Borrowing it
Nothing to install: this file belongs to yoshimi-I/ai-engineer-teams. 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/yoshimi-I/ai-engineer-teams/main/AGENTS.mdgit clone --depth 1 https://github.com/yoshimi-I/ai-engineer-teamsWrote 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/yoshimi-i/ai-engineer-teams/agents-md)<a href="https://agentmods.dev/instructions/yoshimi-i/ai-engineer-teams/agents-md"><img src="https://agentmods.dev/badge/instructions/yoshimi-i/ai-engineer-teams/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/yoshimi-i/ai-engineer-teams/agents-md"><img src="https://agentmods.dev/badge/instructions/yoshimi-i/ai-engineer-teams/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 | $0.00602 | $0.00602 |
| Opus 5 | $0.00301 | $0.00301 |
| Sonnet 5 | $0.00120 | $0.00120 |
| Haiku 4.5 | $0.00060 | $0.00060 |
Grade A, and why
ai-engineer-teams 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 8d 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 — 57 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI Engineer Teams
Auto-scaling agent development pipeline with AI-DLC INCEPTION planning. The orchestrator starts minimal and spawns additional zellij panes on demand based on open issues, PRs, and post-merge state — it is not a fixed "N agent" pool.
This file is also loaded by Claude Code (via the CLAUDE.md symlink) and
Codex (as AGENTS.md), so the same project rules apply whether the pipeline
is driven by Kiro CLI, Claude Code, or Codex CLI. Pick one with
AI_RUNNER=kiro (default), AI_RUNNER=claude, or AI_RUNNER=codex; the
legacy KIRO_AI_RUNNER name is still honoured.
Slash commands live in .kiro/prompts/ and are mirrored at
.claude/commands/; skills live in .kiro/skills/ and are mirrored at
.claude/skills/. The .kiro/ paths are kept as the canonical location
because kiro-cli reads them natively — supported runners resolve the same
project guidance through their native surfaces.
First interaction
Tell me what you want to build. The INCEPTION workflow starts automatically:
- Workspace detection → analyze existing code (if any)
- Requirements analysis → clarify what to build
- User stories → define user-facing behavior (if needed)
- Architecture design → choose tech stack and structure (if needed)
- Issue generation → create GitHub issues for the pipeline
Language
Always respond in Japanese.
Rules
All rules are in .kiro/steering/development-rules.md. Key points:
- TDD: write tests before implementation
- 3-layer testing: unit + integration + E2E required
- Git: worktree isolation, Conventional Commits (English), squash merge
- PR comments and issues: always in English
- Parallel agents: assignee-based mutex on GitHub issues is the source of
truth.
issue/task.mdis an auxiliary local log. - Audit trail: all decisions recorded in
aidlc-docs/audit.md
After INCEPTION
Run ./scripts/start-pipeline.sh (or just start) to launch the
orchestrator in zellij. The orchestrator:
- Starts minimal (no agent panes)
- Adds
implementpanes when ready issues appear (AI planner decides count) - Adds
reviewpanes when APPROVED PRs need merge-manager handling - Adds
fix-reviewpanes when review changes / conflicts need fixing - Adds
e2e-hunt/ui-audit/watch-mainpanes based on merge state and env-var flags (ORCH_AUTO_*)
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.
- 8d ago First seen · 57 lines · 602 tokens per session scan A ade82793339f
ai-engineer-teams AGENTS.md is an instructions file published in the GitHub repository yoshimi-I/ai-engineer-teams (2 stars, last pushed 2mo ago), licensed MIT. It adds 602 tokens to every session, about $0.0030 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
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.
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.
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).
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).
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.
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.