Borrowing it
Nothing to install: this file belongs to dustinblack/agent-dashboard. 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/dustinblack/agent-dashboard/main/AGENTS.mdgit clone --depth 1 https://github.com/dustinblack/agent-dashboardWrote 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/dustinblack/agent-dashboard/agents-md)<a href="https://agentmods.dev/instructions/dustinblack/agent-dashboard/agents-md"><img src="https://agentmods.dev/badge/instructions/dustinblack/agent-dashboard/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/dustinblack/agent-dashboard/agents-md"><img src="https://agentmods.dev/badge/instructions/dustinblack/agent-dashboard/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 | $0.00892 | $0.00892 |
| Opus 5.5 | $0.00357 | $0.00357 |
| Sonnet 5.5 | $0.00178 | $0.00178 |
| Haiku 4.5 | $0.00089 | $0.00089 |
Grade A, and why
agent-dashboard 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 — 68 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Behavior & Standards for Agent Dashboard
This document establishes the baseline behavior and technical standards for AI agents collaborating on the Agent Dashboard project.
Inspiration
This project is inspired by the following blog post:
Core Technical Stack
- Backend: Python 3.9+ with FastAPI and
python-socketio. - Frontend: React (TypeScript) via Vite,
xterm.js, andsocket.io-client. - Database: SQLite with SQLAlchemy ORM.
- Authentication: OIDC/OAuth for UI users; Static API Keys (Machine Tokens) for agents.
- Deployment: OCI containers (Podman/Docker) using
compose. - Integration: Python wrapper script using
ptyorpexpect.
Coding Standards
Python
- Formatting: Use
blackfor formatting. - Linting: Adhere to
flake8andpylintstandards. - Documentation: Use Google-style docstrings. Be verbose with documentation for new functions.
- Error Handling: Implement robust error handling and logging in all new functions.
- Style: Max line length of 88 characters.
Frontend (React/TypeScript)
- Formatting: Use
prettier. - Linting: Use
eslintwith project-specific configurations. - Language: Use TypeScript for all new components and logic.
- Styling: Use Tailwind CSS v4 utility classes. Custom CSS should only be used for overrides that Tailwind cannot express (e.g., third-party component styling).
Workflow & Safety
Research & Strategy
- Research Phase: Systematically map the codebase and validate assumptions. Prioritize empirical reproduction of issues.
- Strategy Phase: Share a concise summary of the strategy before execution.
- Plan Mode: Use
enter_plan_modefor architectural changes, new features, or complex refactoring.
Execution & Validation
- Atomic Changes: Keep changes surgical and focused on the sub-task.
- Testing: Every change must include verification logic (e.g., unit tests, integration tests, or reproduction scripts).
- Validation: Run project-specific build, lint, and test commands before finalizing.
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 · 68 lines · 892 tokens per session scan A cd0a789579d2
agent-dashboard AGENTS.md is an instructions file published in the GitHub repository dustinblack/agent-dashboard (17 stars, last pushed 28d ago), licensed Apache-2.0. It adds 892 tokens to every session, about $0.0036 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.
Other instructions, from other repositories
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).
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.
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, cache eligibility and rollout and applying the notice (cutover).
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.
vscode copilot-instructions.md
Copilot instructions for microsoft/vscode, covering vs code copilot instructions, project overview, root folders, core architecture (src/ folder) and built-in extensions (extensions/ folder).
deno copilot-instructions.md
Copilot instructions for denoland/deno, covering deno development guide for github copilot, network access, high level overview, key directories and key files to understand first.