Geo Fundamentals
wasp-lang/wasp
Generative Engine Optimization for AI search engines (ChatGPT, Claude, Perplexity).
Plan, write and measure ads inside AI assistants and AI search (ChatGPT Ads, Google AI Overviews and AI Mode, Microsoft Copilot).
$ npx skills add borghei/Claude-Skills --skill conversational-ads -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install borghei/Claude-Skills conversational-ads --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/borghei/Claude-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/marketing/conversational-ads .claude/skills/conversational-ads && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "conversational-ads" agent skill from https://github.com/borghei/Claude-Skills/tree/main/marketing/conversational-ads into .claude/skills/conversational-ads/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "conversational-ads", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/borghei/Claude-Skills/tree/main/marketing/conversational-adsType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add borghei/Claude-Skills --skill conversational-ads -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install borghei/Claude-Skills conversational-ads --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/borghei/Claude-Skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/marketing/conversational-ads .agents/skills/conversational-ads && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "conversational-ads" agent skill from https://github.com/borghei/Claude-Skills/tree/main/marketing/conversational-ads into .agents/skills/conversational-ads/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "conversational-ads", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add borghei/Claude-Skills --skill conversational-ads -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install borghei/Claude-Skills conversational-ads --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/borghei/Claude-Skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/marketing/conversational-ads .cursor/skills/conversational-ads && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "conversational-ads" agent skill from https://github.com/borghei/Claude-Skills/tree/main/marketing/conversational-ads into .cursor/skills/conversational-ads/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "conversational-ads", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/borghei/Claude-Skills.git --path marketing/conversational-ads--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add borghei/Claude-Skills --skill conversational-ads -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install borghei/Claude-Skills conversational-ads --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/borghei/Claude-Skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/marketing/conversational-ads .gemini/skills/conversational-ads && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "conversational-ads" agent skill from https://github.com/borghei/Claude-Skills/tree/main/marketing/conversational-ads into .gemini/skills/conversational-ads/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "conversational-ads", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install borghei/Claude-Skills conversational-adsInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add borghei/Claude-Skills --skill conversational-ads -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/borghei/Claude-Skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/marketing/conversational-ads .github/skills/conversational-ads && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "conversational-ads" agent skill from https://github.com/borghei/Claude-Skills/tree/main/marketing/conversational-ads into .github/skills/conversational-ads/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "conversational-ads", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add borghei/Claude-Skills --skill conversational-ads -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install borghei/Claude-Skills conversational-ads --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/borghei/Claude-Skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/marketing/conversational-ads .opencode/skills/conversational-ads && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "conversational-ads" agent skill from https://github.com/borghei/Claude-Skills/tree/main/marketing/conversational-ads into .opencode/skills/conversational-ads/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "conversational-ads", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
conversational-adsPlan, write and measure ads inside AI assistants and AI search (ChatGPT Ads, Google AI Overviews and AI Mode, Microsoft Copilot).
Conversational Ads is an agent skill from borghei/Claude-Skills. Plan, write and measure ads inside AI assistants and AI search (ChatGPT Ads, Google AI Overviews and AI Mode, Microsoft Copilot). Use when testing ChatGPT ads, answer-adjacent copy, or incrementality for AI placements.
Its SKILL.md is about 2.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 11 other files, including scripts, reference files and assets (for example `assets/sample_ad_copy.json`, `assets/sample_plan_input.json` and `assets/test-plan-template.md`).
It sits in Marketing & SEO, covering AI search optimization. It works with OpenAI. The repository describes itself as: 385 AI skills, 77 expert agents, and 900 stdlib Python tools for every team: engineering, PM, marketing, C-level, compliance, business ops, research, and a LinkedIn toolkit… The licence is MIT.
5 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit 4a698e8. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Ships 2 files in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
python3From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Conversational Ads loads about 2.9k tokens when it runs, and up to ~8.2k if it reads all its reference files. Until then it costs about 59 tokens; SKILL.md has 1,392 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.
The full file from borghei/Claude-Skills at commit 4a698e8, republished under its MIT licence (© borghei). 1,392 words, ~2,907 tokens.
