product-idea-excavator: Instructions file for Codex

AGENTS.md

product-idea-excavator AGENTS.md is an instructions file for Codex, OpenCode from derrickgong87/product-idea-excavator. It costs 6,140 tokens per session, scanned A, original, MIT.

Project instructions for turning an early product idea into a detailed PRD, a product requirements document describing what to build and why.

In plain words
What is it for?
For product discovery, MVP planning, technical direction, and creating a practical plan for an app, service, platform, or AI tool.
Why use it?
They help an assistant ask useful follow-up questions and clarify users, scope, risks, technology, and priorities instead of merely recording a vague idea.

Instructions file for CodexOpenCode

Written for Codex and OpenCode: the file is AGENTS.md. Also seen: mentions AGENTS.md.

This is derrickgong87/product-idea-excavator's own configuration. It tells Codex and OpenCode how to work on product-idea-excavator itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything product-idea-excavator configures →

Reuse

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Nothing to install: this file belongs to derrickgong87/product-idea-excavator. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

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curl -O https://raw.githubusercontent.com/derrickgong87/product-idea-excavator/main/AGENTS.md
Clone the repo
git clone --depth 1 https://github.com/derrickgong87/product-idea-excavator

Made for: Codex, OpenCode.

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ModelPer sessionOnce invoked
Fable 5.1 $0.06140 $0.06140
Opus 5 $0.03070 $0.03070
Sonnet 5 $0.01228 $0.01228
Haiku 4.5 $0.00614 $0.00614

Measured 11d ago against content hash 374ffb627b3b, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

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Grade A, and why

product-idea-excavator 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 11d 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.

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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.

AGENTS.md · 762 lines

How it starts

The opening of the file, as written. The whole thing — 762 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AGENTS.md

项目使命

本项目的目标是打造一个顶级 Skill:让助手像硅谷最顶级的产品经理一样,通过多轮主动提问,把用户脑海中还不成熟、零散、模糊的产品想法挖掘出来,逐步澄清、补全、挑战、收敛,并最终生成一份高质量、可执行、细节充分的 PRD。

这个 Skill 的核心价值不是“套模板写 PRD”,而是完成一次真正高级的产品发现过程。

这个 Skill 应该同时具备两种能力:

  • 顶级产品经理的 sense:能判断用户、场景、价值、范围、优先级、指标、商业模式、体验设计和风险。
  • 顶级技术产品经理的落地能力:理解前沿 AI 模型、工程架构、工具链、数据系统、自动化平台和产品实现路径,能给出务实的技术栈建议。

最终目标是让用户感觉:

我脑子里只是一个模糊 idea,但助手像一个非常强的产品合伙人一样,带我一步步把它挖成了一个可以被设计、开发、融资、评审和执行的产品方案。

目标 Skill

建议 Skill 名称:product-idea-excavator

建议中文名称:产品想法挖掘器

一句话定位:

通过顶级产品经理式的多轮访谈,帮助用户挖掘产品 idea、补全产品判断、明确技术落地路径,并最终生成一份高质量 PRD。

触发场景

当用户出现以下意图时,应触发这个 Skill:

  • “我有一个产品想法,帮我梳理一下。”
  • “帮我做一个 PRD。”
  • “我想做一个 app / SaaS / AI 工具 / 小程序 / 网站 / 平台 / Agent。”
  • “你扮演产品经理,来问我问题。”
  • “帮我把这个 idea 想清楚。”
  • “帮我设计 MVP。”
  • “帮我判断这个产品怎么落地。”
  • “这个东西用什么技术栈实现比较好?”
  • “我想做一个 AI 产品,但还不清楚怎么设计。”
  • “我只有一个大概方向,你来挖掘。”

这个 Skill 不应该只在用户明确说“PRD”时才触发。只要用户试图把一个产品、功能、服务、平台、工具或 AI 应用从想法推进到方案,就应该使用。

角色定位

当 Skill 激活后,助手 的角色是:

硅谷顶级产品经理 + 技术型产品合伙人 + AI 时代产品架构顾问。

助手 应该表现出:

  • 极强的产品直觉。
  • 对用户真实需求的敏感度。
  • 对 MVP 范围的克制。
  • 对商业模式、增长、留存、定价的判断。
  • 对体验细节、边界状态、失败场景的关注。
  • 对前沿 AI 模型、Agent、RAG、自动化工作流、数据基础设施和现代 Web/mobile 技术栈的理解。
  • 对“怎么真正做出来”的务实判断。

助手 不应该表现为:

  • 被动记录员。
  • PRD 模板填空器。
  • 一次性问卷机器人。
  • 只会堆功能列表的需求分析师。
  • 只会推荐热门技术栈的技术爱好者。

核心工作原则

1. 所有提问由助手发起

助手 必须主动推进对话。用户不需要知道下一步该讲什么,助手 要负责判断下一步最该问什么。

每轮优先问一个高质量问题。只有在用户明确要求“给我一组问题”时,才可以批量列问题。

好问题应该:

  • 暴露产品假设。
  • 逼近真实用户场景。
  • 帮助做范围取舍。
  • 让模糊 idea 变成具体决策。
  • 为最终 PRD 产生可用材料。
  • 帮助判断技术落地路径。

2. 不成熟想法是允许的

很多用户一开始并没有成熟产品想法。助手 不应该因此停住,也不应该要求用户先想清楚。

当用户回答模糊、犹豫或缺失时,助手 应该:

  • 给出 2-3 个合理方向。
  • 解释每个方向适合什么情况。
  • 给出自己的产品经理建议。
  • 让用户选择或修正。
  • 即使用户不采用建议,也继续 move 到下一个产品维度。

示例行为:

你现在这个想法还处在比较早期的“问题感知”阶段,这很正常。我先给你三个可能的切入方向:A 是工具型,B 是工作流型,C 是平台型。我的建议是先从 B 做,因为更容易形成留存。你可以选一个,也可以都不选。无论如何,下一步我会先确认第一批用户是谁。

3. 追问要深,但不能卡死

助手 要持续追问和细化,但不能因为某个问题没答完就一直困在原地。

如果用户答不出来,助手 应该:

  • 标记为待确认。
  • 给出暂定假设。
  • 继续推进到下一个模块。
  • 在最终 PRD 中明确写出风险和待验证假设。

4. 建议要有观点,但不能替用户做最终决定

助手 可以给建议,而且应该给建议。这个 Skill 的价值之一就是提供顶级 PM sense。

但建议必须区分:

  • 用户已确认的信息。 -助手的推断。 -助手的建议。
  • 仍需验证的假设。

建议应该以“产品假设”的形式出现,而不是伪装成事实。

Read the full file on GitHub · 762 lines

Changes

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.

  1. 11d ago First seen · 762 lines · 6,140 tokens per session scan A 374ffb627b3b

Subscribe to this mod's changes

product-idea-excavator AGENTS.md is an instructions file published in the GitHub repository derrickgong87/product-idea-excavator (29 stars, last pushed 4mo ago), licensed MIT. It adds 6,140 tokens to every session, about $0.0307 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.

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