Borrowing it
Nothing to install: this file belongs to HanZephyr/AI-Data-Access-Gateway. 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/HanZephyr/AI-Data-Access-Gateway/main/AGENTS.mdgit clone --depth 1 https://github.com/HanZephyr/AI-Data-Access-GatewayWrote 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/hanzephyr/ai-data-access-gateway/agents-md)<a href="https://agentmods.dev/instructions/hanzephyr/ai-data-access-gateway/agents-md"><img src="https://agentmods.dev/badge/instructions/hanzephyr/ai-data-access-gateway/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 | $0.00372 | $0.00372 |
| Opus 5 | $0.00186 | $0.00186 |
| Sonnet 5 | $0.00074 | $0.00074 |
| Haiku 4.5 | $0.00037 | $0.00037 |
Grade A, and why
AI-Data-Access-Gateway 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 6d 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.
What it actually says
AGENTS
Repository Purpose
AI Data Access Gateway is a secure data access gateway MVP for AI agents. It exposes governed metadata discovery and read-only runtime data access with authorization, SQL safety checks, masking, runtime decrypt controls, and audit logging.
Source Of Truth
- Current code, tests, and runnable configuration are the source of truth.
- Historical design docs under
docs/superpowers/specs/are useful context but must not override the implemented repository state. - If a historical design doc conflicts with current code, follow current code and update outward-facing docs accordingly.
Important Directories
src/adg/: backend application codetests/: backend unit and integration coverageweb/: React + Vite admin consoleexamples/: demo seed and example client flowsdocs/en/: English release-facing project docsdocs/zh-CN/: Chinese mirror docsdocs/superpowers/: internal planning, spec, acceptance, and repository memory artifacts
Working Rules
- Keep release-facing English and Chinese docs in sync.
- Do not describe roadmap items as current features.
- Prefer minimal, bounded edits over broad unrelated cleanup.
- Do not remove or overwrite internal planning artifacts unless explicitly asked.
- Preserve concurrent user or teammate changes outside the files you have been asked to own.
- When release scope changes materially, update status and roadmap docs alongside any landing-page copy that depends on them.
Verification Commands
uv sync --extra dev --extra all
uv run --extra dev pytest
uv run --extra dev ruff check .
uv run --extra dev mypy src tests
Set-Location web
npm ci
npm test
npm run build
npm run audit:prod
Set-Location ..
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.
- 6d ago First seen · 46 lines · 372 tokens per session scan A 3a21e72309bd
AI-Data-Access-Gateway AGENTS.md is an instructions file published in the GitHub repository HanZephyr/AI-Data-Access-Gateway (5 stars, last pushed 23d ago), licensed Apache-2.0. It adds 372 tokens to every session, about $0.0019 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.