web-researcher

---

name: web-researcher description: > Web research with OMC team parallel execution. Triggers on "웹에서 찾아", "최신 정보", "리서치해", "동향", "web research", "find online", "latest info", "look up", "search the web", "trend analysis" and similar. v3: Spawns research-agent in parallel for multi-angle search. Deduplicates via memory_similar. Builds knowledge graph connections. For comprehensive research use /deep-research instead.

Web Researcher — Automated Web Research & Knowledge Integration

Preamble

Before executing this skill:

1. Load context from memory:

   memory_search(query: "{skill-relevant-query}", associative: true, limit: 5)
   memory_search(tag: "{skill-name}", limit: 3)
   

   Review returned memories for relevant past context, decisions, and patterns.

2. Check OMC state for active work:

   state_get_status()
   

   If conflicting active tasks exist, warn the user before proceeding.

3. Detect current branch (for git-related skills):

   git rev-parse --abbrev-ref HEAD 2>/dev/null || echo "not-a-git-repo"
   

4. Check proactive mode:

   state_read("occ-proactive")
   

   If "false": do NOT proactively suggest other OpenClaw-CC skills during this session. Only run skills the user explicitly invokes.

5. Log skill activation:

   memory_daily_log(type: "note", entry: "Skill activated: /{skill-name}")
   

Role

Perform systematic web research using multiple queries and angles. Collect, verify, structure, and persist findings in memory. Link new knowledge to existing related memories for a connected knowledge graph.

Workflow

Step 1 — Check Existing Knowledge

Memory Context Loading

Before starting work, load relevant context from the 3-layer memory system:

# Search for related past work
memory_search(query: "{task description}", associative: true, limit: 5)

# Search by relevant tags
memory_search(tag: "{relevant-tag}", limit: 3)

# Check for recent related daily logs
memory_search_date(start: "{7 days ago}", end: "{today}", category: "daily-logs", limit: 5)