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lanbow-ads

Lanbow Ads control skill for ad campaign management and optimization across Meta (Facebook/Instagram), Google Ads, TikTok Ads, YouTube Ads, Amazon Ads, Shopify Ads, and DSP/programmatic.

danyangliu-sandwichlab0 source installs☆ 0 Repository stars

Installation

Follow the repository instructions for this skill and your agent. Review the files and dependencies before adding it to your workflow.

SkillHub CLI

skillhub install danyangliu-sandwichlab/lanbow-ads

Inspect the source and compatibility requirements, then follow its installation steps.

Give your agent the source link and ask it to inspect instructions and dependencies before explaining the installation steps.

View source ↗Guides

Skill instructions

Lanbow Ads

Purpose

Core mission:

  • Serve as Lanbow's dedicated ad operations and optimization interface.
  • Manage planning, launch, monitoring, and scaling across ad channels.
  • Standardize decision policies for bidding, budget, and performance recovery.
  • Output clear operator actions for media teams.

When To Trigger

Use this skill when the user asks for:

  • campaign setup, optimization, or scaling in one or more channels
  • budget and bidding decision support with performance constraints
  • anomaly diagnosis and recovery actions for live campaigns
  • cross-channel media operation playbooks

High-signal keywords:

  • lanbow ads, run ads, campaign, media buyer
  • bidding, budget, allocation, optimize, scale
  • cpa, roas, performance, monitor, abtest

Input Contract

Required:

  • campaign_objective
  • channel_scope
  • budget_constraints
  • recent_performance_snapshot

Optional:

  • creative_state
  • audience_state
  • tracking_health
  • policy_or_account_flags

Output Contract

  1. Campaign Action Plan
  2. Bidding and Budget Policy
  3. AB Test and Scale Model
  4. Monitoring and Alert Plan
  5. Operator Handoff Checklist

Workflow

  1. Normalize objective and KPI constraints.
  2. Evaluate channel readiness and structure quality.
  3. Produce bid and allocation actions.
  4. Attach testing and scaling rules.
  5. Return monitoring triggers and operator checklist.

Decision Rules

  • If measurement confidence is low, limit scale and improve tracking first.
  • If ROAS is stable above threshold, allow staged budget increases.
  • If CPA is unstable, reduce concurrency of experiments.
  • If anomaly risk is high, prefer containment actions first.

Platform Notes

Primary scope:

  • Meta (Facebook/Instagram), Google Ads, TikTok Ads, YouTube Ads, Amazon Ads, Shopify Ads, DSP/programmatic

Platform behavior guidance:

  • Keep channel recommendations execution-specific and auditable.
  • Align bid logic with each platform's optimization mechanics.

Constraints And Guardrails

  • No irreversible chan...

Source information

Source
github
Repository
openclaw/skills
Path
skills/danyangliu-sandwichlab/lanbow-ads
Version
—
Commit
0816935e8aa1feb790bf33d706e9cca33587da53
Classification source
rules
Status
active
Visibility
public

These signals come from indexed source analysis and may lag behind changes. Check the current source files.

Extracted content

SKILL.md
# Lanbow Ads

## Purpose
Core mission:
- Serve as Lanbow's dedicated ad operations and optimization interface.
- Manage planning, launch, monitoring, and scaling across ad channels.
- Standardize decision policies for bidding, budget, and performance recovery.
- Output clear operator actions for media teams.

## When To Trigger
Use this skill when the user asks for:
- campaign setup, optimization, or scaling in one or more channels
- budget and bidding decision support with performance constraints
- anomaly diagnosis and recovery actions for live campaigns
- cross-channel media operation playbooks

High-signal keywords:
- lanbow ads, run ads, campaign, media buyer
- bidding, budget, allocation, optimize, scale
- cpa, roas, performance, monitor, abtest

## Input Contract
Required:
- campaign_objective
- channel_scope
- budget_constraints
- recent_performance_snapshot

Optional:
- creative_state
- audience_state
- tracking_health
- policy_or_account_flags

## Output Contract
1. Campaign Action Plan
2. Bidding and Budget Policy
3. AB Test and Scale Model
4. Monitoring and Alert Plan
5. Operator Handoff Checklist

## Workflow
1. Normalize objective and KPI constraints.
2. Evaluate channel readiness and structure quality.
3. Produce bid and allocation actions.
4. Attach testing and scaling rules.
5. Return monitoring triggers and operator checklist.

## Decision Rules
- If measurement confidence is low, limit scale and improve tracking first.
- If ROAS is stable above threshold, allow staged budget increases.
- If CPA is unstable, reduce concurrency of experiments.
- If anomaly risk is high, prefer containment actions first.

## Platform Notes
Primary scope:
- Meta (Facebook/Instagram), Google Ads, TikTok Ads, YouTube Ads, Amazon Ads, Shopify Ads, DSP/programmatic

Platform behavior guidance:
- Keep channel recommendations execution-specific and auditable.
- Align bid logic with each platform's optimization mechanics.

## Constraints And Guardrails
- No irreversible chan...

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