From godag
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.
npx claudepluginhub blueif16/amazing-claude-code-plugins --plugin godagThis skill uses the workspace's default tool permissions.
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.
Creates isolated Git worktrees for feature branches with prioritized directory selection, gitignore safety checks, auto project setup for Node/Python/Rust/Go, and baseline verification.
Executes implementation plans in current session by dispatching fresh subagents per independent task, with two-stage reviews: spec compliance then code quality.
Dispatches parallel agents to independently tackle 2+ tasks like separate test failures or subsystems without shared state or dependencies.
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.