Borrowing it
Nothing to install: this file belongs to iflow-ai/NioPD. 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/iflow-ai/NioPD/master/AGENTS.mdgit clone --depth 1 https://github.com/iflow-ai/NioPDWrote 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/iflow-ai/niopd/agents-md)<a href="https://agentmods.dev/instructions/iflow-ai/niopd/agents-md"><img src="https://agentmods.dev/badge/instructions/iflow-ai/niopd/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/iflow-ai/niopd/agents-md"><img src="https://agentmods.dev/badge/instructions/iflow-ai/niopd/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 | $0.01443 | $0.01443 |
| Opus 5.5 | $0.00577 | $0.00577 |
| Sonnet 5.5 | $0.00289 | $0.00289 |
| Haiku 4.5 | $0.00144 | $0.00144 |
Grade A, and why
NioPD 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 2mo 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 for the NioPD System
This document provides guidance for AI agents working with the NioPD system.
1. System Overview
NioPD is an AI-powered assistant system for Product Managers. It is designed to automate and assist with the core PM workflow, from defining high-level initiatives to tracking success metrics.
The system is file-based and command-driven. All data is stored in markdown files within the niopd-workspace/ directory, and the AI's behavior is guided by a series of command prompts and agent definitions.
2. Core Philosophy: Agent-Driven Synthesis
NioPD relies on specialized agents to perform complex synthesis tasks. Unlike a general-purpose chatbot, NioPD uses agents to transform one type of document into another (e.g., turning feedback into a PRD, or turning initiatives into a roadmap).
Your primary role as an agent is to follow the instructions defined in the commands/niopd/ and agents/niopd/ directories to execute these transformations accurately.
3. Available Agents
🤖 competitor-analyzer
- Purpose: To analyze a competitor's website and produce a structured summary of their product, pricing, and positioning.
- Input: A single URL for a competitor's homepage.
- Output: A structured markdown competitor analysis report with core value proposition, features, target audience, and pricing model.
🤖 data-analyst
- Purpose: To analyze structured data from a file (like CSV) and answer natural language questions about that data.
- Input: A file containing structured data and a natural language query.
- Output: A markdown data analysis report with direct answers and supporting methodology.
🤖 feedback-synthesizer
- Purpose: To process raw user feedback and identify key themes, pain points, and feature requests.
- Input: A file containing user feedback.
- Output: A structured markdown summary of the feedback with themes, pain points, and user quotes.
🤖 interview-summarizer
- Purpose: To read user interview transcripts and extract critical insights, including user needs, pain points, and direct quotes.
- Input: A text file containing the full transcript of a user interview.
- Output: A markdown interview summary with key takeaways, core themes, and verbatim quotes.
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.
- 2mo ago First seen · 100 lines · 1,443 tokens per session scan A 5be062e55027
NioPD AGENTS.md is an instructions file published in the GitHub repository iflow-ai/NioPD (119 stars, last pushed 10mo ago), licensed MIT. It adds 1,443 tokens to every session, about $0.0058 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.
NioPD AGENTS.md compared with instructions from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| NioPD AGENTS.mdiflow-ai/NioPD | Instructions file | 119 | 10mo ago | MIT | A | 1,443 | 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 |