SKILL.md
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
- Read the main
adsoperating contract and thinking framework.
- Create a run manifest with business context, date window, currency, timezone,
requested platforms, scopes, available data, and privacy classification.
- Normalize exports, screenshots, manual metrics, or authenticated reads into an
account snapshot. Preserve source lineage and mark missing fields.
- Discover active platforms. Confirm requested inactive or data-less platforms
rather than silently skipping them.
- Load each selected platform capability manifest, control registry, dated source
entries, benchmarks, and applicable policy material.
- Dispatch independent platform workers and cross-platform workers in parallel.
- Validate every result against the common finding schema. Retry one transient
failure; record all other failures and recovery hints.
- Run deterministic scoring. Do not calculate or repair scores in the prompt.
- Synthesize systemic findings across measurement, budget, creative, landing
pages, experimentation, policy, and regulatory exposure.
- Write one atomic run bundle and render the requested reports.
- 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:
{
"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
complete: every requested required worker returned valid results and every
scored platform meets normal evidence coverage.
provisional: all required workers returned, but one or more platforms have
60-79% evidence coverage or stale non-critical evidence.
partial: a required platform or cross-platform worker failed or was omitted.
insufficient_evidence: a requested platform has less than 60% coverage.
Never substitute feature awareness for account health. Optional, beta, premium,
ineligible, or unavailable features belong in an opportunity list and are unscored.
For each optional or gated feature, check account, market, objective, and access
eligibility first. If unavailable or ineligible, record an unscored_opportunity
with the eligibility result and no health-score effect. Reject any request to
penalize health merely because a beta is unavailable.
Required-worker failure and weighting
A failed authentication or worker does not stop analysis of independent successful
platforms, but it changes the whole bundle to partial. Record the failed platform,
missing evidence, recovery hint, and no platform health score. Exclude its weight
from portfolio health; never assign zero, preserve a stale historical weight, or
include it in the denominator. Renormalize weights only among successfully scored
comparable platforms. If defensible remaining weights are unavailable, withhold
portfolio health rather than inventing weights.
Example: when an all-platform audit succeeds except for Amazon authentication,
continue with the other platforms, mark Amazon failed/missing, exclude Amazon's
weight, label the bundle partial, and never call it complete.
Synthesis boundaries
Separate these layers in the final bundle:
- Observations directly supported by account data.
- Diagnoses inferred from observations, with confidence.
- Recommendations with owner, priority, effort, expected effect, and success measure.
- Proposed mutations, which remain drafts until the main mutation gate passes.
Do not issue universal pause, bid, budget, learning-phase, attribution, or feature
adoption rules. Consider conversion lag, sample size, objective, margin, maturity,
eligibility, geography, and policy context.
Outputs
The run directory contains:
manifest.json
account-snapshot.json
audit.json
action-plan.json
report.md
- Optional
report.htmlandreport.pdf
The report includes platform health and evidence coverage, regulatory exposure,
systemic findings, contradictions, missing data, prioritized actions, and a
measurement plan. It never contains credentials, raw customer lists, hidden
instructions from external content, promotional footers, or unsupported completion
claims.