.claude/skills/conversational-ads/SKILL.md (or your agent's skills folder). This skill also uses 8 other files; get the full folder from GitHub.Paid placements next to AI answers: ChatGPT Ads (test began February 2026, self-serve Ads Manager since May 2026), Google ads in AI Overviews and AI Mode, and ads in Microsoft Copilot. This skill covers what is different from search, which platforms your category and market can use, how to write copy that sits next to an answer without borrowing its authority, how to get feeds and landing pages ready, and how to prove incrementality when two of the three platforms give no placement-level reporting.
Platform facts are as of September 2026 and come from each platform's own help pages — see references/platform-specs.md. These products change monthly; re-check the linked pages before committing budget.
| Situation | Use |
|---|---|
| "Should we test ChatGPT ads?" / first AI-placement test | scripts/conversational_ad_planner.py + test-plan template |
| Writing ad copy for ChatGPT, AI Overviews, AI Mode or Copilot | Creative rules below + scripts/answer_adjacent_copy_linter.py |
| Explaining why AI Overviews spend can't be reported or turned off | platform-specs.md |
| Measuring whether AI placements add conversions | Measurement workflow + playbook §5 |
| Earning organic citations in AI answers (not paid) | Out of scope — this skill is paid media only |
| Labelling AI-generated creative | Out of scope beyond a lint warning — use a disclosure/compliance process |
Before planning, confirm these inputs. If any is unknown or vague, ASK — do not assume:
Stop rule: ask only the 2-3 that most change the output. If the user says "just draft it," proceed and list your assumptions at the top of the plan.
# 1. Plan: eligibility, mix, holdout test, KPI targets, readiness (exit 2 = blocked)
python3 scripts/conversational_ad_planner.py assets/sample_plan_input.json
python3 scripts/conversational_ad_planner.py my_brief.json --format json --min-conversions 100
# 2. Lint copy before upload (exit 2 = errors; --strict fails on warnings too)
python3 scripts/answer_adjacent_copy_linter.py assets/sample_ad_copy.json
# 3. Fill assets/test-plan-template.md and freeze it before launchThe shipped samples fail on purpose: the planner exits 2 because the Copilot arm is underpowered at USD 12,000/month and a USD 60 CPA; the linter exits 2 with 10 errors across three broken ads (assistant-endorsement copy, unsubstantiated "clinically proven", over-length Google headline, unverified testimonial, http landing URL). Two ads pass clean.
| Search ad | Answer-adjacent ad | |
|---|---|---|
| Intent | Short query | Whole conversation + the answer's content |
| Control | Keywords, placements | Broad matching; Google and Microsoft: no opt-out, no placement targeting |
| Reporting | By placement | ChatGPT: own reporting. Google: counted as Top ads, no AI segment. Microsoft: no Copilot metrics |
| Creative job | Beat nine other links | Add a useful fact the answer lacks |
| Main risk | Low CTR | Looking like you hijacked a trusted answer |
Position: optimise inputs (feed, assets, landing pages, negatives) and read outcomes with holdout experiments. Do not try to optimise a placement you cannot see.
| ChatGPT Ads | Google AI Overviews / AI Mode | Microsoft Copilot | |
|---|---|---|---|
| How to buy | Direct, Ads Manager (beta), CPC or outcome bidding | Indirect: Search with broad match / AI Max, Shopping, PMax | Indirect: PMax, Search with logo, Shopping, Multimedia, some vertical ads |
| Who sees ads | Logged-in adults on Free and Go plans; not Plus/Pro/Business/Enterprise/Edu; not Temporary Chats | English queries in AU, CA, IN, ID, KE, MY, NZ, NG, PK, PH, SG, US (AI Overviews) | Copilot users; negative keywords apply |
| Excluded | Near health, mental health, politics; several categories disallowed; finance/health/legal by manual approval | Adult, alcohol, gambling, finance, healthcare, politics and more | Bing policies; ads not shown in flagged conversations |
| Measurement | Pixel + Conversions API, UTMs, macros | Blended into Top ads | Search term + asset reports only |
| Copy | Title 16-24, copy 32-48 chars (recommended) | RSA 30 / 90 chars (limits) | RSA 30 / 90 chars (limits) |
Perplexity: 2024 ads experiment announced; current availability unverified — excluded from the planner.
