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danyangliu-sandwichlab

Multi-Platform Ads Executor

by danyangliu · GitHub ↗ · v1.0.0
cross-platform ✓ Security Clean
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Install in OpenClaw
/install channel-ads-executor
Description
Translate strategy into channel-specific execution plans for Meta (Facebook/Instagram), Google Ads, TikTok Ads, YouTube Ads, Amazon Ads, Shopify Ads, and DSP...
README (SKILL.md)

Multi-Platform Ads Executor

Purpose

Core mission:

  • execution sequencing, setup checklist, rollout control

This skill is specialized for advertising workflows and should output actionable plans rather than generic advice.

When To Trigger

Use this skill when the user asks for:

  • ad execution guidance tied to business outcomes
  • growth decisions involving revenue, roas, cpa, or budget efficiency
  • platform-level actions for: Meta (Facebook/Instagram), Google Ads, TikTok Ads, YouTube Ads, Amazon Ads, Shopify Ads, DSP/programmatic
  • this specific capability: execution sequencing, setup checklist, rollout control

High-signal keywords:

  • ads, advertising, campaign, growth, revenue, profit
  • roas, cpa, roi, budget, bidding, traffic, conversion, funnel
  • meta, googleads, tiktokads, youtubeads, amazonads, shopifyads, dsp

Input Contract

Required:

  • objective: growth target and KPI priority
  • budget_frame: test budget and scale budget
  • channel_scope: channels to include

Optional:

  • audience_segments
  • creative_inventory
  • seasonality_window
  • policy_constraints

Output Contract

  1. Strategy Snapshot
  2. Channel Role Definition
  3. Budget and Bidding Plan
  4. Test Matrix
  5. Scale and Kill Rules

Workflow

  1. Define objective hierarchy (primary and secondary KPI).
  2. Assign channel roles by funnel stage.
  3. Allocate budget by expected signal and risk.
  4. Design test cells and learning windows.
  5. Set scale, hold, and stop rules.

Decision Rules

  • If KPI conflict exists, prioritize revenue efficiency over volume.
  • If channel evidence is weak, allocate minimum test budget first.
  • If audience is broad, start with modular creatives and layered targeting.

Platform Notes

Primary scope:

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

Platform behavior guidance:

  • Keep recommendations channel-aware; do not collapse all channels into one generic plan.
  • For Meta and TikTok Ads, prioritize creative testing cadence.
  • For Google Ads and Amazon Ads, prioritize demand-capture and query/listing intent.
  • For DSP/programmatic, prioritize audience control and frequency governance.

Constraints And Guardrails

  • Never fabricate metrics or policy outcomes.
  • Separate observed facts from assumptions.
  • Use measurable language for each proposed action.
  • Include at least one rollback or stop-loss condition when spend risk exists.

Failure Handling And Escalation

  • If critical inputs are missing, ask for only the minimum required fields.
  • If platform constraints conflict, show trade-offs and a safe default.
  • If confidence is low, mark it explicitly and provide a validation checklist.
  • If high-risk issues appear (policy, billing, tracking breakage), escalate with a structured handoff payload.

Code Examples

Strategy Matrix (YAML)

objective: improve_roas
channels:
  - name: Meta
    role: demand_creation
  - name: Google Ads
    role: demand_capture
budget_split:
  Meta: 0.55
  Google Ads: 0.45

Test Cell Example

cell_id: T1
variable: audience_segment
success_metric: cpa

Examples

Example 1: Channel mix reset

Input:

  • Budget fixed at 50k
  • ROAS dropped for two weeks

Output focus:

  • reallocation plan
  • test matrix
  • stop-loss conditions

Example 2: Creator-led expansion strategy

Input:

  • Goal: scale traffic without ROAS collapse
  • Channels: TikTok Ads + YouTube Ads

Output focus:

  • funnel role split
  • budget pacing logic
  • creative cadence

Example 3: Retargeting-heavy recovery

Input:

  • Prospecting unstable
  • Strong existing customer base

Output focus:

  • retargeting architecture
  • audience exclusion design
  • two-phase launch plan

