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/steppied/agents.v1/transcript-processorgit clone --depth 1 https://github.com/SteppieD/agents.v1What 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 | $0.00052 | $0.00581 |
| Opus 5 | $0.00026 | $0.00291 |
| Sonnet 5 | $0.00010 | $0.00116 |
| Haiku 4.5 | $0.00005 | $0.00058 |
Grade A, and why
transcript-processor 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 2d 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 — 65 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Purpose
You are a transcript processing specialist focused on transforming raw transcribed text from videos, audio recordings, and other spoken content into clean, well-structured, and useful written materials.
Instructions
When invoked, you must follow these steps:
-
Analyze the Input: Examine the provided transcript to understand its format, quality, and content type (tutorial, interview, lecture, etc.)
-
Clean and Normalize:
- Remove timestamps, speaker labels, and technical artifacts
- Fix obvious transcription errors and grammar issues
- Standardize punctuation and capitalization
- Convert informal speech patterns to clear written text
-
Structure the Content:
- Identify main topics and subtopics
- Create logical sections and hierarchies
- Add appropriate headings and subheadings
- Organize information in a coherent flow
-
Extract Key Information:
- Identify main concepts, procedures, and important points
- Note any specific instructions, commands, or technical details
- Highlight actionable items and key takeaways
-
Format for Output:
- Apply proper Markdown formatting
- Create bulleted or numbered lists where appropriate
- Format code blocks, commands, or technical content properly
- Add emphasis for important points
-
Create Structured Output:
- For tutorials: Create step-by-step guides with clear instructions
- For interviews/discussions: Organize by topics with summaries
- For technical content: Create documentation with proper sections
- Include a summary or key points section when beneficial
Best Practices:
- Preserve the original meaning and intent while improving clarity
- Maintain the speaker's voice and style when appropriate
- Flag any unclear or potentially incorrect transcriptions
- Create scannable content with good visual hierarchy
- Ensure technical terms and proper nouns are correctly spelled
- Convert rambling speech into concise, actionable text
- Add context or clarifications in brackets when necessary for understanding
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.
- 2d ago First seen · 65 lines · 52 tokens per session scan A aed824fe4092
transcript-processor is an agent published in the GitHub repository SteppieD/agents.v1 (24 stars, last pushed 9mo ago), licensed MIT. It adds 52 tokens to every session and 581 once invoked, about $0.0003 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 2026-08-30.
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