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Guide for using Reddit MCP to gather community sentiment, pain points, and adoption trends. Load this skill when a DAG contains research tasks about market validation, developer experience, or community opinions.
默认使用会先检查来源的 Prompt；你也可以切换为直接命令，或下载本地副本。
决定是否安装前，请先阅读 SKILL.md，以及 SkillsMP 当前展示的配套文件。
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt；运行前请先检查来源。
npx skills add https://github.com/blueif16/amazing-claude-code-plugins --skill market-recon命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地？可下载 SkillsMP 当前能够提供的文件。
正在显示 SKILL.md
基于 SOC 职业分类
Start, check, or continue any work. Analyzes intent, plans tasks, and orchestrates execution via subagents (L2) or Agent Teams (L3).
Generate Playwright test scripts for browser-based acceptance verification. Load when DAG tasks touch UI, routes, or user-facing API responses.
Classify intent, assess complexity, generate task DAGs. Activates on /go or when user describes work.
| name | market-recon |
| description | Guide for using Reddit MCP to gather community sentiment, pain points, and adoption trends. Load this skill when a DAG contains research tasks about market validation, developer experience, or community opinions. |
This skill is for the main thread / orchestrator only. Subagents cannot call MCP tools directly. You fetch the data, write it to disk, and pass the file path to the subagent.
DAG contains tasks with type=research AND signals like: community, sentiment, pain points, adoption, market, trends, opinions, practitioners, experience.
Pick 2-3 subreddits matching the topic:
ClaudeAI, ChatGPTCoding, cursorprogramming, webdev, ExperiencedDevsdevops, sysadmin, kubernetesreactjs, nextjs, webdevSearch with short, specific queries (2-4 words). Run 2-3 queries per subreddit to cover angles: the tool name, the pain point, the alternative.
Skim results for signal: recurring complaints, praise patterns, specific user stories. Ignore hype posts with no substance.
Write results to .godag/context/{task_id}-market.md:
# Market Recon: {topic}
## Sources
- r/{sub1}: {N} relevant posts searched
- r/{sub2}: {N} relevant posts searched
## Key Pain Points
1. {pain point} — {1-2 sentence evidence with post reference}
2. ...
## Positive Signals
1. {signal} — {evidence}
## Sentiment: {positive|negative|mixed|shifting}
## Gaps / Unmet Needs
- {gap}
Keep the file under 2000 tokens. The subagent needs a concise briefing, not a data dump.
In the spawn prompt, add:
Read .godag/context/{task_id}-market.md for community research data.
Analyze and synthesize — don't just summarize what's in the file.