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.
git clone --depth 1 https://github.com/TechNickAI/ai-coding-configWrote 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/commands/technickai/ai-coding-config/generate-agents-file)<a href="https://agentmods.dev/commands/technickai/ai-coding-config/generate-agents-file"><img src="https://agentmods.dev/badge/commands/technickai/ai-coding-config/generate-agents-file/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/commands/technickai/ai-coding-config/generate-agents-file"><img src="https://agentmods.dev/badge/commands/technickai/ai-coding-config/generate-agents-file.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 | $0.00024 | $0.02342 |
| Opus 5.5 | $0.00010 | $0.00937 |
| Sonnet 5.5 | $0.00005 | $0.00468 |
| Haiku 4.5 | $0.00002 | $0.00234 |
Grade A, and why
generate-AGENTS-file 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 25d 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 — 307 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Generate AGENTS.md
Creates or updates AGENTS.md - a universal project context file for AI coding
assistants (Claude Code, Cursor, GitHub Copilot, etc.).
Purpose: Prevent mistakes by providing context the AI would otherwise lack.
What belongs in AGENTS.md:
- Domain knowledge that isn't obvious from code structure
- Constraints that cause silent failures if violated
- Architectural decisions that affect how code should be written
- References to detailed rules via @ imports
What does NOT belong:
- Commands (LLMs know how to run pnpm, npm, pytest, etc.)
- Generic best practices (LLMs already know these)
- Project descriptions (that's what README is for)
- Anything an LLM would figure out from reading the code
The test: "Would an AI make a mistake without this specific piece of context?" If no, cut it.
Add an "Always Apply Rules" section at the top with @ references:
## Always Apply Rules
Core project rules that apply to all tasks:
@rules/git-interaction.mdc @rules/typescript-coding-standards.mdc
Why use @ references instead of extraction:
- AI coding assistants load the full rule when they see
@path/to/rule.mdc - Ensures rules stay up-to-date without AGENTS.md edits
- No token overhead from duplicating rule content
- Single source of truth for all conventions
When to still extract (rare):
- Only if a rule has a specific command or constraint worth highlighting elsewhere
- Don't duplicate - reference in "Always Apply Rules" section instead
From README.md:
- Project tech stack and versions (be specific: "Next.js 14" not just "Next.js")
- Key commands (dev, build, test)
- Skip: Project description, installation steps for end users, contributing guides
From .claude/context.md (if exists):
- Identity or personality instructions (if project uses custom personality)
- Any project-specific AI behavior guidelines
From recent git commits (last 10):
- Observe commit message style and conventions
- Identify patterns (emoji usage, conventional commits, etc.)
# Project Context for AI Assistants
## Always Apply Rules
Core project rules that apply to all tasks:
[@ references to your alwaysApply: true rules]
## Project Overview
Brief description of what this project is.
## Tech Stack
- Framework/language with specific versions
- Key dependencies that affect how code should be written
- Build tools and their commands
## Project Structure
- `dir/` - Brief purpose (only if non-obvious)
- Focus on where AI should look for specific types of files
## Code Conventions
DO:
- Specific patterns to follow
- Required practices unique to this project
- Non-obvious constraints that prevent mistakes
DON'T:
- Specific anti-patterns to avoid
- Project-specific constraints
- Explicitly forbidden practices (like --no-verify if that's a rule)
## Git Workflow
- Commit message format (if specific convention exists)
- Important: Include critical git constraints from always-apply rules
- Skip generic emoji lists - one example is enough
- Skip restating the full commit format if it's standard
## Important Notes
- Non-obvious gotchas or warnings
- Critical context that prevents mistakes
- Dependencies between systems
- Unique aspects of this project that AI must understand
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.
- 25d ago First seen · 307 lines · 24 tokens per session scan A abcddb90d593
generate-AGENTS-file is a command published in the GitHub repository TechNickAI/ai-coding-config (24 stars, last pushed 26d ago), licensed MIT. It adds 24 tokens to every session and 2,342 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 2026-09-22.
Other commands, from other repositories
destination
Set, clear, or show the workspace prompts destination — use this when running claude above multiple repos and you want all prompts to land in one shared store.
doctor
Diagnose Promptcellar — check hook binaries, plugin wiring, resolved config.
log
Show the last N captured prompts in this repo (git-log style, defaults to 10).
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.