Video Understand
calesthio/OpenMontage
Understand video content locally using ffmpeg frame extraction and Whisper transcription.
Graceful degradation workflow for ffmpeg encoding failures with progressive fallback strategies
$ npx skills add HKUDS/OpenSpace --skill ffmpeg-graceful-degradation -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install HKUDS/OpenSpace ffmpeg-graceful-degradation --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/HKUDS/OpenSpace.git skills-src && mkdir -p .claude/skills && cp -r skills-src/benchmarks/gdpval/skills/ffmpeg-graceful-degradation .claude/skills/ffmpeg-graceful-degradation && rm -rf skills-srcUse ~/.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/
Install the "ffmpeg-graceful-degradation" agent skill from https://github.com/HKUDS/OpenSpace/tree/main/benchmarks/gdpval/skills/ffmpeg-graceful-degradation into .claude/skills/ffmpeg-graceful-degradation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ffmpeg-graceful-degradation", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/HKUDS/OpenSpace/tree/main/benchmarks/gdpval/skills/ffmpeg-graceful-degradationType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add HKUDS/OpenSpace --skill ffmpeg-graceful-degradation -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install HKUDS/OpenSpace ffmpeg-graceful-degradation --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/HKUDS/OpenSpace.git skills-src && mkdir -p .agents/skills && cp -r skills-src/benchmarks/gdpval/skills/ffmpeg-graceful-degradation .agents/skills/ffmpeg-graceful-degradation && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "ffmpeg-graceful-degradation" agent skill from https://github.com/HKUDS/OpenSpace/tree/main/benchmarks/gdpval/skills/ffmpeg-graceful-degradation into .agents/skills/ffmpeg-graceful-degradation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ffmpeg-graceful-degradation", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add HKUDS/OpenSpace --skill ffmpeg-graceful-degradation -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install HKUDS/OpenSpace ffmpeg-graceful-degradation --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/HKUDS/OpenSpace.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/benchmarks/gdpval/skills/ffmpeg-graceful-degradation .cursor/skills/ffmpeg-graceful-degradation && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "ffmpeg-graceful-degradation" agent skill from https://github.com/HKUDS/OpenSpace/tree/main/benchmarks/gdpval/skills/ffmpeg-graceful-degradation into .cursor/skills/ffmpeg-graceful-degradation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ffmpeg-graceful-degradation", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/HKUDS/OpenSpace.git --path benchmarks/gdpval/skills/ffmpeg-graceful-degradation--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add HKUDS/OpenSpace --skill ffmpeg-graceful-degradation -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install HKUDS/OpenSpace ffmpeg-graceful-degradation --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/HKUDS/OpenSpace.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/benchmarks/gdpval/skills/ffmpeg-graceful-degradation .gemini/skills/ffmpeg-graceful-degradation && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "ffmpeg-graceful-degradation" agent skill from https://github.com/HKUDS/OpenSpace/tree/main/benchmarks/gdpval/skills/ffmpeg-graceful-degradation into .gemini/skills/ffmpeg-graceful-degradation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ffmpeg-graceful-degradation", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install HKUDS/OpenSpace ffmpeg-graceful-degradationInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add HKUDS/OpenSpace --skill ffmpeg-graceful-degradation -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/HKUDS/OpenSpace.git skills-src && mkdir -p .github/skills && cp -r skills-src/benchmarks/gdpval/skills/ffmpeg-graceful-degradation .github/skills/ffmpeg-graceful-degradation && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "ffmpeg-graceful-degradation" agent skill from https://github.com/HKUDS/OpenSpace/tree/main/benchmarks/gdpval/skills/ffmpeg-graceful-degradation into .github/skills/ffmpeg-graceful-degradation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ffmpeg-graceful-degradation", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add HKUDS/OpenSpace --skill ffmpeg-graceful-degradation -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install HKUDS/OpenSpace ffmpeg-graceful-degradation --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/HKUDS/OpenSpace.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/benchmarks/gdpval/skills/ffmpeg-graceful-degradation .opencode/skills/ffmpeg-graceful-degradation && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "ffmpeg-graceful-degradation" agent skill from https://github.com/HKUDS/OpenSpace/tree/main/benchmarks/gdpval/skills/ffmpeg-graceful-degradation into .opencode/skills/ffmpeg-graceful-degradation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ffmpeg-graceful-degradation", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
ffmpeg-graceful-degradationGraceful degradation workflow for ffmpeg encoding failures with progressive fallback strategies
Ffmpeg Graceful Degradation is an agent skill from HKUDS/OpenSpace. Graceful degradation workflow for ffmpeg encoding failures with progressive fallback strategies
Its SKILL.md is about 1.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 1 other file.
It sits in Media & Creative, covering Video production and Error handling. It works with FFmpeg. The repository describes itself as: "OpenSpace: The Skill Management Layer for AI Agents" -- https://open-space.cloud/. The licence is MIT.
