Agent skill

Google Ads Intent Map

by TheMattBerman in TheMattBerman/google-ads-copilot

Build or update a Google Ads Intent Map from search terms, campaign data, and account context.

Install Google Ads Intent Map

skills CLI

$ npx skills add TheMattBerman/google-ads-copilot --skill google-ads-intent-map -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI

$ gh skill install TheMattBerman/google-ads-copilot google-ads-intent-map --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy

$ git clone --depth 1 https://github.com/TheMattBerman/google-ads-copilot.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/google-ads-intent-map .claude/skills/google-ads-intent-map && rm -rf skills-src

Use ~/.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/

Paste into Claude Code

Install the "google-ads-intent-map" agent skill from https://github.com/TheMattBerman/google-ads-copilot/tree/main/skills/google-ads-intent-map into .claude/skills/google-ads-intent-map/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "google-ads-intent-map", 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

$skill-installer install https://github.com/TheMattBerman/google-ads-copilot/tree/main/skills/google-ads-intent-map

Type 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.

skills CLI

$ npx skills add TheMattBerman/google-ads-copilot --skill google-ads-intent-map -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install TheMattBerman/google-ads-copilot google-ads-intent-map --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/TheMattBerman/google-ads-copilot.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/google-ads-intent-map .agents/skills/google-ads-intent-map && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "google-ads-intent-map" agent skill from https://github.com/TheMattBerman/google-ads-copilot/tree/main/skills/google-ads-intent-map into .agents/skills/google-ads-intent-map/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "google-ads-intent-map", 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.

skills CLI

$ npx skills add TheMattBerman/google-ads-copilot --skill google-ads-intent-map -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install TheMattBerman/google-ads-copilot google-ads-intent-map --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/TheMattBerman/google-ads-copilot.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/google-ads-intent-map .cursor/skills/google-ads-intent-map && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "google-ads-intent-map" agent skill from https://github.com/TheMattBerman/google-ads-copilot/tree/main/skills/google-ads-intent-map into .cursor/skills/google-ads-intent-map/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "google-ads-intent-map", 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

$ gemini skills install https://github.com/TheMattBerman/google-ads-copilot.git --path skills/google-ads-intent-map

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add TheMattBerman/google-ads-copilot --skill google-ads-intent-map -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install TheMattBerman/google-ads-copilot google-ads-intent-map --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/TheMattBerman/google-ads-copilot.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/google-ads-intent-map .gemini/skills/google-ads-intent-map && rm -rf skills-src

Use ~/.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/

Paste into Gemini CLI

Install the "google-ads-intent-map" agent skill from https://github.com/TheMattBerman/google-ads-copilot/tree/main/skills/google-ads-intent-map into .gemini/skills/google-ads-intent-map/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "google-ads-intent-map", 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.

GitHub CLI

$ gh skill install TheMattBerman/google-ads-copilot google-ads-intent-map

Installs 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).

skills CLI

$ npx skills add TheMattBerman/google-ads-copilot --skill google-ads-intent-map -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/TheMattBerman/google-ads-copilot.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/google-ads-intent-map .github/skills/google-ads-intent-map && rm -rf skills-src

Use ~/.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/

Paste into GitHub Copilot

Install the "google-ads-intent-map" agent skill from https://github.com/TheMattBerman/google-ads-copilot/tree/main/skills/google-ads-intent-map into .github/skills/google-ads-intent-map/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "google-ads-intent-map", 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.

skills CLI

$ npx skills add TheMattBerman/google-ads-copilot --skill google-ads-intent-map -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install TheMattBerman/google-ads-copilot google-ads-intent-map --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/TheMattBerman/google-ads-copilot.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/google-ads-intent-map .opencode/skills/google-ads-intent-map && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "google-ads-intent-map" agent skill from https://github.com/TheMattBerman/google-ads-copilot/tree/main/skills/google-ads-intent-map into .opencode/skills/google-ads-intent-map/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "google-ads-intent-map", 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.

