Best use case
Marketing Orchestrator Skill is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
## Purpose
Teams using Marketing Orchestrator Skill should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/marketing-orchestrator/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How Marketing Orchestrator Skill Compares
| Feature / Agent | Marketing Orchestrator Skill | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
## Purpose
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
Related Guides
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SKILL.md Source
# Marketing Orchestrator Skill
## Purpose
Orchestrates the marketing audit pipeline by sequentially running the following collector agents:
- Instagram Collector
- Meta Ads Collector
- SEO / Keyword Collector
- Competitor Finder
- Website Audit Collector
Aggregates the individual results and invokes the Report Generator skill to produce the final comprehensive marketing audit report.
## Input Schema
```typescript
interface MarketingInput {
instagramHandle?: string;
websiteDomain?: string;
}
```
## Output Schema
```typescript
interface MarketingAuditReport {
reportMarkdown: string;
rawData: any;
error?: string;
}
```
## Implementation Pattern
- Validate input: either `instagramHandle` or `websiteDomain` is required
- Sequentially call each collector skill, passing relevant input
- Collect results in a composite data object
- Call report-generator skill with the aggregated data
- Return the final report markdown and raw data
## Example Usage
```typescript
const input = { instagramHandle: 'gymshark', websiteDomain: 'gymshark.com' };
const report = await marketingOrchestrator(input);
console.log(report.reportMarkdown);
```
## Orchestration Logic (Pseudocode)
```typescript
async function marketingOrchestrator(input: MarketingInput): Promise<MarketingAuditReport> {
if (!input.instagramHandle && !input.websiteDomain) {
throw new Error("Either instagramHandle or websiteDomain is required");
}
const auditData: any = {
input,
collectedAt: new Date().toISOString(),
};
if (input.instagramHandle) {
auditData.instagram = await runSkill('instagram-collector', { handle: input.instagramHandle });
}
if (input.websiteDomain) {
auditData.metaAds = await runSkill('meta-ads-collector', { brandName: input.websiteDomain, domain: input.websiteDomain });
auditData.keywords = await runSkill('seo-collector', { domain: input.websiteDomain });
auditData.competitors = await runSkill('competitor-finder', { brandName: input.websiteDomain, domain: input.websiteDomain });
auditData.websiteAudit = await runSkill('website-audit', { domain: input.websiteDomain });
}
const report = await runSkill('report-generator', auditData);
return {
reportMarkdown: report.reportMarkdown,
rawData: auditData,
};
}
```
## Notes
- Each runSkill call corresponds to invoking another skill as a sub-agent or subprocess.
- The calling framework should handle API keys, env vars for external services.
- Errors in individual collectors should not block the overall orchestration.
- Extend as needed for additional collectors or data sources.Related Skills
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