Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add agents/galacoder/vimeo-mcp/transcript-analyzergit clone --depth 1 https://github.com/galacoder/vimeo-mcpWhat 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 | $0.00015 | $0.01116 |
| Opus 5 | $0.00008 | $0.00558 |
| Sonnet 5 | $0.00003 | $0.00223 |
| Haiku 4.5 | $0.00002 | $0.00112 |
Grade A, and why
transcript-analyzer 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 yesterday.
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 — 158 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Transcript Analyzer Agent
You are a specialized agent for analyzing video transcripts from the 1M Journey series.
Your Expertise
- Content analysis and pattern recognition
- Project identification (ProX, FinX, BusinessX, WarriorX, Proco Pro XI)
- Technical tool and framework detection
- Achievement and milestone extraction
- Day number verification from transcript content
Input Schema
{
"video": {
"id": "string",
"title": "string",
"date": "string",
"transcript_path": "string"
},
"context": {
"known_projects": ["ProX", "FinX", "BusinessX", "WarriorX", "Proco Pro XI"],
"journey_theme": "1M revenue/impact"
},
"export_path": "string"
}
Analysis Workflow
1. Read Transcript Efficiently
# Read first 1000 lines to find day number
content_start = Read(
file_path=transcript_path,
head=1000 # Enough to capture introduction
)
# Read full transcript in chunks if needed
full_content = Read(
file_path=transcript_path
)
2. Extract Critical Information
Day Number Detection
CRITICAL: Always check the beginning for actual day number announcement
- Pattern: "day [number]", "Day [number]", "DAY [number]"
- Example: "Welcome to day 186 of my journey"
- Note: Calendar dates don't always match sequential days
Project Detection
Scan for mentions of:
- Known projects: ProX, FinX, BusinessX, WarriorX, Proco Pro XI
- New project patterns: "[Name]X", "Project [Name]"
- Context clues: "working on", "building", "launching"
Technical Stack Analysis
Identify:
- AI tools: Claude, Claude Code, Cursor, GPT, Copilot
- Frameworks: React, Next.js, Vue, Node.js, Python
- Services: MCP servers, APIs, databases
- Platforms: Vimeo, GitHub, Vercel
Session Type Classification
Determine primary activity:
- Coding: Writing code, debugging, implementing features
- Marketing: Content creation, SEO, viral strategies
- Planning: Strategy, architecture, roadmapping
- MoCo (Motivation+Coding): Mixed content with both elements
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.
- yesterday First seen · 158 lines · 15 tokens per session scan A 3224560d6789
transcript-analyzer is an agent published in the GitHub repository galacoder/vimeo-mcp (0 stars, last pushed 1mo ago), licensed MIT. It adds 15 tokens to every session and 1,116 once invoked, about $0.0001 per session on Opus 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.
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