# Google Search Ads Builder > Build a complete, import-ready Google Search Ads campaign from scratch — deep keyword research (competitor mining, review/community/HN language, site audit, autocomplete), keyword architecture with funnel + intent classification, ad-group structure, RSA copy (15 headlines / 4 descriptions per group), negative-keyword lists, bid strategy, and a Google Ads Editor import CSV. For early-stage teams who'd otherwise waste their first $5K. - Skill: `robomotionio/google-search-ads-builder` (Agent Skill, multi-file: 6 files) - Install (CLI): `npx skillmds@latest add robomotionio/google-search-ads-builder` - Raw SKILL.md: https://api.skillmd.com/api/skills/robomotionio/google-search-ads-builder/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Marketing & Growth - Author: robomotionio (https://skillmd.com/u/robomotionio) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/robomotionio/google-search-ads-builder --- # Google Search Ads Builder Composite: **keyword research → architecture → structure → copy → negatives → bid → export.** Scripts cover the deterministic research primitives (HN terminology, autocomplete expansion) and the export (RSA-limit validation + Google Ads Editor CSV). **The architecture, intent/funnel classification, ad-group design, RSA copywriting, negatives, and bid strategy are the agent's reasoning** — then validated and serialized by the export script. ## When to use - "Set up Google Search Ads for ``" / "Build a PPC campaign." - "Do keyword research for Google Ads" / "What keywords should we bid on?" - "Generate Google Ads copy" / "I need an import file for Google Ads Editor." ## How to run ### 1 — Keyword research Seeds + competitor/review/community mining are agent-driven via web search (Robomotion Proxy, `geo`): `site:`, ` alternative/vs`, `best tools`, `site:g2.com`/`site:capterra.com`, `site:reddit.com`. **SERP path: if `DATAFORSEO_LOGIN`/ `DATAFORSEO_PASSWORD` (or `SERPER_API_KEY`) is set → structured SERP API and real keyword volume/difficulty; if not → the agent's keyless web search with directional volume (default).** Reuse the **`google-ad-scraper`** capability for competitor ad terms, and **`fetch_landing_page.py`** from `../ad-to-landing-page-auditor/scripts/` (or web search) for the own-site / competitor content audit. Deterministic research primitives: ```bash # Technical-buyer framing from Hacker News (keyless) python3 ${SKILL_DIR}/scripts/hn_terms.py --query "workflow automation" --days 365 --output ${WORKSPACE}/hn.json # Autocomplete / modifier / long-tail expansion (keyless Google Suggest) python3 ${SKILL_DIR}/scripts/autocomplete_expand.py --seeds "workflow automation,rpa software" \ --geo US --alpha --output ${WORKSPACE}/expanded.json ``` For Reddit/review depth beyond search: **if `APIFY_API_TOKEN` is set → use an Apify actor (better depth); if not → degrade to `site:` web search over public pages (default).** ### 2 — Architecture, structure, copy, negatives, bid (you, the agent) From the pooled keywords: classify funnel stage + intent, estimate competitive density (from SERP density + autocomplete + HN/review frequency — **paid keyword-volume/difficulty is an optional enrichment: if `DATAFORSEO_*` is set use its real metrics, else derive directional volume from the keyless signals**), score keywords, pull a quick-wins list. Build ad groups (**≤15 single-theme keywords each, one LP per group**). Write **3 RSAs per ad group: 15 headlines ≤30 chars, 4 descriptions ≤90 chars.** Build negatives (universal + category + intent + competitor + cross-ad-group). Recommend bid strategy + budget split by `monthly_budget` tier. Emit the campaign as a JSON tree (see `build_import_csv.py` header for the shape) to `${WORKSPACE}/campaign.json`. ### 3 — Validate limits + emit the import CSV ```bash python3 ${SKILL_DIR}/scripts/build_import_csv.py --input ${WORKSPACE}/campaign.json \ --csv ${WORKSPACE}/google-ads-import-$(date +%F).csv \ --report ${WORKSPACE}/validation.json ``` This **enforces RSA char limits and ad-group caps before writing the CSV** so the import won't reject rows. If `ok:false`, fix the flagged headlines/descriptions and rerun — the CSV is not written on validation failure (exit code 1). ### 4 — Render the strategy doc Write `google-search-campaign-.md` to `${WORKSPACE}` (overview, research summary, competitive density map, campaign tree, keywords with match type/funnel stage/ intent/priority, RSA copy, negatives, bid + budget split, top-10 quick-wins, launch checklist) and attach both it and the CSV to the Agent Teams channel. ## Outputs - `google-search-campaign-.md` — the strategy doc. - `google-ads-import-.csv` — Google Ads Editor import file. ## Credentials / env - **Required:** none — keyword research runs on web search + the keyless HN API + Google Suggest; the export is stdlib. Architecture/copy/bid are the agent's reasoning. - **Optional (each with a keyless default fallback):** - `APIFY_API_TOKEN` — if set → Apify Reddit/review actor for depth; else → `site:` web search over public pages (default). - `DATAFORSEO_LOGIN`/`DATAFORSEO_PASSWORD` (or `SERPER_API_KEY`) — if set → structured SERP API + real keyword volume/difficulty; else → keyless web search + directional volume from SERP density + Google Suggest + HN/review frequency (default). - `HTTPS_PROXY` — Robomotion Proxy for geo-correct SERP/autocomplete/research. ## Notes & edge cases - Paid search-volume is optional enrichment: with `DATAFORSEO_*` set, use real keyword volume/difficulty; without it (default), derive volume/competition directionally from SERP density + autocomplete + HN/review frequency. - RSA limits are enforced by `build_import_csv.py` (headline ≤30, description ≤90); fix and rerun on failure rather than shipping a rejecting import. - Cap each ad group at 15 single-theme keywords; cross-negative between groups to stop cannibalization. - Use a proxy + `geo` so SERP/review/autocomplete results reflect the target market.