PraisonAI is a framework and SDK for building AI agents and teams that research, generate code or content, analyze data, support users, and automate workflows. Developers use it to create autonomous task-running agents with memory, retrieval-augmented generation, and support for many language models.
Borrowing it
Nothing to install: this file belongs to MervinPraison/PraisonAI. 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/MervinPraison/PraisonAI/main/AGENTS.mdgit clone --depth 1 https://github.com/MervinPraison/PraisonAIWrote 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/mervinpraison/praisonai/agents-md)<a href="https://agentmods.dev/instructions/mervinpraison/praisonai/agents-md"><img src="https://agentmods.dev/badge/instructions/mervinpraison/praisonai/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 | $0.01055 | $0.01055 |
| Opus 5 | $0.00528 | $0.00528 |
| Sonnet 5 | $0.00211 | $0.00211 |
| Haiku 4.5 | $0.00105 | $0.00105 |
Grade A, and why
PraisonAI 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 — 28 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Instructions
You are working on the PraisonAI project.
Project Guidelines
- Follow the existing code style and conventions
- Be concise and helpful in responses
- Test implementation thoroughly
- Ensure backward compatibility with existing APIs
- Follow protocol-driven design across the nine Python PyPI packages plus the TypeScript SDK: core protocols in
praisonaiagents/, agentic terminal CLI inpraisonai-code/, bots/gateway inpraisonai-bot/, LLM fine-tuning + agent training inpraisonai-train/, browser automation inpraisonai-browser/, MCP server host inpraisonai-mcp/, sandbox backends inpraisonai-sandbox/, deployment inpraisonai-deploy/, integrations/serve/dashboard in thepraisonai/wrapper, TypeScript/JavaScript SDK insrc/praisonai-ts/(npm: praisonai) - TypeScript review routing: For TS/JS issues and PRs, read
src/praisonai-ts/AGENTS.md(not just this file). Canonical source issrc/praisonai-ts/in this monorepo; MervinPraison/praisonai-js is the npm mirror only (sync: monorepo → praisonai-js via workflow Sync to praisonai-js). Do not implement TS fixes in praisonai-js for PraisonAI issues. - Preserve old
praisonai.*import paths via shims when moving code between packages (see §2.3 insrc/praisonai-agents/AGENTS.md; shim helpers insrc/praisonai/praisonai/cli/_shim.py) - Package boundaries and dependency rules:
ARCHITECTURE.md§2 (Tier 2 packages must never PyPI-depend on the wrapper; cross-tier access goes through lazy_*_bridgemodules) - Boundary manifests:
src/praisonai/tests/PRAISONAI_BOT_MANIFEST.md(C9),src/praisonai/tests/PRAISONAI_TRAIN_MANIFEST.md(C10),src/praisonai/tests/PRAISONAI_BROWSER_MANIFEST.md(C11),src/praisonai/tests/PRAISONAI_MCP_MANIFEST.md(C12),src/praisonai/tests/PRAISONAI_SANDBOX_MANIFEST.md(C13),src/praisonai/tests/PRAISONAI_DEPLOY_MANIFEST.md(C14) - When reviewing a PR or an issue, evaluate whether the change addresses a framework concern or a user goal, and design its surface (params, naming, defaults) accordingly
- The aim of this package is to stay lightweight and powerful. Do a critical review at each stage — when triaging an issue, when planning a fix, and when reviewing/implementing a PR. Reject scope creep for the sake of adding features: if a capability already exists (e.g. via existing Agent params like
instructions/backstory/tools/hooks/memory), prefer it over a new API surface. A change must genuinely strengthen the SDK (simpler, more robust, more user-friendly) — do not add knobs, params, modules, or exports that have no live consumer or that merely duplicate existing behaviour.
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 · 28 lines · 1,055 tokens per session scan A 40fcd10c22fc
PraisonAI AGENTS.md is an instructions file published in the GitHub repository MervinPraison/PraisonAI (9,028 stars, last pushed yesterday), licensed MIT. It adds 1,055 tokens to every session, about $0.0053 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 2026-08-30.
Other instructions, from other repositories
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).
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.
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 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).
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.