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Community Skill Radar

Community
ArchieIndian
community-skill-radar

Searches Reddit communities for OpenClaw pain points and feature requests, scores them by signal strength, and writes a prioritized PROPOSALS.md for you to review and act on.

Overview

PublisherArchieIndian
Repositoryopenclaw-superpowers
Skill namecommunity-skill-radar
Stars
74
Forks
14
Bundled files
3
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 3 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by ArchieIndian on GitHub. Read the source before you install it.

Installation

Install the Community Skill Radar AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/ArchieIndian/openclaw-superpowers/tree/main/skills/openclaw-native/community-skill-radar
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/ArchieIndian/openclaw-superpowers.git /tmp/openclaw-superpowers
mkdir -p .claude/skills
cp -r /tmp/openclaw-superpowers/skills/openclaw-native/community-skill-radar .claude/skills/community-skill-radar
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Community Skill Radar in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Community Skill Radar on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Community Skill Radar is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Community Skill Radar

What it does

Your best skill ideas don't come from guessing — they come from what the community is actually struggling with. Community Skill Radar scans Reddit every 3 days for posts and comments mentioning OpenClaw pain points, feature requests, and skill gaps. It scores them by signal strength (upvotes, comment depth, recurrence) and writes a prioritized PROPOSALS.md in the repo root.

You review the proposals. You decide what to build. The radar just makes sure you never miss a signal.

When to invoke

  • Automatically, every 3 days (cron)
  • Manually when you want a fresh pulse-check on community needs
  • Before planning a new batch of skills

Subreddits searched

SubredditWhy
openclawPrimary OpenClaw community
LocalLLaMALocal AI users — many run OpenClaw
ClaudeAIClaude ecosystem — overlaps with OpenClaw users
MachineLearningBroader AI practitioners
AIAgentsAgent-specific discussions

Custom subreddits can be configured via --subreddits.

Signal scoring

Each candidate is scored on 5 dimensions:

SignalWeightSource
Upvotes2xPost/comment score
Comment depth1.5xNumber of replies — more discussion = stronger signal
Recurrence3xSame pain point appearing across multiple posts
Keyword density1xConcentration of problem/request keywords
Recency1.5xNewer posts score higher (7-day decay)

How to use

bash
python3 radar.py --scan                     # Full scan, write PROPOSALS.md
python3 radar.py --scan --lookback 7        # Scan last 7 days (default: 3)
python3 radar.py --scan --subreddits openclaw,LocalLLaMA
python3 radar.py --scan --min-score 5.0     # Only proposals scoring ≥5.0
python3 radar.py --status                   # Last scan summary from state
python3 radar.py --history                  # Show past scan results
python3 radar.py --format json              # Machine-readable output

Cron wakeup behaviour

Every 3 days at 9am:

  1. Fetch recent posts from each configured subreddit via Reddit's public JSON API (no auth required)
  2. Filter for posts/comments containing OpenClaw-related keywords
  3. Extract pain points and feature request signals
  4. Score each candidate
  5. Deduplicate against previously seen proposals (stored in state)
  6. Write PROPOSALS.md to the repo root
  7. Print summary to stdout

PROPOSALS.md format

markdown
# Skill Proposals — Community Radar

*Last scanned: 2026-03-16 09:00 | 5 subreddits | 14 candidates*

## High Signal (score ≥ 8.0)

### 1. Skill auto-update mechanism (score: 12.4)
- **Source:** r/openclaw — "Anyone else manually pulling skill updates?"
- **Signal:** 47 upvotes, 23 comments, seen 3 times across 2 subreddits
- **Pain point:** No way to update installed skills without manual git pull
- **Potential skill:** `skill-auto-updater` — checks upstream repos for new versions

### 2. Context window usage dashboard (score: 9.1)
- **Source:** r/LocalLLaMA — "My openclaw agent keeps losing context mid-task"
- **Signal:** 31 upvotes, 18 comments
- **Pain point:** No visibility into how much context each skill consumes
- **Potential skill:** `context-usage-dashboard` — real-time token budget display

## Medium Signal (score 4.0–8.0)

...

## Previously Seen (already in state — not re-proposed)

...

Procedure

Step 1 — Let the cron run (or trigger manually)

bash
python3 radar.py --scan

Step 2 — Review PROPOSALS.md

Open PROPOSALS.md in the repo root. High-signal proposals are the ones the community is loudest about.

Step 3 — Act on proposals you want to build

For each proposal you decide to build, either:

  • Ask your agent to create it: "Build a skill for <pain point> using create-skill"
  • Open a GitHub issue for the community

Step 4 — Mark proposals as actioned

bash
python3 radar.py --mark-actioned "skill-auto-updater"

This moves the proposal to the "actioned" list in state so it won't be re-proposed on future scans.

State

Scan results, seen proposals, and actioned items stored in ~/.openclaw/skill-state/community-skill-radar/state.yaml.

Fields: last_scan_at, subreddits, proposals list, actioned list, scan_history.

Notes

  • Uses Reddit's public JSON API at reddit.com/<subreddit>/search.json. No authentication required. Rate-limited to 1 request per 2 seconds to respect Reddit's guidelines.
  • Does not post, comment, or interact with Reddit in any way — read-only scanning.
  • PROPOSALS.md is gitignored by default (local working document). Add to .gitignore if not already present.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Community Skill Radar AI skill do?

Searches Reddit communities for OpenClaw pain points and feature requests, scores them by signal strength, and writes a prioritized PROPOSALS.md for you to review and act on.

Why use Community Skill Radar on TypingMind?

Because you install it once and use it with any model. Community Skill Radar is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Community Skill Radar in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/ArchieIndian/openclaw-superpowers/tree/main/skills/openclaw-native/community-skill-radar. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Community Skill Radar?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Community Skill Radar?

As many as you like. As long as a model supports skills, you can use Community Skill Radar with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Community Skill Radar AI skill free?

It is published on GitHub by ArchieIndian. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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