Video Generation
bytedance/deer-flow
Generates short videos from a structured JSON prompt, optionally guided by a reference image used as the first or last frame.
Process filler word annotations to generate video edit lists.
Install Filler Word Processing
$ npx skills add benchflow-ai/skillsbench --skill filler-word-processing -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install benchflow-ai/skillsbench filler-word-processing --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/benchflow-ai/skillsbench.git skills-src && mkdir -p .claude/skills && cp -r skills-src/tasks-extra/video-filler-word-remover/environment/skills/filler-word-processing .claude/skills/filler-word-processing && 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 "filler-word-processing" agent skill from https://github.com/benchflow-ai/skillsbench/tree/main/tasks-extra/video-filler-word-remover/environment/skills/filler-word-processing into .claude/skills/filler-word-processing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "filler-word-processing", 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/benchflow-ai/skillsbench/tree/main/tasks-extra/video-filler-word-remover/environment/skills/filler-word-processingType 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 benchflow-ai/skillsbench --skill filler-word-processing -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install benchflow-ai/skillsbench filler-word-processing --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/benchflow-ai/skillsbench.git skills-src && mkdir -p .agents/skills && cp -r skills-src/tasks-extra/video-filler-word-remover/environment/skills/filler-word-processing .agents/skills/filler-word-processing && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "filler-word-processing" agent skill from https://github.com/benchflow-ai/skillsbench/tree/main/tasks-extra/video-filler-word-remover/environment/skills/filler-word-processing into .agents/skills/filler-word-processing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "filler-word-processing", 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 benchflow-ai/skillsbench --skill filler-word-processing -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install benchflow-ai/skillsbench filler-word-processing --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/benchflow-ai/skillsbench.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/tasks-extra/video-filler-word-remover/environment/skills/filler-word-processing .cursor/skills/filler-word-processing && 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 "filler-word-processing" agent skill from https://github.com/benchflow-ai/skillsbench/tree/main/tasks-extra/video-filler-word-remover/environment/skills/filler-word-processing into .cursor/skills/filler-word-processing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "filler-word-processing", 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/benchflow-ai/skillsbench.git --path tasks-extra/video-filler-word-remover/environment/skills/filler-word-processing--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 benchflow-ai/skillsbench --skill filler-word-processing -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install benchflow-ai/skillsbench filler-word-processing --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/benchflow-ai/skillsbench.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/tasks-extra/video-filler-word-remover/environment/skills/filler-word-processing .gemini/skills/filler-word-processing && 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 "filler-word-processing" agent skill from https://github.com/benchflow-ai/skillsbench/tree/main/tasks-extra/video-filler-word-remover/environment/skills/filler-word-processing into .gemini/skills/filler-word-processing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "filler-word-processing", 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 benchflow-ai/skillsbench filler-word-processingInstalls 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 benchflow-ai/skillsbench --skill filler-word-processing -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/benchflow-ai/skillsbench.git skills-src && mkdir -p .github/skills && cp -r skills-src/tasks-extra/video-filler-word-remover/environment/skills/filler-word-processing .github/skills/filler-word-processing && 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 "filler-word-processing" agent skill from https://github.com/benchflow-ai/skillsbench/tree/main/tasks-extra/video-filler-word-remover/environment/skills/filler-word-processing into .github/skills/filler-word-processing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "filler-word-processing", 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 benchflow-ai/skillsbench --skill filler-word-processing -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install benchflow-ai/skillsbench filler-word-processing --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/benchflow-ai/skillsbench.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/tasks-extra/video-filler-word-remover/environment/skills/filler-word-processing .opencode/skills/filler-word-processing && 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 "filler-word-processing" agent skill from https://github.com/benchflow-ai/skillsbench/tree/main/tasks-extra/video-filler-word-remover/environment/skills/filler-word-processing into .opencode/skills/filler-word-processing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "filler-word-processing", 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.
Facts
- Skill name
filler-word-processing- GitHub stars
- 1.8k
- Token cost
- ~1.1k tokens
- SKILL.md length
- 167 words
- Files
- 1
- Skills in repo
- 178
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
Process filler word annotations to generate video edit lists.
- Working with timestamp annotations for removing speech disfluencies (um
- SKILL.md covers Annotation Format, Converting Annotations to Cut…, Merging Overlapping Segments and Complete Processing Pipeline, plus 2 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- You know) from audio/video content
What it does
Filler Word Processing is an agent skill from benchflow-ai/skillsbench. Process filler word annotations to generate video edit lists. Use when working with timestamp annotations for removing speech disfluencies (um, uh, like, you know) from audio/video content.
