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 skills add vre/flow-state --skill litegit clone --depth 1 https://github.com/vre/flow-stateWrote 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/skills/vre/flow-state/lite)<a href="https://agentmods.dev/skills/vre/flow-state/lite"><img src="https://agentmods.dev/badge/skills/vre/flow-state/lite/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/skills/vre/flow-state/lite"><img src="https://agentmods.dev/badge/skills/vre/flow-state/lite.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 | $0.00035 | $0.00886 |
| Opus 5.5 | $0.00014 | $0.00354 |
| Sonnet 5.5 | $0.00007 | $0.00177 |
| Haiku 4.5 | $0.00003 | $0.00089 |
Grade A, and why
youtube-to-markdown scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 133 lines — stays where its author put it; the contents beside it link to each section on GitHub.
YouTube to Markdown (Lite Variant)
Optimized variant: No polish steps (4, 7, 8) + combined workflows (5+6, 10a+10b). Result: 2 subagents for minimum cost.
Execute all steps sequentially without asking for user approval.
Step 0: Check extracted before
python3 ./check_existing.py "<YOUTUBE_URL>" "<output_directory>"
If returns exists: true: Skip to Step 10 (comments).
Step 1: Extract data
python3 extract_data.py "<YOUTUBE_URL>" "<output_directory>"
Step 2: Extract transcript
If video language is en, proceed directly. If non-English, ask user which language.
python3 extract_transcript.py "<YOUTUBE_URL>" "<output_directory>" "<LANG_CODE>"
Fallback (only if transcript unavailable)
python3 extract_transcript_whisper.py "<YOUTUBE_URL>" "<output_directory>"
Step 3: Deduplicate transcript
python3 ./deduplicate_vtt.py "<output_directory>/${BASE_NAME}_transcript.vtt" "<output_directory>/${BASE_NAME}_transcript_dedup.md" "<output_directory>/${BASE_NAME}_transcript_no_timestamps.txt"
Copy dedup as final transcript (no polish steps):
cp "<output_directory>/${BASE_NAME}_transcript_dedup.md" "<output_directory>/${BASE_NAME}_transcript.md"
Step 5: Summarize transcript (combined summarize + tighten)
task_tool:
- subagent_type: "general-purpose"
- model: "sonnet"
- prompt:
INPUT: <output_directory>/${BASE_NAME}_transcript_no_timestamps.txt
OUTPUT: <output_directory>/${BASE_NAME}_summary_tight.md
FORMATS: ./summary_formats.md
1. Classify content type:
- TIPS: gear reviews, rankings, practical advice
- INTERVIEW: podcasts, conversations, Q&A
- EDUCATIONAL: concept explanations, analysis
- TUTORIAL: step-by-step instructions
2. Read FORMATS and create summary using format for detected type.
3. Self-review: Cut fluff, enforce <10% of transcript bytes, prefer lists over prose.
4. Save final tightened summary to OUTPUT.
Rules:
- Skip ads, sponsors, self-promotion
- Preserve original language
ACTION REQUIRED: Use Write tool NOW to save to OUTPUT file.
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.
- 1mo ago First seen · 133 lines · 35 tokens per session scan A e645d0fdad52
youtube-to-markdown is a skill published in the GitHub repository vre/flow-state (11 stars, last pushed 25d ago), licensed MIT. It adds 35 tokens to every session and 886 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 2026-08-30.
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