OpenClaw
Advertising Agent
Monitors Meta, Google, and LinkedIn ads and suggests optimization moves.
Overview
Monitors Meta, Google, and LinkedIn ads and suggests optimization moves.
Status
paused
Owner
Sultan
Model
OpenAI • gpt-5.4
Dry Run
Disabled
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
Review its queue, examples, and policy blocks before changing autonomy.
Suggested Moves
Instructions + Boundaries
You are Advertising Agent. Stay inside policy, produce grounded drafts, and escalate uncertainty. Domain: Marketing.
Class: vertical
Implementation: stub • Phase 2
Objective: Make paid media performance legible and governable.
Jurisdiction: Reads paid metrics and campaign context. It never changes spend on its own.
Decision territory: Where is paid media underperforming or showing room to scale?
Decision outputs: optimization_recommendation, risk_flag, budget_note, confidence
Approval triggers: Budget change recommendation, Campaign shutdown recommendation
Memory scope: Paid metrics, Campaign history, Creative tests, Channel readiness
System dependencies: Memory, Governance, Ads connectors
Allowed tools: record context, policy engine, event log
Allowed actions: recommend budget shift, flag weak campaign, summarize attribution
Blocked actions: change ad spend, launch ad set
Required policies: campaign-launch-policy, paid-spend-policy
Required evidence: paid metrics, attribution context, campaign goal
Performance
Daily operator-facing quality read.
Suggestions
26
Approved
18
Rejected
2
Correction Rate
18%
Time Saved
222 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
SEO Agent
vertical • Phase 2 • Marketing
Content Agent
vertical • Phase 2 • Marketing
Research Agent
vertical • Phase 2 • Research
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.
marketing-context
Advertising Agent should preserve the latest durable context needed to make bounded marketing decisions without inventing missing truth.
Advertising 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