voice-to-article: Instructions file for Codex

AGENTS.md

voice-to-article AGENTS.md is an instructions file for Codex, OpenCode from axelfreeman/voice-to-article. It costs 1,700 tokens per session, scanned A, original, MIT.

Project instructions for turning voice recordings into published articles. The workflow transcribes a person's voice, extracts its structure, optionally researches facts when explicitly requested, writes SEO-focused HTML, and deploys it.

In plain words
What is it for?
Use them to process voice memos into articles, including transcription, article structure, search markup, cross-links, and publishing. They are aimed at solopreneurs who want to dictate expertise instead of writing manually.
Why use it?
They define when this repository is appropriate and prevent agents from drafting content without the required voice source or using the workflow for unrelated page types.

Instructions file for CodexOpenCode

Written for Codex and OpenCode: the file is AGENTS.md. Also seen: mentions CLAUDE.md; positional $N argument; mentions Claude Code.

This is axelfreeman/voice-to-article's own configuration. It tells Codex and OpenCode how to work on voice-to-article itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything voice-to-article configures →

Reuse

Borrowing it

Nothing to install: this file belongs to axelfreeman/voice-to-article. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/axelfreeman/voice-to-article/main/AGENTS.md
Clone the repo
git clone --depth 1 https://github.com/axelfreeman/voice-to-article

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.

agentmods badge for voice-to-article AGENTS.md

README.md
[![agentmods](https://agentmods.dev/badge/instructions/axelfreeman/voice-to-article/agents-md.svg)](https://agentmods.dev/instructions/axelfreeman/voice-to-article/agents-md)
Your own site
<a href="https://agentmods.dev/instructions/axelfreeman/voice-to-article/agents-md"><img src="https://agentmods.dev/badge/instructions/axelfreeman/voice-to-article/agents-md.svg" alt="Measured on agentmods" height="20"></a>
Per session 1,700 This file is loaded in full into every session.
When invoked 1,700 The same file — it is already loaded in full.
Security scan A 1 finding. Scan, not verified.
Origin original No closer match found 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.

ModelPer sessionOnce invoked
Fable 5.1 $0.01700 $0.01700
Opus 5 $0.00850 $0.00850
Sonnet 5 $0.00340 $0.00340
Haiku 4.5 $0.00170 $0.00170

Measured 6d ago against content hash 46e6c41d799e, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

voice-to-article AGENTS.md scanned grade A with 1 finding 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 6d 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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

- Verify: `curl -sI [url]` → 200
AGENTS.md · 175 lines

How it starts

The opening of the file, as written. The whole thing — 175 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AGENTS.md — Voice → Article Pipeline

Instructions for AI coding agents (Claude Code, Codex CLI, Cursor, Hermes Agent) working with this repo.


Who You Are

You are a Voice-to-Article pipeline agent. Your job: receive voice memos → transcribe → extract structure → research semantics → write SEO-optimized HTML → deploy to a live site.

You work for solopreneurs who have domain expertise but hate writing. You handle the boring parts (meta tags, schemas, FTP, cross-links) so the author can just talk.


When To Use This

Use this repo when:

  • The user says "turn this voice memo into an article" or "publish this"
  • The user wants SEO + AEO (Article Schema, FAQPage Schema, llms.txt)
  • The user wants zero-tool publishing — no Ahrefs, no WordPress, no copywriters
  • The user is building a content flywheel powered by voice dictation

Do NOT use this for:

  • One-off AI-generated blog posts with no voice input (wrong tool — this pipeline starts with a human voice)
  • Non-blog content (landing pages, docs, product pages)
  • Content the user hasn't dictated yet (never pre-write without voice source)

Methodology (Pipeline)

📱 Voice Memo → 🗣️ Whisper → 🧠 Structure → 🔍 Semantics → ✍️ HTML → 🚀 Deploy

Phase 0: Semantic Research (only when explicitly asked)

  • Any language: Google Suggest (suggestqueries.google.com, set hl= accordingly)
  • Trending: Google Trends (pytrends)
  • Group into 4-7 intent clusters, present as scaffold, STOP — wait for dictation

Phase 1: Transcribe

  • OpenAI Whisper API (whisper-1), $0.006/min
  • Keep raw transcript — slang, repetitions, profanity — all of it
  • Post bullet summary back to user to confirm you're tracking

Phase 2: Extract Structure

From raw transcript: core thesis (1 sentence), sections (6-10 H2s), supporting points, FAQ candidates (4-6), keywords (6-10)

Phase 3: Write HTML

  • Full HTML page with Article + FAQPage JSON-LD Schema
  • TLDR block, 6-10 H2 sections, 2-4 card blocks (emoji titles), FAQ section
  • Deploy to /var/www/axelfreeman.com/blog/[slug].html
  • Preserve author's voice — no corporate-speak. "I" not "we."

Read the full file on GitHub · 175 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.

  1. 6d ago First seen · 175 lines · 1,700 tokens per session scan A 46e6c41d799e

Subscribe to this mod's changes

voice-to-article AGENTS.md is an instructions file published in the GitHub repository axelfreeman/voice-to-article (21 stars, last pushed 9d ago), licensed MIT. It adds 1,700 tokens to every session, about $0.0085 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other instructions, from other repositories

next.js AGENTS.md

AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.

vercel/next.js · 7,296 tokens

codex AGENTS.md

AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.

openai/codex · 5,182 tokens

vscode buildNext.instructions.md

Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).

microsoft/vscode · 6,785 tokens

vscode oss-third-party-notices.instructions.md

Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).

microsoft/vscode · 5,001 tokens

langchain AGENTS.md

AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.

langchain-ai/langchain · 4,469 tokens

spec-kit AGENTS.md

AGENTS.md instructions for github/spec-kit, covering agents.md, about spec kit and specify, quickstart — add a new integration in 5 steps, integration architecture and integrationmanifest — file tracking.

github/spec-kit · 7,104 tokens