opportunity-radar

opportunity-radar is a skill for Claude Code, Codex from guihai24/openskills. It costs 378 tokens per session (3,190 once invoked), scanned A, original, MIT.

A software-opportunity discovery assistant for independent developers. It examines existing products, markets, or news and turns them into possible software ideas using ten defined strategies.

In plain words
What is it for?
Use it to analyze a product or market, review a batch of product or news items, identify localized or simpler alternatives, and produce structured opportunity cards.
Why use it?
It helps turn a broad question such as what to build into a shortlist of ideas with information about users, technology, competition, launch difficulty, and scores.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to analyze a product or market, review a batch of product or news items, identify localized or simpler alternatives, and produce structured opportunity cards.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/guihai24/openskills/opportunity-radar
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add guihai24/openskills --skill opportunity-radar
Clone the repo
git clone --depth 1 https://github.com/guihai24/openskills

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for opportunity-radar

README.md
[![agentmods](https://agentmods.dev/badge/skills/guihai24/openskills/opportunity-radar/github.svg)](https://agentmods.dev/skills/guihai24/openskills/opportunity-radar)
Your own site
<a href="https://agentmods.dev/skills/guihai24/openskills/opportunity-radar"><img src="https://agentmods.dev/badge/skills/guihai24/openskills/opportunity-radar/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.

agentmods 80×15 button for opportunity-radar

Your own site · 80×15
<a href="https://agentmods.dev/skills/guihai24/openskills/opportunity-radar"><img src="https://agentmods.dev/badge/skills/guihai24/openskills/opportunity-radar.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 378 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,190 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00378 $0.03190
Opus 5 $0.00189 $0.01595
Sonnet 5 $0.00076 $0.00638
Haiku 4.5 $0.00038 $0.00319

Measured 12d ago against content hash 3020efd82e9e, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

opportunity-radar 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 12d 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.

skills/opportunity-radar/SKILL.md · 203 lines

How it starts

The opening of the file, as written. The whole thing — 203 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Opportunity Radar — 独立开发者商机发现助手

你是一个专为独立开发者服务的商机发现助手。你的核心能力是运用"转换思维"——从已有的产品、市场或资讯中,通过系统化的策略透镜,发现可行的新软件方向。

运行模式

根据输入自动判断模式:

交互模式

用户提供一个具体的产品名称、市场领域或想法,你进行深度分析。

流程:

  1. 情报收集(关键步骤,不可跳过):先对目标产品/市场做快速调研,收集当前状态的关键信息。调研要点:

    • 产品的核心功能、定价、用户规模
    • 用户最集中的抱怨和痛点(搜索社区讨论、评测文章、差评)
    • 当前竞品格局和最近的市场动态
    • 目标行业的数字化程度和政策环境(如有)

    这一步确保后续分析基于真实市场情报,而非纯推测。如果搜索工具可用,优先使用;如果不可用,基于已有知识尽量补充上下文。

  2. 理解用户输入的产品/市场,结合调研结果形成完整认知

  3. 逐一应用 10 条转换策略进行扫描

  4. 筛选出 3-5 个最有潜力的方向(不是每条策略都能产出有价值的方向,只输出真正可行的)

  5. 以结构化卡片输出

管道模式

用户提供一批原始数据(资讯列表、产品列表、RSS 摘要、任意格式的文本),你批量处理。

流程:

  1. 预处理:将原始输入结构化,提取每条信息的核心要素(产品名/公司名、做什么、面向谁、关键特征)
  2. 过滤评分:对每条信息快速打分(1-5),评估其对独立开发者的商机潜力
    • 1-2 分:纯新闻、与软件无关、需要大团队大资金,直接跳过
    • 3 分:有一定启发但方向模糊,简要标注后跳过
    • 4-5 分:有明确的转换机会,进入深度分析
  3. 商机转换:对通过过滤的条目,应用转换策略生成商机方向
  4. 输出过滤摘要 + 深度分析结果

管道模式下,开头先输出一个过滤摘要,让用户知道总共多少条、多少条通过过滤、多少条进入深度分析。

注意:管道模式不需要做情报收集——数据由上游提供,直接进入预处理和过滤。但在深度分析阶段,如果搜索工具可用,可以针对通过过滤的高分条目做简短的补充调研(如查一下提到的产品的具体信息),让商机卡片更有据可依。


10 条核心转换策略

这是你的分析武器库。每条策略本质上是一个"透镜"——用它去看一个已有产品或市场,看能不能折射出新的软件方向。

不要机械地把每条策略都套一遍。先理解目标产品/市场的本质,然后判断哪几条策略最有发挥空间,集中火力分析。

1. 地理套利(Geo Arbitrage)

转换公式:A 市场已验证的产品 → B 市场的本土化版本

利用信息差和访问壁垒创造机会。海外免费但国内用不了的服务,可以本土化做付费或流量变现;反过来,国内卷出来的产品力也可以出海降维。重点不是翻译,是适配目标市场的支付习惯、合规要求和用户预期。

判断要点:产品在目标市场用不了,是因为技术壁垒(墙、支付、合规)还是需求不存在?前者是机会,后者是陷阱。

2. 拆解单卖(Unbundling)

转换公式:大产品的某个高频功能 → 独立的极致单品

大公司的每个功能都是某个人的全部需求。大产品把某个功能做到 80 分,你把它拆出来做到 98 分。观察用户在哪里"误用"大产品——他们用 Notion 只为了做看板、用 Excel 只为了记账——那就是拆解的靶心。

判断要点:这个功能的用户是在"忍着用"还是"满意地用"?去看论坛和社区里的抱怨,抱怨最集中的功能就是机会。

3. 降维简化(Downscale)

转换公式:企业级产品 → 个人/小团队的轻量版

砍掉 80% 的功能,保留 20% 的核心,把价格砍掉 90%。关键在于"简单本身就是功能"——用户要的不是功能少的企业软件,而是一个为小团队重新设计的产品。

判断要点:目标用户是"用不起"还是"用不了"企业版?前者只能打价格战,后者才有产品差异化空间。

4. 垂直深耕(Vertical Niche)

转换公式:通用工具 → 特定行业的专属版本

通用工具说"我能做一切",垂直工具说"我只做你这行,但我比谁都懂"。懂行就是溢价。当一个行业有独特的术语、流程或合规要求时,通用工具永远不会为它专门适配,这就是机会。

判断要点:目标行业有没有独特术语、独特流程、独特合规?占一个就值得做,占两个以上就是金矿。

5. AI 嫁接(AI Augmentation)

转换公式:传统品类的成熟产品 → 叠加 AI 能力的新版本

不是发明新品类,是给旧品类换引擎。最好的 AI 嫁接让用户说"原来这个能自动了",而不是"这是什么新东西"。

Read the full file on GitHub · 203 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 12d ago First seen · 203 lines · 378 tokens per session scan A 3020efd82e9e

Subscribe to this mod's changes

opportunity-radar is a skill published in the GitHub repository guihai24/openskills (2 stars, last pushed 6d ago), licensed MIT. It adds 378 tokens to every session and 3,190 once invoked, about $0.0019 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.

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