← ClaudeAtlas

hector-brand-ads-auditlisted

Use ONLY when the user explicitly asks to run a "brand ads audit", "ads audit", "advertising audit", or "brand advertising audit" for a named brand or Amazon Ads profile. Trigger phrases include "run an ads audit for X", "run a brand audit for X", "do an advertising audit on X", "audit X's Amazon ads", and close paraphrases where "audit" + ("ads" OR "advertising" OR "brand") co-occur. Builds a 5-pillar HTML slide deck (Account Overview, Bleeding, Harvesting, Headroom, Placement + Strategy) via Hector MCP and renders 1280×720 slides. Does NOT fire on conversational mentions of audits, on bid-lookup or date-resolution requests, on questions about audit methodology without an account named, or on requests to edit this skill. ALWAYS asks precursor questions (account+country, date range, comparison toggle, focus ASINs, currency-override) before any MCP call.
hectorai-live/hector-amazon-ads · ★ 0 · Web & Frontend · score 72
Install: claude install-skill hectorai-live/hector-amazon-ads
# Hector Brand Advertising Audit (v1.1) > ## ⚠️ CRITICAL OBLIGATIONS — READ BEFORE EVERY USE > > 1. **ALWAYS run the precursor-questions block before any MCP call.** Account+country, date range, comparison toggle, focus ASINs, currency-override. The audit cannot begin until REQUIRED precursors are answered. > 2. **NEVER guess the profile_id.** Always resolve via `find_profile_by_name`. If multiple profiles match, present them and have the user pick. If zero match, surface that — do not proceed. > 3. **Push filters server-side wherever possible.** Use `master_search_filters` on every `analytics_*` call. Client-side filtration is reserved only for what server-side cannot do (multi-token brand exclusion, ASIN-pattern matching, normalized joins). > 4. **Use temp files for any MCP response >30 rows.** Write raw response to `/home/claude/audit_data/<pillar>_raw.json` immediately. Process via Python script that writes `<pillar>_aggregated.json`. Only the small aggregate enters chat context. This is mandatory — context overflow is the #1 risk to multi-pillar runs. > 5. **Bleeding is UNGROUPED.** One row per search-term × campaign × ad-group combination. Negation happens at ad-group level — grouping hides which campaign to negate in. Reinstate Campaign column. > 6. **Headroom and Harvesting are GROUPED by SearchTerm.** Impression share is a search-term-level metric. Same brand classifier applied per pillar (exclude in bleeding, partition in headroom, exclude in harvesting). > 7. **He