Borrowing it
Nothing to install: this file belongs to aviz92/ai-agents-marketplace. 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/aviz92/ai-agents-marketplace/main/AGENTS.mdgit clone --depth 1 https://github.com/aviz92/ai-agents-marketplaceWrote 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/aviz92/ai-agents-marketplace/agents-md)<a href="https://agentmods.dev/instructions/aviz92/ai-agents-marketplace/agents-md"><img src="https://agentmods.dev/badge/instructions/aviz92/ai-agents-marketplace/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/aviz92/ai-agents-marketplace/agents-md"><img src="https://agentmods.dev/badge/instructions/aviz92/ai-agents-marketplace/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 | $0.00635 | $0.00635 |
| Opus 5 | $0.00318 | $0.00318 |
| Sonnet 5 | $0.00127 | $0.00127 |
| Haiku 4.5 | $0.00064 | $0.00064 |
Grade A, and why
ai-agents-marketplace 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 10d 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 — 60 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Instructions
Versioning
Every time an artifact's content or metadata changes (anything under skills/,
plugins/, or rules/), bump the version field in its metadata.yaml.
This is how the CLI detects that an update is available.
Git
Never commit or push without explicit human approval.
Avi Zaguri — Workspace Rules
Senior Python developer. Be direct, concise, no fluff.
Rule Precedence
NEVER print the changes made to a file in the response. Always summarize the changes instead.
Project-local CLAUDE.md or AGENTS.md in the repo overrides this file. If they conflict, follow the project-local rules and flag the conflict once.
Plan Mode Response Format
- In plan mode, respond in 100 words or less
- Use numbered steps only
- No explanations, no commentary, no context
Libraries (check first)
I maintain an open-source Python ecosystem under github.com/aviz92/. Before implementing any utility — logging, exceptions, CLI scaffolding, API clients (GitHub/GitLab/Jira/Notion), DB access, email, secrets, DRF CRUD, test parameterization, test reporting, or a new project scaffold — consult LIBRARIES.md first. Before writing code that uses a library, fetch its current README from https://github.com/aviz92/<library_name>. Do not rely on memory for API shape.
Behavior
- Act autonomously on small-to-medium tasks: bug fixes, single-file changes, adding tests, refactoring within one module, dependency bumps, doc edits.
- Ask first for: changes touching 3+ files, public API changes, new dependencies, schema or migration changes, anything that alters project structure.
- Proactively flag tech debt, performance, and security issues.
Environment
- Package manager:
uvexclusively — never pip - Python: >=3.12
Security
- Never read/write .env, secrets/, credentials, token files
- Never commit API keys or passwords
- Always use parameterized queries
Git
- Conventional Commits (feat:, fix:, refactor:, test:, chore:, docs:)
- Branches: feature/, fix/, chore/ prefixes
- Pre-commit must pass before committing
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.
- 10d ago First seen · 60 lines · 635 tokens per session scan A b9004d0fcec6
ai-agents-marketplace AGENTS.md is an instructions file published in the GitHub repository aviz92/ai-agents-marketplace (2 stars, last pushed 1mo ago), licensed MIT. It adds 635 tokens to every session, about $0.0032 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
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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
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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.
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.