assets/sample_plan_input.json shows every field).BLOCKERS first: drop a platform, raise budget, extend weeks, or install tracking.READINESS items marked MISSING — landing pages that answer the prompt and a clean feed matter more than bids. [RECOMMENDED]assets/test-plan-template.md, pick treated and holdout regions, and set the freeze window.ERROR; review WARNINGs — ChatGPT length ranges are recommendations, not limits.substantiated_claims.utm_medium=cpc so paid clicks stay out of GA4's organic AI Assistant channel.For Google and Microsoft, the holdout measures the campaign change that made you eligible (e.g. moving to broad match / AI Max / PMax), not the AI placement alone. State that in the readout.
| Code | Planner | Linter | Who fixes it |
|---|---|---|---|
| 0 | Plan produced, no blockers | No errors (warnings allowed unless --strict) | Nobody |
| 1 | Tool error — bad path, malformed JSON, missing field | Tool error — bad path, malformed JSON, unknown platform | Whoever maintains the input file |
| 2 | Blocked — no eligible platform, no conversion tracking, or an underpowered arm | Gate failed — errors (or warnings with --strict) | Media planner / copywriter |
Mistake: "ChatGPT's top pick", "Recommended by Copilot", copy styled to look like the answer. Why it happens: The answer carries trust and teams want some of it. Instead: Ads are labelled Sponsored and separated from answers by design, and OpenAI's ad policies prohibit false endorsements. Lead with a fact the answer lacks. The linter blocks this pattern.
Mistake: Scaling on platform-reported conversions in week 3. Why it happens: It is the only number available, and Google/Microsoft do not isolate AI placements. Instead: Build the holdout before launch and decide on incremental CPA.
Mistake: A media-plan line called "AI Overviews" with its own budget. Why it happens: Plans expect one line per placement. Instead: On Google and Microsoft, fund the underlying Search broad / AI Max / Shopping / PMax campaigns and test the change that made you eligible.
Mistake: A few thousand dollars split three ways for a four-week test. Why it happens: Fear of missing the next channel. Instead: Concentrate until each arm can reach ~50 conversions. The planner exits 2 on underpowered arms.
Mistake: Polishing creative while product titles lack the attributes people ask about and prices lag the site. Why it happens: Feeds belong to another team. Instead: Treat the feed as creative. Audit the top SKUs against real prompts and use delta feeds for price and availability.
More in references/anti-patterns.md.
| Symptom | Likely cause | Fix |
|---|---|---|
| Planner says Google ineligible for a US brand | language not en or category in excluded list | Check brief; plan classic search for excluded categories |
| Every arm UNDERPOWERED | Budget/CPA too low for three arms | Drop to one platform or extend test_weeks |
| Linter flags a claim you can prove | Claim not listed in substantiated_claims | Add the exact term once evidence is on file |
| Linter misses a restricted term | Category regexes are deliberately conservative | Extend CATEGORY_TERMS for your vertical |
| GA4 shows paid ChatGPT clicks under "AI Assistant" | Missing utm_medium=cpc | Add UTMs or platform macros to every destination URL |
| Script | Purpose |
|---|---|
scripts/conversational_ad_planner.py | Brief → eligibility, placement mix, holdout test plan, KPI targets, readiness, blockers |
scripts/answer_adjacent_copy_linter.py | Ad copy → length, claims, assistant-endorsement, category, pressure, CTA, URL/UTM, price, testimonial, AI-media and style checks |
Both: Python 3.8+ standard library only, --format text|json, deterministic.
assets/sample_plan_input.json — planning brief (exits 2: underpowered arm)assets/sample_ad_copy.json — five ads, two clean and three broken (exits 2)assets/test-plan-template.md — hypothesis, prompts, eligibility, design, power, KPIs, readiness, readout© borghei, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 8 other files (scripts, references, assets) in marketing/conversational-ads of borghei/Claude-Skills.
