Borrowing it
Nothing to install: this file belongs to aiblueprinthq/ai-blueprint. 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/aiblueprinthq/ai-blueprint/main/AGENTS.mdgit clone --depth 1 https://github.com/aiblueprinthq/ai-blueprintWrote 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/aiblueprinthq/ai-blueprint/agents-md)<a href="https://agentmods.dev/instructions/aiblueprinthq/ai-blueprint/agents-md"><img src="https://agentmods.dev/badge/instructions/aiblueprinthq/ai-blueprint/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/aiblueprinthq/ai-blueprint/agents-md"><img src="https://agentmods.dev/badge/instructions/aiblueprinthq/ai-blueprint/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 | $0.01133 | $0.01133 |
| Opus 5.5 | $0.00453 | $0.00453 |
| Sonnet 5.5 | $0.00227 | $0.00227 |
| Haiku 4.5 | $0.00113 | $0.00113 |
Grade A, and why
ai-blueprint 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 7d 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 — 100 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md
Instructions for AI coding agents working in this project. This is the cross-tool
entry point. Codex, Google Antigravity, and OpenCode read AGENTS.md. Other
compatible tools do too. Claude Code reads CLAUDE.md, which imports this file,
so there is a single source of truth.
Claude Code, Codex, and every other AI tool must not add AI attribution to
commits or pull requests, including AI Co-Authored-By trailers or generated-by
signatures. Preserve genuine human attribution. See
Commit and PR attribution
for optional tool settings.
What this is
A description of your project and the problem it solves.
This project is built with the AI Blueprint, a workflow layer, not an
app skeleton. To start a new project, scaffold the app first in an empty folder
(create-next-app, Vite, etc.), then overlay these files on top. Never run a
framework scaffolder inside a directory that already holds the blueprint files
(AGENTS.md, CLAUDE.md, .agents/, .claude/, blueprint/); it fails
because the directory isn't empty.
The workflow is defined by the local skills and context files below.
Proportional engineering
Build for established requirements, not hypothetical scale, threats, or future flexibility. Reuse existing code, the standard library, native platform features, and installed dependencies before adding machinery.
- Unknown scale or extensibility defaults to the smaller reversible design. Do not infer enterprise, multi-tenant, hostile-user, or compliance requirements.
- Derive trust and data-integrity boundaries from actual reachability: untrusted input, auth/session/ownership, shared persisted data, destructive operations, payments, secrets, and sensitive data.
- Ask only when an unknown materially changes behavior, architecture, persisted data, interoperability, a real security boundary, or cost. Otherwise choose the simplest repository-native implementation.
- Add an abstraction, dependency, service, configuration surface, compatibility layer, or security mechanism only for a current requirement.
- Simplicity never removes real trust-boundary validation, data-loss prevention, accessibility, explicit security requirements, configured tests, or project rules.
- Stack-specific template standards apply only when the project uses that stack.
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.
- 7d ago Changed · -237 lines · -3,011 tokens per session 73d00ac5e2c6
- 26d ago Changed · +2 lines · +35 tokens per session e3a06c6affb2
- 1mo ago Changed · +25 lines · +265 tokens per session 6099e0786323
- 1mo ago Changed · +22 lines · +160 tokens per session ce4ec2c658ac
- 1mo ago Changed · +20 lines · +222 tokens per session 241880359659
- 1mo ago Changed · +2 lines · +58 tokens per session 973dfdbd1e90
- 1mo ago Changed · +6 lines · +75 tokens per session 41d676d85eb1
- 2mo ago Changed · +17 lines · +217 tokens per session c1bf21c0f622
- 2mo ago Changed · +4 lines · +66 tokens per session d8f401b6fa16
- 2mo ago First seen · 239 lines · 3,046 tokens per session scan A 90e126e05cf9
ai-blueprint AGENTS.md is an instructions file published in the GitHub repository aiblueprinthq/ai-blueprint (493 stars, last pushed 7d ago), licensed MIT. It adds 1,133 tokens to every session, about $0.0045 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 2026-08-30.
ai-blueprint AGENTS.md compared with instructions from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| ai-blueprint AGENTS.mdaiblueprinthq/ai-blueprint | Instructions file | 493 | 7d ago | MIT | A | 1,133 | Codex, OpenCode |
| vscode buildNext.instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 9,719 | GitHub Copilot |
| next.js AGENTS.mdvercel/next.js | Instructions file | 143k | yesterday | MIT | A | 7,461 | Codex, OpenCode |
| langchain AGENTS.mdlangchain-ai/langchain | Instructions file | 149k | yesterday | MIT | A | 4,680 | Codex, OpenCode |
| vscode oss-third-party-notices.instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 5,516 | GitHub Copilot |
| vscode copilot-instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 3,093 | GitHub Copilot |
| deepseek-harness AGENTS.mddeepseek-ai/deepseek-harness | Instructions file | 274k | 2d ago | MIT | A | 4,313 | Codex, OpenCode |