Its SKILL.md is about 1.1k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Media & Creative, covering AI video generation. The repository describes itself as: SkillsBench evaluates how well skills work and how effective agents are at using them. The licence is Apache-2.0.
When your agent uses it
- Working with timestamp annotations for removing speech disfluencies (um
- You know) from audio/video content
Example prompts
- “/filler-word-processing”
Requirements
- Python 3
What it can do on your machine
Read from SKILL.md and the folder at commit 9a1f4dd. It shows what the files ask for, not the result of running them.
Tool permissions
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.
Runs code
No scripts in the folder and no shell commands in SKILL.md (its code samples are python and json).
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Filler Word Processing loads about 1.1k tokens when it runs. Until then it costs about 53 tokens; SKILL.md has 167 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.
Safety
Auto-check passed
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.
SKILL.md
The full file from benchflow-ai/skillsbench at commit 9a1f4dd, republished under its Apache-2.0 licence (© benchflow-ai). 167 words, ~1,061 tokens.
Download SKILL.mdSave it as
.claude/skills/filler-word-processing/SKILL.md (or your agent's skills folder).- name
- filler-word-processing
- description
- Process filler word annotations to generate video edit lists. Use when working with timestamp annotations for removing speech disfluencies (um, uh, like, you know) from audio/video content.
Filler Word Processing
Annotation Format
Typical annotation JSON structure:
[
{"word": "um", "timestamp": 12.5},
{"word": "like", "timestamp": 25.3},
{"word": "you know", "timestamp": 45.8}
]Converting Annotations to Cut Segments
Each filler word annotation marks when the word starts. To remove it, use word-specific durations since different fillers have different lengths:
import json
# Word-specific durations (in seconds)
WORD_DURATIONS = {
"uh": 0.3,
"um": 0.4,
"hum": 0.6,
"hmm": 0.6,
"mhm": 0.55,
"like": 0.3,
"yeah": 0.35,
"so": 0.25,
"well": 0.35,
"okay": 0.4,
"basically": 0.55,
"you know": 0.55,
"i mean": 0.5,
"kind of": 0.5,
"i guess": 0.5,
}
DEFAULT_DURATION = 0.4
def annotations_to_segments(annotations_file, buffer=0.05):
"""
Convert filler word annotations to (start, end) cut segments.
Args:
annotations_file: Path to JSON annotations
buffer: Small buffer before the word (seconds)
Returns:
List of (start, end) tuples representing segments to remove
"""
with open(annotations_file) as f:
annotations = json.load(f)
segments = []
for ann in annotations:
word = ann.get('word', '').lower().strip()
timestamp = ann['timestamp']
# Use word-specific duration, fall back to default
word_duration = WORD_DURATIONS.get(word, DEFAULT_DURATION)
# Cut starts slightly before the word
start = max(0, timestamp - buffer)
# Cut ends after word duration
end = timestamp + word_duration
segments.append((start, end))
return segmentsMerging Overlapping Segments
When filler words are close together, merge their cut segments:
def merge_overlapping_segments(segments, min_gap=0.1):
"""
Merge segments that overlap or are very close together.
Args:
segments: List of (start, end) tuples
min_gap: Minimum gap to keep segments separate
Returns:
Merged list of segments
"""
if not segments:
return []
# Sort by start time
sorted_segs = sorted(segments)
merged = [sorted_segs[0]]
for start, end in sorted_segs[1:]:
prev_start, prev_end = merged[-1]
# If this segment overlaps or is very close to previous
if start <= prev_end + min_gap:
# Extend the previous segment
merged[-1] = (prev_start, max(prev_end, end))
else:
merged.append((start, end))
return mergedComplete Processing Pipeline
def process_filler_annotations(annotations_file, word_duration=0.4):
"""Full pipeline: load annotations -> create segments -> merge overlaps"""
# Load and create initial segments
segments = annotations_to_segments(annotations_file, word_duration)
# Merge overlapping cuts
merged = merge_overlapping_segments(segments)
return mergedTuning Parameters
| Parameter | Typical Value | Notes |
|---|---|---|
| word_duration | varies | Short fillers (um, uh) ~0.25-0.3s, single words (like, yeah) ~0.3-0.4s, phrases (you know, i mean) ~0.5-0.6s |
| buffer | 0.05s | Small buffer captures word onset |
| min_gap | 0.1s | Prevents micro-segments between close fillers |
Word Duration Guidelines
| Category | Words | Duration |
|---|---|---|
| Quick hesitations | uh, um | 0.3-0.4s |
| Sustained hums (drawn out while thinking) | hum, hmm, mhm | 0.55-0.6s |
| Quick single words | like, yeah, so, well | 0.25-0.35s |
| Longer single words | okay, basically | 0.4-0.55s |
| Multi-word phrases | you know, i mean, kind of, i guess | 0.5-0.55s |
Quality Considerations
- Too aggressive: Cuts into adjacent words, sounds choppy
- Too conservative: Filler words partially audible
- Sweet spot: Clean cuts with natural-sounding result
Test with a few samples before processing full video.
