ai-coding-config

A command for installing or updating reusable AI coding settings from the ai-coding-config repository. These settings can include editor rules, commands, agents, personalities, and GitHub workflows.

In plain words
What is it for?
Use it to create or update the shared configuration, inspect the current project, and copy suitable settings into that project.
Why use it?
It avoids manually copying and maintaining the same AI configuration across projects and computers.

Command for Claude Code

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 commands/technickai/claude_telemetry/ai-coding-config
Clone the repo
git clone --depth 1 https://github.com/TechNickAI/claude_telemetry

Made for: Claude Code.

Per session 13 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,822 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. 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 $0.00013 $0.01822
Opus 5 $0.00006 $0.00911
Sonnet 5 $0.00003 $0.00364
Haiku 4.5 $0.00001 $0.00182

Measured 3d ago against content hash 99565d668439, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

ai-coding-config 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.

.claude/commands/ai-coding-config.md · 196 lines

How it starts

The opening of the file, as written. The whole thing — 196 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AI Coding Configuration

Manages reusable AI configurations across machines and projects.

Understanding the System

First, get context about what ai-coding-config does:

The system contains Cursor rules, Claude commands, Claude Code Agents, personalities, and GitHub workflows in ~/.ai_coding_config. This command copies (not reads/rewrites) relevant configurations into projects and keeps them synced.

Arguments (Optional)

If user provides 'update' argument (/ai-coding-config update), skip to Goal 6. Otherwise, proceed conversationally through the setup goals.

Primary Goals

Goal 1: Ensure ~/.ai_coding_config Exists and Is Up to Date

If the repo isn't cloned yet, clone it:

git clone https://github.com/TechNickAI/ai-coding-config.git ~/.ai_coding_config

If it already exists, update it:

cd ~/.ai_coding_config && git pull

Then offer to set up the current project.

Goal 2: Understand the Project Context

Figure out what kind of project this is and what it needs:

  • Detect language/framework (Python/Django/FastAPI, TypeScript/React/Next.js, etc.)
  • Look for existing configurations to avoid duplicates
  • Understand the project's specific needs (API? Web app? CLI tool?)

Be specific about frameworks, not just languages. Django projects need different rules than FastAPI projects.

Goal 3: Present Relevant Options

Show the user what's available that matches their project:

  • Group rules by relevance (framework-specific first, then universal)
  • For each rule, read the description field from its frontmatter to explain what it does
  • Present personality options (one personality, or none) with descriptions from frontmatter
  • Present Claude Code Agents (default to all, but let them choose) with descriptions from frontmatter
  • Mention that VSCode settings, Prettier config, and GitHub workflows will be included by default
  • Separate personalities and agents from rules in your presentation

Read the full file on GitHub · 196 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. 3d ago First seen · 196 lines · 13 tokens per session scan A 99565d668439

Subscribe to this mod's changes

ai-coding-config is a command published in the GitHub repository TechNickAI/claude_telemetry (30 stars, last pushed 10mo ago), licensed MIT. It adds 13 tokens to every session and 1,822 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 2026-08-30.