4 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 3827781. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Shell commands in SKILL.md call:
ffmpegpipFrom the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md. Its commands use pip, which can reach the network depending on how they are called.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Ffmpeg Graceful Degradation loads about 1.6k tokens when it runs. Until then it costs about 31 tokens; SKILL.md has 350 words of instructions outside code blocks.
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.
The automated check found no risky patterns in SKILL.md.
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); files beside SKILL.md are not scanned.
The full file from HKUDS/OpenSpace at commit 3827781, republished under its MIT licence (© HKUDS). 350 words, ~1,641 tokens.
.claude/skills/ffmpeg-graceful-degradation/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.When processing videos with ffmpeg, encoding failures are common due to codec availability, library version mismatches, or system configuration issues. This skill provides a systematic fallback strategy to ensure video processing completes successfully.
The pattern involves: (1) probing encoder availability upfront, (2) testing on a short clip before batch processing, (3) progressive fallback through copy mode, alternative codecs, and finally moviepy, (4) using moviepy as a reliable bundled alternative.
Before any encoding work, check what encoders are available:
ffmpeg -encoders | grep -E "libx264|libopenh264|mpeg4"Expected output shows which encoders are present:
libx264 - Preferred H.264 encoder (may be missing)libopenh264 - Alternative H.264 (often has library issues)mpeg4 - Universal fallback (always available)Never start batch processing without validation. Extract and test a short segment:
# Extract 5-second test clip
ffmpeg -y -i input.mp4 -ss 0 -t 5 -c copy test_clip.mp4
# Attempt encode with preferred codec
ffmpeg -y -i test_clip.mp4 -c:v libx264 -preset fast test_output.mp4Check the exit code and output for errors. Common failures:
libopenh264.so: wrong ELF classEncoder libx264 not foundIf the preferred encoder fails, try these fallbacks in order:
ffmpeg -y -i input.mp4 -c:v copy -c:a copy output.mp4Fast, lossless, but doesn't change codec/format.
ffmpeg -y -i input.mp4 -c:v mpeg4 -q:v 3 -c:a copy output.mp4Universal compatibility, larger file sizes, always available.
pip install moviepyThen use Python instead of raw ffmpeg:
from moviepy.editor import VideoFileClip, concatenate_videoclips
# Single clip processing
clip = VideoFileClip("input.mp4")
clip.write_videofile("output.mp4", codec="libx264")
# Concatenate multiple clips
clips = [VideoFileClip(f) for f in clip_files]
final = concatenate_videoclips(clips)
final.write_videofile("output.mp4", codec="libx264")MoviePy bundles its own ffmpeg binary, avoiding system library issues.
Here's a complete graceful degradation workflow:
import subprocess
import os
def safe_video_encode(input_path, output_path, clips=None):
"""
Encode video with graceful degradation fallbacks.
Args:
input_path: Single input file path, or
clips: List of clip paths for concatenation
Returns:
True if successful, False otherwise
"""
# Step 1: Check encoder availability
result = subprocess.run(
["ffmpeg", "-encoders"],
capture_output=True, text=True
)
has_libx264 = "libx264" in result.stdout
has_mpeg4 = "mpeg4" in result.stdout
# Step 2: If concatenating, prepare clips with moviepy
if clips:
try:
from moviepy.editor import VideoFileClip, concatenate_videoclips
loaded_clips = [VideoFileClip(c) for c in clips]
final = concatenate_videoclips(loaded_clips)
final.write_videofile(output_path, codec="libx264", logger=None)
return True
except Exception as e:
print(f"MoviePy failed: {e}")
# Step 3: Try ffmpeg with progressive fallbacks
encoders_to_try = []
if has_libx264:
encoders_to_try.append("libx264")
encoders_to_try.append("mpeg4") # Always available
for codec in encoders_to_try:
cmd = [
"ffmpeg", "-y",
"-i", input_path,
"-c:v", codec,
"-c:a", "copy",
output_path
]
result = subprocess.run(cmd, capture_output=True, text=True)
if result.returncode == 0:
return True
# Step 4: Last resort - copy mode
cmd = ["ffmpeg", "-y", "-i", input_path, "-c", "copy", output_path]
result = subprocess.run(cmd, capture_output=True, text=True)
return result.returncode == 0Start
│
▼
Check encoders (ffmpeg -encoders)
│
├─ libx264 available? ──Yes──► Try libx264
│ │ │
│ No └─► Success? ──Yes──► Done
│ │ │
│ ▼ No
│ Test short clip │
│ │ ▼
│ ▼ Try -c:v copy
│ Encode fails? ──Yes──► Check libopenh264 │
│ │ │ │
│ No Broken ▼
│ │ │ Try mpeg4
│ ▼ ▼ │
│ Done Install moviepy │
│ │ │
│ ▼ │
│ Use VideoFileClip ◄────┘
│ concatenate_videoclips
│ │
│ ▼
│ Done
│
▼
End| Error Message | Cause | Solution |
|---|---|---|
libopenh264.so: wrong ELF class | Library architecture mismatch | Use moviepy or mpeg4 |
Encoder libx264 not found | FFmpeg built without x264 | Use mpeg4 fallback |
Broken pipe | Process killed mid-operation | Try copy mode first |
Invalid data found | Corrupt or incompatible input | Re-extract source |
© HKUDS, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 1 other file in benchmarks/gdpval/skills/ffmpeg-graceful-degradation of HKUDS/OpenSpace.
