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 instructions/mir-am/skills-agents-ai-coding/agents-mdgit clone --depth 1 https://github.com/mir-am/skills-agents-ai-codingWrote 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/instructions/mir-am/skills-agents-ai-coding/agents-md)<a href="https://agentmods.dev/instructions/mir-am/skills-agents-ai-coding/agents-md"><img src="https://agentmods.dev/badge/instructions/mir-am/skills-agents-ai-coding/agents-md.svg" alt="Measured on agentmods" 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 | $0.01693 | $0.01693 |
| Opus 5 | $0.00847 | $0.00847 |
| Sonnet 5 | $0.00339 | $0.00339 |
| Haiku 4.5 | $0.00169 | $0.00169 |
Grade A, and why
skills-agents-ai-coding 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 5d 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 — 161 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md
Project Overview
This is Mir's Agents & Skills for AI Coding Assistants, a collection of reusable Agent Skills and agents for CLI coding assistants, hosted in the opencode-skills repository. Skills are markdown-based instruction sets that teach AI agents specific workflows using the open Agent Skills format. Agents are markdown-based definitions that create specialized AI assistants with custom prompts, tools, and permissions.
Repository Structure
opencode-skills/
skills/ # Skills: one directory per skill, each containing a SKILL.md
changelog-bump-ver/
SKILL.md
gh-copilot-review-read/
SKILL.md
gh-copilot-review/
SKILL.md
gh-copilot-review-resolve/
SKILL.md
gh-cr-submit/
gh-issue/
gh-issue-fix/
gh-pr-review/
gh-release/
git-branch/
git-commit/
git-pr/
git-push/
make-changelog/
save-plan/
work-report/
session-note/
agents/ # Agents: flat .md files, one per agent
code-review.md
sync.sh # Installs/updates skills for supported CLIs and agents for OpenCode
README.md
AGENTS.md # This file
Skill Anatomy
Each skill is a directory under skills/ containing a SKILL.md file.
-
YAML frontmatter with metadata in the repository source format:
--- name: <skill-name> description: <one-line description> license: MIT compatibility: opencode metadata: audience: developers workflow: <category> category: <category> ---Non-OpenCode sync targets receive transformed copies of this source file. Installs for
ghcandccstrip repo-specific metadata fields and rewrite workspace paths for their target environment. -
Markdown body with structured sections:
## What I do- Bullet list of capabilities## When to use me- Trigger conditions- Workflow sections with step-by-step instructions
- Code blocks with exact commands to run
- Edge cases and error handling
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.
- 5d ago First seen · 161 lines · 1,693 tokens per session scan A 05899e9a65bc
skills-agents-ai-coding AGENTS.md is an instructions file published in the GitHub repository mir-am/skills-agents-ai-coding (2 stars, last pushed 4mo ago), licensed MIT. It adds 1,693 tokens to every session, about $0.0085 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 2026-08-31.
Other instructions, from other repositories
asm AGENTS.md
AGENTS.md instructions for luongnv89/asm, covering agents.md, when to delegate, definitions, shared boundaries and editing this file.
beads AGENTS.md
AGENTS.md instructions for gastownhall/beads, covering agent instructions, key sections, project scope, pr safety for agents and visual design anti-patterns.
ai-ready AGENTS.md
AGENTS.md instructions for johnpapa/ai-ready, covering ai-ready repo — agent guide, repository structure, tech stack, build & run and testing.
ai-ready copilot-instructions.md
Copilot instructions for johnpapa/ai-ready, covering copilot instructions — ai-ready, project type, writing conventions, markdown and yaml (skill frontmatter, workflows, issue templates).
remind AGENTS.md
Instructions for sandst1/remind, covering remind - development guide for ai agents, project overview, architecture, key abstractions and data models (models.py).
github-azure-agentic-journeys AGENTS.md
Instructions for DanWahlin/github-azure-agentic-journeys, covering agents and skills, journeys, prerequisites, agent & skill system and available agents.