig(resolution=720, quality=23, aspect_ratio="16:9"),
    audio_config=AudioConfig(mute=False),
)
Reframe aspect ratio (for social platforms)

Warning: reframe() is a slow server-side operation. For long videos it can take several minutes and may time out. Best practices:

  • Always limit to a short segment using start/end when possible
  • For full-length videos, use callback_url for async processing
  • Trim the video on a Timeline first, then reframe the shorter result
python
from videodb import ReframeMode

# Always prefer reframing a short segment:
reframed = video.reframe(start=0, end=60, target="vertical", mode=ReframeMode.smart)

# Async reframe for full-length videos (returns None, result via webhook):
video.reframe(target="vertical", callback_url="https://example.com/webhook")

# Presets: "vertical" (9:16), "square" (1:1), "landscape" (16:9)
reframed = video.reframe(start=0, end=60, target="square")

# Custom dimensions
reframed = video.reframe(start=0, end=60, target={"width": 1280, "height": 720})
Generative media
python
image = coll.generate_image(
    prompt="a sunset over mountains",
    aspect_ratio="16:9",
)

Error handling

python
from videodb.exceptions import AuthenticationError, InvalidRequestError

try:
    conn = videodb.connect()
except AuthenticationError:
    print("Check your VIDEO_DB_API_KEY")

try:
    video = coll.upload(url="https://example.com/video.mp4")
except InvalidRequestError as e:
    print(f"Upload failed: {e}")
Show full SKILL.md (453 more words)Show less
Common pitfalls
ScenarioError messageSolution
Indexing an already-indexed videoSpoken word index for video already existsUse video.index_spoken_words(force=True) to skip if already indexed
Scene index already existsScene index with id XXXX already existsExtract the existing scene_index_id from the error with re.search(r"id\s+([a-f0-9]+)", str(e))
Search finds no matchesInvalidRequestError: No results foundCatch the exception and treat as empty results (shots = [])
Reframe times outBlocks indefinitely on long videosUse start/end to limit segment, or pass callback_url for async
Negative timestamps on TimelineSilently produces broken streamAlways validate start >= 0 before creating VideoAsset
generate_video() / create_collection() failsOperation not allowed or maximum limitPlan-gated features — inform the user about plan limits

Additional docs

Reference documentation is in the reference/ directory adjacent to this SKILL.md file. Use the Glob tool to locate it if needed.

Screen Recording (Desktop Capture)

Use ws_listener.py to capture WebSocket events during recording sessions. Desktop capture supports macOS only.

Quick Start
  1. Start listener: python scripts/ws_listener.py &
  2. Get WebSocket ID: cat /tmp/videodb_ws_id
  3. Run capture code (see reference/capture.md for full workflow)
  4. Events written to: /tmp/videodb_events.jsonl
Query Events
python
import json
events = [json.loads(l) for l in open("/tmp/videodb_events.jsonl")]

# Get all transcripts
transcripts = [e["data"]["text"] for e in events if e.get("channel") == "transcript"]

# Get visual descriptions from last 5 minutes
import time
cutoff = time.time() - 300
recent_visual = [e for e in events 
                 if e.get("channel") == "visual_index" and e["unix_ts"] > cutoff]
Utility Scripts

For complete capture workflow, see reference/capture.md.

Do not use ffmpeg, moviepy, or local encoding tools when VideoDB supports the operation. The following are all handled server-side by VideoDB — trimming, combining clips, overlaying audio or music, adding subtitles, text/image overlays, transcoding, resolution changes, aspect-ratio conversion, resizing for platform requirements, transcription, and media generation. Only fall back to local tools for operations listed under Limitations in reference/editor.md (transitions, speed changes, crop/zoom, colour grading, volume mixing).

When to use what
ProblemVideoDB solution
Platform rejects video aspect ratio or resolutionvideo.reframe() or conn.transcode() with VideoConfig
Need to resize video for Twitter/Instagram/TikTokvideo.reframe(target="vertical") or target="square"
Need to change resolution (e.g. 1080p → 720p)conn.transcode() with VideoConfig(resolution=720)
Need to overlay audio/music on videoAudioAsset on a Timeline
Need to add subtitlesvideo.add_subtitle() or CaptionAsset
Need to combine/trim clipsVideoAsset on a Timeline
Need to generate voiceover, music, or SFXcoll.generate_voice(), generate_music(), generate_sound_effect()

Repository

https://github.com/video-db/skills

Maintained By: VideoDB

Limitations

  • Use this skill only when the task clearly matches the scope described above.
  • Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
  • Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.