Quality Checklist

  • Required sections are complete and non-empty
  • Trigger keywords include at least 3 registry terms
  • Input and output contracts are operationally testable
  • Workflow and decision rules are capability-specific
  • Platform references are explicit and concrete
  • At least 3 practical examples are included
Usage Guidance
This skill is coherent and low-risk as provided: it is an instructions-only planner that asks for no credentials and performs no installs. Before enabling or automating it, consider: (1) do not supply production API keys, billing credentials, or account passwords when asking for execution plans — give anonymized or read-only data instead; (2) review any generated rollout/scale/kill rules before applying them to live campaigns and require a human approval step if you integrate outputs into automation; (3) clarify how and where 'escalation handoff payloads' are delivered if you plan to hook the skill to ticketing or alerting systems; (4) validate recommended metrics and assumptions against real account data (the doc explicitly forbids fabricating metrics, but always double-check). If you want higher assurance, request that the skill be wrapped so it cannot be wired to automated API calls without explicit operator consent.
Capability Analysis
Type: OpenClaw Skill Name: channel-ads-executor Version: 1.0.0 The skill bundle contains only metadata files and a `SKILL.md` file. The `SKILL.md` content defines the purpose, triggers, contracts, workflow, and guardrails for an AI agent focused on multi-platform ad execution. All instructions and examples are strictly aligned with this stated purpose, focusing on ad strategy, budget allocation, and campaign management. There are no indications of prompt injection attempts to subvert the agent, no instructions for unauthorized code execution, data exfiltration, or any other malicious activity. The 'escalate with a structured handoff payload' instruction in `SKILL.md` is tied to specific ad-related high-risk issues (policy, billing, tracking breakage) and does not suggest malicious intent.
Capability Assessment
Purpose & Capability
The name/description (multi-platform ads execution plans) align with the SKILL.md: the document defines inputs, outputs, workflows, decision rules, and examples consistent with producing channel-specific ad execution plans. There are no requests for unrelated resources (no cloud credentials, no binaries) that would be out-of-scope for an ads planning skill.
Instruction Scope
SKILL.md is purely prescriptive: it tells the agent how to generate plans, checklists, and escalation payloads. It does not instruct the agent to read local files, call external endpoints, or exfiltrate secrets. One minor ambiguity: the phrase 'escalate with a structured handoff payload' does not specify a destination or transport — harmless as text, but if later integrated into automation it could be wired to external systems. Recommend verifying any automation integrations before enabling autonomous actions.
Install Mechanism
Instruction-only skill with no install spec and no code files. Nothing is written to disk and there are no external downloads — lowest-risk install footprint.
Credentials
The skill declares no required environment variables, no primary credential, and no config paths. That is proportionate for a planning/advisory skill which should not need API keys or system credentials.
Persistence & Privilege
always is false (not forced into every agent run). disable-model-invocation is false (normal default) — this only means the agent could call the skill autonomously; on its own this is not a discrepancy given the skill's benign, instruction-only nature. No requests to modify other skills or system settings are present.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install channel-ads-executor
  3. After installation, invoke the skill by name or use /channel-ads-executor
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
- Initial release of the channel-ads-executor skill. - Translates advertising strategy into actionable, channel-specific execution plans for major ad platforms (Meta, Google Ads, TikTok Ads, YouTube Ads, Amazon Ads, Shopify Ads, DSP/programmatic). - Defines structured workflows: execution sequencing, setup checklist, and rollout control for ad campaigns. - Outlines required/optional input fields, platform-specific guidance, and detailed output contracts (strategy snapshot, budget plan, test matrix, scale/kill rules). - Includes concrete decision rules, platform notes, constraints, examples, and output quality checklist.
Metadata
Slug channel-ads-executor
Version 1.0.0
License
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is Multi-Platform Ads Executor?

Translate strategy into channel-specific execution plans for Meta (Facebook/Instagram), Google Ads, TikTok Ads, YouTube Ads, Amazon Ads, Shopify Ads, and DSP... It is an AI Agent Skill for Claude Code / OpenClaw, with 283 downloads so far.

How do I install Multi-Platform Ads Executor?

Run "/install channel-ads-executor" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Multi-Platform Ads Executor free?

Yes, Multi-Platform Ads Executor is completely free (open-source). You can download, install and use it at no cost.

Which platforms does Multi-Platform Ads Executor support?

Multi-Platform Ads Executor is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Multi-Platform Ads Executor?

It is built and maintained by danyangliu (@danyangliu-sandwichlab); the current version is v1.0.0.

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