ChenneyZhuang/competitor-recon ↗★ 0
competitor-recon
Complaint-driven competitor research: enumerate competitors, extract features/pricing/positioning plus cited user complaints from reviews, forums, and issue trackers, cluster the complaints, and deliver a comparison table with copy-worthy and skip lists. 适合需求调研与竞品选型；需要可访问多源评论与问题反馈并保留来源。
Install
npx -p @deepseek-ai/dsh dsh plugin --profile web add github:ChenneyZhuang/competitor-reconREADME
Read the full README ↗competitor-recon 竞品调研
Run competitor reconnaissance before building any feature: the review sections of existing products are the cheapest requirements research that exists.
动手做功能之前先跑竞品侦察：现有产品的用户评论区，是世界上最便宜的需求调研。
Why / 为什么
Marketing pages state intentions; user reviews state outcomes. One grounded complaint is worth more than any amount of feature-page copy — and a complaint repeated by three independent users is an unmet need you can build against.
营销页写的是意图，用户评论写的是结果。一条有出处的真实抱怨，胜过整页功能文案；三个互不相识的用户抱怨同一件事，就是一个可以动手满足的未满足需求。
The method / 方法（4 步）
- Enumerate 3–6 competitors — search English and Chinese sources; one language samples half the market.
- Extract per competitor: features, pricing (numbers, not "contact us"), positioning, and user complaints with source links.
- Cluster complaints by the underlying need, ranked by frequency.
- Deliver: comparison table + copy-worthy list + skip list. A feature idea enters the build list only with a cited user complaint behind it.
Worked example — recon on an open-source ledger app (2026-09, real run)
Sources actually fetched during the run: V2EX threads (via curl), the target's GitHub issue tracker (via API — reaction counts double as frequency statistics), community forums.
| Complaint cluster | Evidence | Verdict |
|---|---|---|
| Ads / subscription inflation driving users out | multiple independent forum posts naming the incumbents | differentiate: stay clean, price predictably |
| "AI auto-capture might be wrong, I re-check manually" | feature request with 👍×3 in the target's own tracker | build: recognition → confirmation loop |
| Reimbursement / refund flows too complex | complaints across two products, praise for a third's | build: expense-return workflow done simply |
| Multi-currency locked behind a paywall | a long-time user defected over exactly this | skip: no demand evidence beyond the wall itself |
The run produced the full comparison table plus a skip list with reasons — 3 build ideas, each cited; 3 skips, each justified.
Rules that make it work / 让它生效的规则
- Reviews outrank marketing pages; conflicts are recorded as claims.
- Complaint clusters are the finding — one is anecdote, three is a need.
- Issue trackers are goldmines: a 👍 count is a frequency statistic for free.
- Tool blocked? Switch clients, not sources (curl, public APIs). The evidence bar never drops.
Install / 安装
git clone https://github.com/ChenneyZhuang/competitor-recon ~/.claude/skills/competitor-recon
One SKILL.md. Needs only web search and any fetch client. MIT. v0.2.0 — live-tested end-to-end.
单个 SKILL.md，只需搜索与抓取能力。MIT 许可，v0.2.0，完整实测通过。