© benchflow-ai, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in tasks-extra/video-filler-word-remover/environment/skills/filler-word-processing of benchflow-ai/skillsbench.
Open the folder on GitHubat commit 9a1f4dd
Compare with similar skills
Filler Word Processing 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 |
|---|---|---|---|---|---|---|
| Filler Word Processing this skillbenchflow-ai/skillsbench | 1.8k | — | ~1.1k | Automated safety check: Pass | Apache-2.0 | |
| Video Generationbytedance/deer-flow | 83k | 4 repos | ~1.4k | Automated safety check: Pass | MIT | |
| Video Shotseternityspring/reelbench-skills | 868 | 2 repos | ~1.8k | Automated safety check: Notes | Apache-2.0 | |
| Video Cover Imageitwanger/toBeBetterJavaer | 18k | — | ~3.3k | Automated safety check: Pass | None | |
| Seedancesongguoxs/seedance-prompt-skill | 2.9k | 1 repos | ~2.5k | Automated safety check: Pass | None | |
| HyperFrames Video Entry Pointheygen-com/hyperframes | 59k | 3 repos | ~5.2k | Automated safety check: Pass | Apache-2.0 |
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Related
Categories
Questions about Filler Word Processing
What does Filler Word Processing do?
Process filler word annotations to generate video edit lists. Filler Word Processing is an agent skill from benchflow-ai/skillsbench. Process filler word annotations to generate video edit lists.
When should I use Filler Word Processing?
Filler Word Processing fits situations like: working with timestamp annotations for removing speech disfluencies (um; you know) from audio/video content.
How do I install Filler Word Processing in Claude Code?
Run `npx skills add benchflow-ai/skillsbench --skill filler-word-processing -a claude-code`. Or copy the skill folder (tasks-extra/video-filler-word-remover/environment/skills/filler-word-processing in benchflow-ai/skillsbench) into .claude/skills/filler-word-processing in your project. Claude Code loads it when a task matches its description.
How do I install Filler Word Processing in Codex?
Run `npx skills add benchflow-ai/skillsbench --skill filler-word-processing -a codex`. Or copy the skill folder (tasks-extra/video-filler-word-remover/environment/skills/filler-word-processing in benchflow-ai/skillsbench) into .agents/skills/filler-word-processing in your project. Codex loads it when a task matches its description.
Can I use Filler Word Processing 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 benchflow-ai/skillsbench --skill filler-word-processing -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/filler-word-processing, .gemini/skills/filler-word-processing, .github/skills/filler-word-processing and .opencode/skills/filler-word-processing in your project.
What does Filler Word Processing need to run?
SKILL.md names no scripts, command-line tools or credentials: Filler Word Processing is instructions for the agent only. Our summary lists: Python 3.
Does Filler Word Processing access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Filler Word Processing safe to install?
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.
What licence does Filler Word Processing use?
Filler Word Processing is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Filler Word Processing use?
About 1.1k tokens (SKILL.md is roughly 4.2k 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 Filler Word Processing?
Skills that share tags, products or a category with Filler Word Processing: Video Generation (bytedance/deer-flow, 83k stars), Video Shots (eternityspring/reelbench-skills, 868 stars), Video Cover Image (itwanger/toBeBetterJavaer, 18k stars) and Seedance (songguoxs/seedance-prompt-skill, 2.9k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Filler Word Processing?
benchflow-ai (a GitHub organization) maintains it in benchflow-ai/skillsbench, which has 1,832 GitHub stars. The repository holds 178 skills in this directory. The repository was last updated on July 23, 2026.
Source: benchflow-ai/skillsbench on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.