Borrowing it
Nothing to install: this file belongs to CSKishan/ame-skill. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/CSKishan/ame-skill/main/AGENTS.mdgit clone --depth 1 https://github.com/CSKishan/ame-skillWrote 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/cskishan/ame-skill/agents-md)<a href="https://agentmods.dev/instructions/cskishan/ame-skill/agents-md"><img src="https://agentmods.dev/badge/instructions/cskishan/ame-skill/agents-md/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/instructions/cskishan/ame-skill/agents-md"><img src="https://agentmods.dev/badge/instructions/cskishan/ame-skill/agents-md.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 | $0.01499 | $0.01499 |
| Opus 5.5 | $0.00600 | $0.00600 |
| Sonnet 5.5 | $0.00300 | $0.00300 |
| Haiku 4.5 | $0.00150 | $0.00150 |
Grade A, and why
ame-skill 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 1mo 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 — 179 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AME + EMA — Agent Pipeline Documentation
What Is This?
Two VS Code Copilot Chat skills that work as a pipeline:
/ame → single compiled interview → .ame/spec.md
/ema → layer analysis → .ame/plan.md → chunked execution
/ame (Ask Me Exhaustively) closes the requirement gap before any code is written. It compiles all applicable interview questions into one message across five quality dimensions — tech stack, architecture, security, quality, and edge cases — and produces a structured spec file from your answers. Total exchanges: 2–3.
/ema (Enclose My Analysis) reads that spec, identifies which architectural layers the project spans, and generates a dependency-ordered, chunked implementation plan. It offers chunk-by-chunk execution (with per-chunk confirmation) or a "run all" mode for one-shot execution.
Requirements
- VS Code with GitHub Copilot Chat
- Agent mode — both skills write files to the workspace; Ask mode is not sufficient
- Optional: context7 MCP server for live library documentation during the interview
Install
Manual
- Clone or download this repository
- Copy
skills/ame/SKILL.mdto your agents skills folder:- Windows:
%USERPROFILE%\.agents\skills\ame\SKILL.md - macOS/Linux:
~/.agents/skills/ame/SKILL.md
- Windows:
- Copy
skills/ema/SKILL.mdto:- Windows:
%USERPROFILE%\.agents\skills\ema\SKILL.md - macOS/Linux:
~/.agents/skills/ema/SKILL.md
- Windows:
- Restart VS Code
Via skills CLI
npx skills add github:CSKishan/ame-skill
Usage
Full workflow
1. Open VS Code Copilot Chat in Agent mode
2. Describe what you want to build, then invoke:
/ame I want to build a REST API for managing IoT device telemetry
3. AME detects scope, compiles all applicable dimension questions into
one message. Answer everything at once — free-form or labelled.
4. AME processes your answers, writes .ame/spec.md, and presents a
plain-English summary. Confirm it or correct anything in one reply.
5. When done, invoke:
/ema
6. EMA reads .ame/spec.md, generates .ame/plan.md,
shows a chunk summary, and waits for your confirmation to execute.
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.
- 1mo ago First seen · 179 lines · 1,499 tokens per session scan A 400d256202b6
ame-skill AGENTS.md is an instructions file published in the GitHub repository CSKishan/ame-skill (5 stars, last pushed 6mo ago), licensed MIT. It adds 1,499 tokens to every session, about $0.0060 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 2026-08-31.
Other instructions, from other repositories
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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.