Open the folder on GitHubat commit 3827781
Ffmpeg Graceful Degradation 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Ffmpeg Graceful Degradation this skillHKUDS/OpenSpace | 7.8k | — | ~1.6k | Automated safety check: Pass | MIT | |
| Video Understandcalesthio/OpenMontage | 66k | — | ~841 | Automated safety check: Pass | AGPL-3.0 | |
| HyperFrames Video Entry Pointheygen-com/hyperframes | 60k | 3 repos | ~5.2k | Automated safety check: Pass | Apache-2.0 | |
| Video Shotseternityspring/reelbench-skills | 878 | 1 repos | ~1.8k | Automated safety check: Notes | Apache-2.0 | |
| Mobile Demo Film Editorsuperset-sh/superset | 15k | — | ~1.8k | Automated safety check: Pass | Custom licence | |
| Video Editcalesthio/OpenMontage | 66k | — | ~855 | Automated safety check: Notes | AGPL-3.0 |
calesthio/OpenMontage
Understand video content locally using ffmpeg frame extraction and Whisper transcription.
heygen-com/hyperframes
Entry point for making, editing and rendering videos from HTML compositions with HyperFrames, routing each request to the right workflow.
eternityspring/reelbench-skills
拉片:把一条成片拆成逐镜头的分析表——每个镜头的时长、景别、类别、运镜、画面. An agent skill from eternityspring/reelbench-skills.
superset-sh/superset
Edits real mobile screen recordings into a configurable demo video with phone framing, title cards, cutaways and an end card, using a bundled renderer.
calesthio/OpenMontage
Edit videos locally using ffmpeg. An agent skill from calesthio/OpenMontage.
lemomo-ai/lemo-opuscar
Directs a short film made entirely in code in one of the Lemo-Opuscar library's named visual styles, from fetching the library through production and delivery.
HKUDS/OpenSpace
Walks through producing a master audio track plus stems in Python, from checking a reference file and timing sections by BPM to effects, a zip archive and final verification.
HKUDS/OpenSpace
Handle cascading data retrieval tool failures by falling back to embedded knowledge generation
HKUDS/OpenSpace
Gives an agent a workaround when its code-execution sandbox keeps failing: save the Python script to a file and run it through the shell instead.
HKUDS/OpenSpace
A recovery routine for agents whose sandboxed code runner keeps failing: save the Python script to disk, then run it through the shell and read the output.
HKUDS/OpenSpace
Fallback ladder for failed sandboxed code runs, plus the habit of fixing the working directory first so generated files land in the right place.
HKUDS/OpenSpace
Fallback workflow for executing Python code when executecodesandbox fails repeatedly
Works with
Categories
Graceful degradation workflow for ffmpeg encoding failures with progressive fallback strategies. Ffmpeg Graceful Degradation is an agent skill from HKUDS/OpenSpace.
Ffmpeg Graceful Degradation fits situations like: tasks that involve Video production; tasks that involve Error handling.
Run `npx skills add HKUDS/OpenSpace --skill ffmpeg-graceful-degradation -a claude-code`. Or copy the skill folder (benchmarks/gdpval/skills/ffmpeg-graceful-degradation in HKUDS/OpenSpace) into .claude/skills/ffmpeg-graceful-degradation in your project. Claude Code loads it when a task matches its description.
Run `npx skills add HKUDS/OpenSpace --skill ffmpeg-graceful-degradation -a codex`. Or copy the skill folder (benchmarks/gdpval/skills/ffmpeg-graceful-degradation in HKUDS/OpenSpace) into .agents/skills/ffmpeg-graceful-degradation in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add HKUDS/OpenSpace --skill ffmpeg-graceful-degradation -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/ffmpeg-graceful-degradation, .gemini/skills/ffmpeg-graceful-degradation, .github/skills/ffmpeg-graceful-degradation and .opencode/skills/ffmpeg-graceful-degradation in your project.
Going by SKILL.md and its folder, Ffmpeg Graceful Degradation needs the command-line tools its instructions call (ffmpeg and pip). Our summary lists: Python 3.
SKILL.md contains no URLs. Its commands use pip, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Ffmpeg Graceful Degradation is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 1.6k tokens (SKILL.md is roughly 6.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Ffmpeg Graceful Degradation: Video Understand (calesthio/OpenMontage, 66k stars), HyperFrames Video Entry Point (heygen-com/hyperframes, 60k stars), Video Shots (eternityspring/reelbench-skills, 878 stars) and Mobile Demo Film Editor (superset-sh/superset, 15k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
HKUDS (a GitHub organization) maintains it in HKUDS/OpenSpace, which has 7,754 GitHub stars. The repository holds 199 skills in this directory. The repository was last updated on August 12, 2026.
Source: HKUDS/OpenSpace on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.