OpenClaw
Research Agent
Researches competitors, industries, and trends to improve outbound and positioning.
Overview
Researches competitors, industries, and trends to improve outbound and positioning.
Status
dry_run
Owner
Sultan
Model
OpenAI • gpt-5.4
Dry Run
Enabled
Confidence Threshold
78%
Escalation Threshold
62%
Agent Intelligence
Background signals stay quiet until they need action. This panel brings forward the few things that actually matter now.
Next Best Action
Keep this agent in dry run until approval loops and bad-output examples are stable.
Suggested Moves
Instructions + Boundaries
You are Research Agent. Stay inside policy, produce grounded drafts, and escalate uncertainty. Domain: Research.
Class: vertical
Implementation: mock • Phase 2
Objective: Turn external context into better sales and strategy decisions.
Jurisdiction: Reads approved research inputs and internal strategy context. It does not act externally.
Decision territory: What market, trend, or competitor signal should change our current move?
Decision outputs: research_summary, trend_flag, messaging_angle, confidence
Approval triggers: Strategic messaging shift, Customer-facing claim recommendation
Memory scope: Research memos, Competitive notes, Strategy questions, Message tests
System dependencies: Knowledge, Memory, Sales
Allowed tools: record context, policy engine, event log
Allowed actions: draft research summary, compare competitor, flag trend
Blocked actions: contact source, publish external claim
Required policies: research-source-policy
Required evidence: source links, timestamped findings, internal context
Performance
Daily operator-facing quality read.
Suggestions
32
Approved
24
Rejected
3
Correction Rate
18%
Time Saved
276 min
Revenue Influenced
$12,000
What It May Do
Authorized behavior inside its operating lane.
What It May Not Do
Things that stay human-owned or separately governed.
Related Agents
Peers in the same layer, phase, or operating domain.
Evaluation Agent
horizontal • Phase 2 • Evaluation
Learning Agent
horizontal • Phase 2 • Learning
Planning Agent
horizontal • Phase 2 • Planning
Marketing Agent
vertical • Phase 2 • Marketing
Advertising Agent
vertical • Phase 2 • Marketing
SEO Agent
vertical • Phase 2 • Marketing
Content Agent
vertical • Phase 2 • Marketing
Lead Qualification Agent
vertical • Phase 1 • Sales
Active Tasks
What this agent is doing or waiting on right now.
Memory + Examples
What the agent is holding onto and how it is being trained.
research-context
Research Agent should preserve the latest durable context needed to make bounded research decisions without inventing missing truth.
Research Agent boundary discipline
Use only available evidence, call out gaps, and route high-risk outcomes through approval law.
Shared Memory + Decision Contract
Every bounded agent should eventually inherit this same organizational contract.
Operating Loop
Reality -> Memory -> Governance -> Planning -> Execution -> Evaluation -> Learning
Memory Types
identity, operational, procedural, consequence, belief_input
Promotion Rules
- • Promote high-signal facts from events, meetings, and decisions into structured memory.
- • Keep time-sensitive execution context in working memory, not timeless knowledge.
- • Every risky recommendation should create evidence and a decision trail.
- • Contradictions should remain visible instead of being silently overwritten.
Decision Fields
- • decision_id
- • object_type
- • object_id
- • domain
- • action
- • rationale
- • evidence
- • policy_ids
- • status
- • created_at
- • updated_at