What is audio-transcriber AGENTS.md?

Project instructions for an audio-transcription application, covering its Python technology, structure, agent workflow, and exact commands.

Use them when working on the application’s server, agent, modular skills, API client, or connections to external services.

They give coding agents the project context needed to make changes that fit the existing architecture and operating procedure.

audio-transcriber AGENTS.md — Instructions file for Codex and OpenCode by Knuckles-Team: Project instructions for an audio-transcription app

Install

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.

agentmods

npx agentmods add instructions/knuckles-team/audio-transcriber/agents-md

Clone the repo

git clone --depth 1 https://github.com/Knuckles-Team/audio-transcriber

Made for: Codex, OpenCode.

Wrote 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.

README.md

[![agentmods](https://agentmods.dev/badge/instructions/knuckles-team/audio-transcriber/agents-md.svg)](https://agentmods.dev/instructions/knuckles-team/audio-transcriber/agents-md)

Your own site

<a href="https://agentmods.dev/instructions/knuckles-team/audio-transcriber/agents-md"><img src="https://agentmods.dev/badge/instructions/knuckles-team/audio-transcriber/agents-md.svg" alt="Measured on agentmods" height="20"></a>

Per session 3,829 This file is loaded in full into every session.

When invoked 3,829 The same file — it is already loaded in full.

Security scan A 0 findings. Scan, not verified.

Origin 92% copy Near-identical to another mod in the catalogue.

Token cost

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	$0.03829	$0.03829
Opus 5	$0.01914	$0.01914
Sonnet 5	$0.00766	$0.00766
Haiku 4.5	$0.00383	$0.00383

Measured 3d ago against content hash fee79bfab038, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

audio-transcriber AGENTS.md 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 3d 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.

Origin

This is a copy

92% identical to servicenow-api AGENTS.md — 30 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

AGENTS.md · 301 lines

How it starts

The opening of the file, as written. The whole thing — 301 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AGENTS.md

Claude Code loads this file via CLAUDE.md (@AGENTS.md import) — the two stay in sync. Edit this file, not CLAUDE.md.

Tech Stack & Architecture

Language/Version: Python 3.10+
Core Libraries: agent-utilities, fastmcp, pydantic-ai
Key principles: Functional patterns, Pydantic for data validation, asynchronous tool execution.
Architecture:
- mcp_server.py: Main MCP server entry point and tool registration.
- agent.py: Pydantic AI agent definition and logic.
- skills/: Directory containing modular agent skills (if applicable).

Architecture Diagram

graph TD
    User([User/A2A]) --> Server[A2A Server / FastAPI]
    Server --> Agent[Pydantic AI Agent]
    Agent --> Skills[Modular Skills]
    Agent --> MCP[MCP Server / FastMCP]
    MCP --> Client[API Client / Wrapper]
    Client --> ExternalAPI([External Service API])

Workflow Diagram

sequenceDiagram
    participant U as User
    participant S as Server
    participant A as Agent
    participant T as MCP Tool
    participant API as External API

    U->>S: Request
    S->>A: Process Query
    A->>T: Invoke Tool
    T->>API: API Request
    API-->>T: API Response
    T-->>A: Tool Result
    A-->>S: Final Response
    S-->>U: Output

Commands (run these exactly)

Installation

pip install .[all]

Quality & Linting (run from project root)

pre-commit run --all-files

Execution Commands

audio-transcriber\naudio_transcriber.audio_transcriber:audio_transcriber\n# audio-transcriber-mcp\naudio_transcriber.mcp:mcp_server\n# audio-transcriber-agent\naudio_transcriber.agent:agent_server

Project Structure Quick Reference

MCP Entry Point → mcp_server.py
Agent Entry Point → agent.py
Source Code → audio_transcriber/
Skills → skills/ (if exists)

File Tree

├── .bumpversion.cfg\n├── .dockerignore\n├── .env\n├── .gitattributes\n├── .github\n│   └── workflows\n│       └── pipeline.yml\n├── .gitignore\n├── .pre-commit-config.yaml\n├── AGENTS.md\n├── Dockerfile\n├── LICENSE\n├── MANIFEST.in\n├── README.md\n├── audio_transcriber\n│   ├── __init__.py\n│   ├── __main__.py\n│   ├── agent.py\n│   ├── audio_transcriber.py\n│   ├── mcp_server.py\n│   └── personaplex_client.py\n├── compose.yml\n├── debug.Dockerfile\n├── docker-compose.personaplex.yaml\n├── mcp.compose.yml\n├── personaplex.Dockerfile\n├── pyproject.toml\n├── pytest.ini\n├── requirements.txt\n└── scripts\n    ├── test_personaplex_connection.py\n    └── validate_a2a_agent.py

Read the full file on GitHub · 301 lines

Changes

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.

3d ago First seen · 301 lines · 3,829 tokens per session scan A fee79bfab038

Subscribe to this mod's changes

audio-transcriber AGENTS.md is an instructions file published in the GitHub repository Knuckles-Team/audio-transcriber (2 stars, last pushed 5d ago), licensed MIT. It adds 3,829 tokens to every session, about $0.0191 per session on Opus 5. A static security scan graded it A with 0 findings. It is 92% identical to servicenow-api AGENTS.md, differing in 30 lines, and is treated as a copy.

Transformers a2a mcp-server openai transcription whisper

audio-transcriber AGENTS.md