© sickn33, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 11 other files (scripts) in skills/videodb of sickn33/agentic-awesome-skills.

  • SKILL.md
  • reference/api-reference.md
  • reference/capture-reference.md
  • reference/capture.md
  • reference/editor.md
  • reference/generative.md
  • reference/rtstream-reference.md
  • reference/rtstream.md
  • reference/search.md
  • reference/streaming.md
  • reference/use-cases.md
  • scripts/ws_listener.py

Open the folder on GitHubat commit 680176d

Used in 2 other repositories

We found 11 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 2 other GitHub owners. This page covers the copy in sickn33/agentic-awesome-skills, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Videodb next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Videodb compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Videodb this skillsickn33/agentic-awesome-skills47k2 repos~3.5kAutomated safety check: NotesMIT
HyperFrames Media Useheygen-com/hyperframes59k—~2.4kAutomated safety check: PassApache-2.0
Native Subtitle Quote Imagechengyi-ai/native-subtitle-quote-image2.4k—~1.8kAutomated safety check: PassMIT
Edu Math Videowy51ai/edulab1.4k—~2.5kAutomated safety check: NotesApache-2.0
Transcription Memory ReconstructionNxcoreAI/EverRoom3k—~714Automated safety check: PassCustom licence
TranscribeJetBrains/skills3664 repos~776Automated safety check: PassApache-2.0

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Questions about Videodb

What does Videodb do?

Video and audio perception, indexing, and editing. An agent skill from sickn33/agentic-awesome-skills. Videodb is an agent skill from sickn33/agentic-awesome-skills. Video and audio perception, indexing, and editing.

When should I use Videodb?

Videodb fits situations like: tasks that involve Transcription.

How do I install Videodb in Claude Code?

Run `npx skills add sickn33/agentic-awesome-skills --skill videodb -a claude-code`. Or copy the skill folder (skills/videodb in sickn33/agentic-awesome-skills) into .claude/skills/videodb in your project. Claude Code loads it when a task matches its description.

How do I install Videodb in Codex?

Run `npx skills add sickn33/agentic-awesome-skills --skill videodb -a codex`. Or copy the skill folder (skills/videodb in sickn33/agentic-awesome-skills) into .agents/skills/videodb in your project. Codex loads it when a task matches its description.

Can I use Videodb in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add sickn33/agentic-awesome-skills --skill videodb -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/videodb, .gemini/skills/videodb, .github/skills/videodb and .opencode/skills/videodb in your project.

What does Videodb need to run?

Going by SKILL.md and its folder, Videodb needs Python for the scripts in its folder, the command-line tools its instructions call (python and pip) and credentials named VIDEO_DB_API_KEY. Our summary lists: Python 3; A credential in VIDEO_DB_API_KEY. Its frontmatter pre-approves these tools: Read, Grep, Glob, Bash(python:*).

Does Videodb access the network?

SKILL.md names 3 domains. In commands or code: youtube.com; the agent is likely to contact it when it follows the instructions. As links in the text: github.com and console.videodb.io. This is read from the text; nothing was executed.

Is Videodb safe to install?

Our automated static check of SKILL.md found notes only (mentions a .env file), nothing it rates as a warning. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Videodb use?

Videodb is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Videodb use?

About 3.5k tokens (SKILL.md is roughly 14k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Videodb?

Skills that share tags, products or a category with Videodb: HyperFrames Media Use (heygen-com/hyperframes, 59k stars), Native Subtitle Quote Image (chengyi-ai/native-subtitle-quote-image, 2.4k stars), Edu Math Video (wy51ai/edulab, 1.4k stars) and Transcription Memory Reconstruction (NxcoreAI/EverRoom, 3k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Videodb?

sickn33 (a GitHub user) maintains it in sickn33/agentic-awesome-skills, which has 47,379 GitHub stars. The repository holds 1,493 skills in this directory. The repository was last updated on October 9, 2026.

Source: sickn33/agentic-awesome-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.