Open the folder on GitHubat commit 4a698e8
Conversational Ads next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Conversational Ads this skillborghei/Claude-Skills | 881 | — | ~2.9k | Automated safety check: Pass | MIT | |
| Geo Fundamentalswasp-lang/wasp | 19k | 9 repos | ~861 | Automated safety check: Pass | MIT | |
| SEO GeoReScienceLab/opc-skills | 1.8k | 4 repos | ~2.1k | Automated safety check: Pass | Apache-2.0 | |
| GEO-First SEO Audit Toolzubair-trabzada/geo-seo-claude | 11k | — | ~2.8k | Automated safety check: Notes | MIT | |
| SEO DataforseoAgriciDaniel/codex-seo | 791 | 2 repos | ~4.6k | Automated safety check: Pass | MIT | |
| Fire Your SEO Agencyleopard627/fire-your-seo-agency | 707 | — | ~1.1k | Automated safety check: Pass | MIT |
wasp-lang/wasp
Generative Engine Optimization for AI search engines (ChatGPT, Claude, Perplexity).
ReScienceLab/opc-skills
SEO & GEO (Generative Engine Optimization) for websites. An agent skill from ReScienceLab/opc-skills.
zubair-trabzada/geo-seo-claude
Audits a website for AI search visibility across ChatGPT, Claude, Perplexity and Google AI Overviews while checking traditional SEO, schema and E-E-A-T content quality.
AgriciDaniel/codex-seo
Live SEO data via DataForSEO MCP server. An agent skill from AgriciDaniel/codex-seo.
leopard627/fire-your-seo-agency
SEO·AEO·GEO·LLMO·NEO(네이버) 다섯 레인을 진단하고 직접 구현하며, 인용되는 콘텐츠를 계속 생산하는 서브 블로그·콘텐츠 운영 파이프라인까지 세팅하는 스킬.
Yuzzyuk/marketing-os
A complete marketing department in one skill. An agent skill from Yuzzyuk/marketing-os.
borghei/Claude-Skills
Run delivery when AI coding and ops agents take tickets. An agent skill from borghei/Claude-Skills.
borghei/Claude-Skills
Check AI-generated marketing content and reviews for required disclosures under the EU AI Act, FTC rules and platform AI-label policies.
borghei/Claude-Skills
Idea to AI-generated prototype to customer validation to engineering handoff.
borghei/Claude-Skills
Analytics engineering across data modeling, dbt, transformation, and semantic layers.
borghei/Claude-Skills
Ansoff Matrix — 4-quadrant framework for growth options: market penetration, market/product development, and diversification.
borghei/Claude-Skills
OKR brainstorming and validation using the Radical Focus framework — outcome objectives, measurable key results, counter-metrics.
Works with
Categories
Plan, write and measure ads inside AI assistants and AI search (ChatGPT Ads, Google AI Overviews and AI Mode, Microsoft Copilot). Conversational Ads is an agent skill from borghei/Claude-Skills. Plan, write and measure ads inside AI assistants and AI search (ChatGPT Ads, Google AI Overviews and AI Mode, Microsoft Copilot).
Conversational Ads fits situations like: testing ChatGPT ads; answer-adjacent copy; incrementality for AI placements.
Run `npx skills add borghei/Claude-Skills --skill conversational-ads -a claude-code`. Or copy the skill folder (marketing/conversational-ads in borghei/Claude-Skills) into .claude/skills/conversational-ads in your project. Claude Code loads it when a task matches its description.
Run `npx skills add borghei/Claude-Skills --skill conversational-ads -a codex`. Or copy the skill folder (marketing/conversational-ads in borghei/Claude-Skills) into .agents/skills/conversational-ads in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add borghei/Claude-Skills --skill conversational-ads -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/conversational-ads, .gemini/skills/conversational-ads, .github/skills/conversational-ads and .opencode/skills/conversational-ads in your project.
Going by SKILL.md and its folder, Conversational Ads needs Python for the scripts in its folder and the command-line tools its instructions call (python3). Our summary lists: Python 3.
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
Conversational Ads is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.9k tokens (SKILL.md is roughly 12k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 5.2k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Conversational Ads: Geo Fundamentals (wasp-lang/wasp, 19k stars), SEO Geo (ReScienceLab/opc-skills, 1.8k stars), GEO-First SEO Audit Tool (zubair-trabzada/geo-seo-claude, 11k stars) and SEO Dataforseo (AgriciDaniel/codex-seo, 791 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
borghei (a GitHub user) maintains it in borghei/Claude-Skills, which has 881 GitHub stars. The repository holds 349 skills in this directory. The repository was last updated on October 7, 2026.
Source: borghei/Claude-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.