0xAxiom

Social Intel Hub

Edit `config/skills-inventory.json` when you ship new tools. The context matcher uses this to identify threads where your tools are directly relevant.

0xAxiom 16 2 Updated 3mo ago

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Install

npx skillscat add 0xaxiom/axiom-public/agent-tools-skills-social-intel-hub

Install via the SkillsCat registry.

SKILL.md

Social Intel Hub

Find and score engagement opportunities across the web. Surfaces conversations where showing your work is genuinely helpful, not spammy.

How It Works

  1. Search — Query keywords from config/keywords.json via web_search tool (Brave)
  2. Score — Run results through src/scanner.mjs scoring engine (relevance, freshness, authority, context fit)
  3. Suggest — Generate response guidelines via src/responder.mjs matched to your skills inventory
  4. Review — Send top opportunities to Telegram for human approval

Running a Scan (Agent Cron)

The scan runs as an OpenClaw cron job with agentTurn. The agent:

Step 1: Search keywords

Load keywords from config/keywords.json. For each keyword, use web_search with freshness: "pw" (past week).

web_search({ query: keyword.term, count: 5, freshness: "pw" })

Rotate through 3-4 keywords per scan (not all 8). Track which were searched last in a state file.

Step 2: Format results as JSON

Structure results as:

[
  {
    "keyword": "AI agent tools",
    "results": [
      {"title": "...", "url": "...", "description": "...", "domain": "...", "published": "..."}
    ]
  }
]

Step 3: Score

Pipe JSON into the scanner:

echo '$JSON' | node ~/Github/axiom-public/agent-tools/skills/social-intel-hub/src/scanner.mjs 4 10

Step 4: Report

Send results to Telegram. Only report opportunities scoring 5+.

If no opportunities found, reply with just a summary line. Don't spam with empty results.

Scoring Breakdown (0-10 scale)

Factor Range What it measures
Relevance 0-3 DeFi, agents, onchain, automation keywords
Freshness 0-2 Last 24h = 2, last week = 1, older = 0
Authority 0-2 Domain reputation (GitHub/dev.to = high)
Context Fit 0-3 Match against skills inventory

Final score = raw × keyword weight. Keywords like "LP management bot" have 1.5x weight.

Files

  • config/keywords.json — Search terms, weights, exclusions
  • config/skills-inventory.json — Your tools/skills for context matching
  • src/scorer.mjs — Scoring engine
  • src/scanner.mjs — Result processor (stdin JSON → ranked output)
  • src/responder.mjs — Response suggestion generator
  • scripts/scan.sh — CLI wrapper (--demo for test run)

Engagement Rules

These are baked into the responder but worth repeating:

  1. Lead with value, not links. Solve their problem first.
  2. Show your work. Link to actual code, not landing pages.
  3. Read the room. Don't reply to 3-day-old threads.
  4. One reply per thread. Never double-tap.
  5. Skip if someone already answered well. Don't pile on.

Adding Keywords

Edit config/keywords.json:

{"term": "new keyword", "category": "defi", "weight": 1.5}

Higher weight = opportunities with this keyword rank higher.

Adding Skills to Inventory

Edit config/skills-inventory.json when you ship new tools. The context matcher uses this to identify threads where your tools are directly relevant.