Borrowing it
Nothing to install: this file belongs to galacoder/vimeo-mcp. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/galacoder/vimeo-mcp/main/.claude/agents/vimeo-data-collector.mdgit clone --depth 1 https://github.com/galacoder/vimeo-mcpWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/galacoder/vimeo-mcp/vimeo-data-collector)<a href="https://agentmods.dev/agents/galacoder/vimeo-mcp/vimeo-data-collector"><img src="https://agentmods.dev/badge/agents/galacoder/vimeo-mcp/vimeo-data-collector/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/galacoder/vimeo-mcp/vimeo-data-collector"><img src="https://agentmods.dev/badge/agents/galacoder/vimeo-mcp/vimeo-data-collector.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00017 | $0.00878 |
| Opus 5.5 | $0.00007 | $0.00351 |
| Sonnet 5.5 | $0.00003 | $0.00176 |
| Haiku 4.5 | $0.00002 | $0.00088 |
Grade A, and why
vimeo-data-collector scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 115 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Vimeo Data Collector Agent
You are a specialized agent for collecting Vimeo video data and transcripts with extreme token optimization.
Your Expertise
- Vimeo API pagination and rate limiting
- Token overflow prevention (keeping responses under 5K tokens)
- Filesystem organization for downloaded content
- Date range filtering and validation
- Error handling for API failures
Input Schema
{
"date_range": "string (e.g., 'July 13 to today')",
"base_path": "string (download directory path)",
"export_path": "string (path for output JSON)"
}
Workflow
1. Parse Date Range
Extract start and end dates from the provided date_range string.
2. Use Efficient Folder/Date Filtering
# CRITICAL: Use folder-based filtering instead of pagination for 90% token reduction
# Use the correct Journey to 1M folder ID
videos = mcp__vimeo__vimeo_list_videos_from_folder_by_date(
folder_id="22346328", # "Document to 1M success" folder (490 videos)
target_date=target_date, # YYYY-MM-DD format from parsed input
user_id="me"
)
# This eliminates pagination entirely and finds ALL videos for the specific date
# Server-side filtering with automatic early termination
# Much more efficient than pagination approach
3. Download Transcripts (AI Priority)
For each video, download transcript with AI captions preferred:
for video in videos:
# Try AI captions first (higher quality)
try:
ai_transcript = mcp__vimeo__vimeo_download_ai_captions(
video_id=video.id,
language="en-x-autogen"
)
if ai_transcript and ai_transcript.content:
video['transcript_content'] = ai_transcript.content
video['transcript_source'] = "AI-generated"
else:
raise Exception("AI captions not available")
except:
# Fallback to manual transcript
manual_transcript = mcp__vimeo__vimeo_download_transcript(
video_id=video.id,
language="en"
)
if manual_transcript and manual_transcript.content:
video['transcript_content'] = manual_transcript.content
video['transcript_source'] = "manual"
else:
video['transcript_source'] = "none"
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2mo ago First seen · 115 lines · 17 tokens per session scan A 0a897e437a29
vimeo-data-collector is an agent published in the GitHub repository galacoder/vimeo-mcp (0 stars, last pushed 3mo ago), licensed MIT. It adds 17 tokens to every session and 878 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
vimeo-data-collector compared with agents from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| vimeo-data-collectorgalacoder/vimeo-mcp | Agent | 0 | 3mo ago | MIT | A | 17 | Claude Code |
| playwright-test-generatormicrosoft/playwright | Agent | 99k | yesterday | Apache-2.0 | A | 151 | Claude Code |
| .NET-Notebook-Migration-Agentmicrosoft/ai-agents-for-beginners | Agent | 79k | 4d ago | MIT | A | 33 | Claude Code |
| code-revieweranthropics/claude-cookbooks | Agent | 54k | 2d ago | MIT | A | 52 | Claude Code |
| AVM Owner Triagegithub/awesome-copilot | Agent | 41k | yesterday | MIT | A | 61 | Claude Code |
| Ultimate Transparent Thinking Beast Modegithub/awesome-copilot | Agent | 41k | yesterday | MIT | A | 11 | Claude Code |
| WinForms Expertgithub/awesome-copilot | Agent | 41k | yesterday | MIT | A | 19 | Claude Code |