# Full multi-platform ads audit Human Guide

## What This Is For
Full multi-platform paid advertising audit with parallel subagent delegation. It gives the agent a clearer input/output frame for paid media: what context to ask for, what decisions to make, and what usable artifact to return.

Use this as a human-readable version of the Full multi-platform ads audit agent skill. It is meant for marketers, operators, founders, and other non-coders who want the workflow without reading agent-specific implementation instructions.

## When To Use This
- Use this when you need a repeatable process for full multi-platform ads audit.
- Use this when the task needs judgment, examples, constraints, or a clear output format rather than a one-off prompt.
- Use this when you want to hand an AI assistant enough context to produce a usable marketing artifact.

## When Not To Use This
- Do not use this when you only need a quick factual answer.
- Do not use this when the work depends on private data you cannot share with the assistant.
- Do not use this as a replacement for legal, compliance, financial, or medical review.

## What You Need Before Starting
- The goal or business outcome you want.
- The audience, customer segment, or market context.
- Any source material the assistant should respect, such as notes, briefs, examples, URLs, or brand guidance.
- Constraints such as tone, length, channel, deadline, region, or approval requirements.
- A clear definition of what a good final answer should look like.

## Step-By-Step Workflow
1. State the job clearly: "Use the Full multi-platform ads audit guide to help me with..."
2. Add context: audience, goal, offer, channel, source material, and constraints.
3. Ask the assistant to identify missing inputs before producing the final output.
4. Have the assistant follow the skill-specific guidance below.
5. Review the result against the final checklist and ask for revisions where needed.

## Skill-Specific Guidance
- Read the main `ads` operating contract and thinking framework.
- Create a run manifest with business context, date window, currency, timezone,
- Normalize exports, screenshots, manual metrics, or authenticated reads into an
- Discover active platforms. Confirm requested inactive or data-less platforms
- Load each selected platform capability manifest, control registry, dated source
- Dispatch independent platform workers and cross-platform workers in parallel.
- Validate every result against the common finding schema. Retry one transient
- Run deterministic scoring. Do not calculate or repair scores in the prompt.
- Synthesize systemic findings across measurement, budget, creative, landing
- Write one atomic run bundle and render the requested reports.
- Verify bundle completeness, citations, privacy, and render integrity.
- Creative and landing-page quality.

## Decision Points And Nuance
The original skill emphasizes: Procedure, Platform workers, Required finding fields, Completeness rules, Required-worker failure and weighting, Synthesis boundaries, Outputs.

Use these questions to steer the work:
- What is the intended audience or buyer?
- What source material must be preserved?
- What should the assistant optimize for: clarity, persuasion, accuracy, speed, creativity, or conversion?
- What examples represent the desired quality bar?
- What should the assistant avoid?

## Common Mistakes
- that bundle. Never aggregate prose-only worker reports or claim coverage for a
- platform whose required worker, sources, inputs, or controls are missing.
- Run deterministic scoring. Do not calculate or repair scores in the prompt.
- `complete`: every requested required worker returned valid results and every
- `provisional`: all required workers returned, but one or more platforms have
- `partial`: a required platform or cross-platform worker failed or was omitted.
- Never substitute feature awareness for account health. Optional, beta, premium,
- Required-worker failure and weighting

## Copy-And-Paste Prompt
```text
Use the Full multi-platform ads audit human guide.

My goal:
[Describe the business outcome]

Audience:
[Describe who this is for]

Context and source material:
[Paste notes, examples, links, or existing copy]

Constraints:
[Tone, length, channel, timeline, must-include items, must-avoid items]

Before producing the final output, ask me for any missing information that would materially improve the result.
```

## Final Checklist
- [ ] The output matches the original goal.
- [ ] The audience and context are reflected in the answer.
- [ ] Important constraints and source material were preserved.
- [ ] The assistant made the relevant decisions explicit.
- [ ] The final artifact is ready to use, review, or hand to the next person.

## Source
This guide was generated from the agricidaniel/claude-ads skill entry for `ads-audit`.

## Source Skill Notes
These notes preserve the nuance from the original skill. Use them as supporting reference when the workflow above feels too generic.

# Paid Advertising Audit

Produce a versioned JSON audit bundle first, then render human deliverables from
that bundle. Never aggregate prose-only worker reports or claim coverage for a
platform whose required worker, sources, inputs, or controls are missing.

## Procedure

1. Read the main `ads` operating contract and thinking framework.
2. Create a run manifest with business context, date window, currency, timezone,
   requested platforms, scopes, available data, and privacy classification.
3. Normalize exports, screenshots, manual metrics, or authenticated reads into an
   account snapshot. Preserve source lineage and mark missing fields.
4. Discover active platforms. Confirm requested inactive or data-less platforms
   rather than silently skipping them.
5. Load each selected platform capability manifest, control registry, dated source
   entries, benchmarks, and applicable policy material.
6. Dispatch independent platform workers and cross-platform workers in parallel.
7. Validate every result against the common finding schema. Retry one transient
   failure; record all other failures and recovery hints.
8. Run deterministic scoring. Do not calculate or repair scores in the prompt.
9. Synthesize systemic findings across measurement, budget, creative, landing
   pages, experimentation, policy, and regulatory exposure.
10. Write one atomic run bundle and render the requested reports.
11. Verify bundle completeness, citations, privacy, and render integrity.

## Platform workers

Use a dedicated worker for every selected platform:

- `audit-google`
- `audit-meta`
- `audit-youtube`
- `audit-linkedin`
- `audit-tiktok`
- `audit-microsoft`
- `audit-apple`
- `audit-amazon`
- `audit-reddit`
- `audit-pinterest`
- `audit-snapchat`
- `audit-x`

Add cross-platform workers only when their inputs exist:

- Tracking and attribution.
- Creative and landing-page quality.
- Budget, pacing, and financial viability.
- Platform policy, privacy, and regulation.

## Required finding fields

Each worker returns conclusions, not files:

```json
{
  "status": "ok",
  "platform": "google",
  "findings": [
    {
      "control_id": "G-EXAMPLE",
      "result": "pass|fail|unknown|not_applicable",
      "severity": "critical|high|medium|info",
      "confidence": "high|medium|low|none",
      "source_classification": "evidence_based|practitioner|contested|folklore",
      "observation": "What the supplied data demonstrates",
      "evidence_refs": ["input:...", "source:..."],
      "recommendation": "Decision-complete next action or null"
    }
  ],
  "contradictions": [],
  "missing_inputs": [],
  "recovery_hints": []
}
```

Validate against the repository schema rather than relying on this illustrative
fragment when the installed schema is available.

## Completeness rules