Facts

Skill name: google-ads-intent-map
GitHub stars: 238
Token cost: ~1.6k tokens
SKILL.md length: 643 words
Files: 1
Skills in repo: 16
Repo updated: Jun 10, 2026
First seen: Oct 7, 2026
Licence: MIT

At a glance

Build or update a Google Ads Intent Map from search terms, campaign data, and account context.

Works in 11 steps: Announce mode (connected/export). → In connected mode, run the shared… → If pmax-fallback, use rows for… → …
Tasks that involve Paid advertising
SKILL.md covers Data Acquisition, Process, Always Answer and Draft Output, plus 2 more sections
Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Google Ads Intent Map is an agent skill from TheMattBerman/google-ads-copilot. Build or update a Google Ads Intent Map from search terms, campaign data, and account context. Pulls live data via MCP or works with manual exports. Produces structure drafts when intent classes need separation.

Its SKILL.md is about 1.6k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Marketing & SEO, covering Paid advertising. It works with Google Ads and Model Context Protocol. The repository describes itself as: Google Ads Copilot: operator kit for audits, MCP-connected reads, export-mode analysis, and draft/apply workflows. The licence is MIT.

When your agent uses it

Tasks that involve Paid advertising

Example prompts

“/google-ads-intent-map”

Workflow steps

11 steps, taken from the first numbered list in SKILL.md.

Announce mode (connected/export).
In connected mode, run the shared retrieval ladder (data/search-term-retrieval.md). Report retrieval_mode in the output header.
If pmax-fallback, use rows for clustering but note that performance profiling is unavailable. If limited, clustering is blocked — request…
Load existing Intent Map from workspace/ads/intent-map.md if it exists.
Identify recurring query clusters and modifiers across all terms.
Classify clusters into intent classes
For each class: note representative queries, performance profile, and current routing (which campaign/ad group they land in).
Separate high-confidence signals from ambiguous ones.
Infer structural implications — which classes are incorrectly sharing optimization buckets?
Build or update workspace/ads/intent-map.md.
Use the operator summary template when presenting results.

What it can do on your machine

Read from SKILL.md and the folder at commit 2c253ee. It shows what the files ask for, not the result of running them.

Tool permissions
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.
Runs code
No scripts in the folder and no shell commands in SKILL.md (its code samples are sql).
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Google Ads Intent Map loads about 1.6k tokens when it runs. Until then it costs about 58 tokens; SKILL.md has 643 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~58
When it runs · the whole SKILL.md, loaded when a task matches: ~1.6k

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.

Safety

Auto-check passed

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); files beside SKILL.md are not scanned.

SKILL.md

The full file from TheMattBerman/google-ads-copilot at commit 2c253ee, republished under its MIT licence (© TheMattBerman). 643 words, ~1,567 tokens.

Download SKILL.mdSave it as .claude/skills/google-ads-intent-map/SKILL.md (or your agent's skills folder).

name: google-ads-intent-map
description: Build or update a Google Ads Intent Map from search terms, campaign data, and account context. Pulls live data via MCP or works with manual exports. Produces structure drafts when intent classes need separation.

Google Ads Intent Map

Read first:

google-ads/references/operator-thesis.md
google-ads/references/intent-map.md
google-ads/references/query-patterns.md
google-ads/references/deliverable-templates.md

Read workspace if available:

workspace/ads/account.md
workspace/ads/goals.md
workspace/ads/intent-map.md
workspace/ads/queries.md
workspace/ads/winners.md
workspace/ads/learnings.md

Data Acquisition

Connected Mode (MCP available)

Pull via the search tool on google-ads-mcp:

Primary: All search terms for clustering — last 30 days:

sql

SELECT
  search_term_view.search_term,
  campaign.name,
  campaign.advertising_channel_type,
  metrics.impressions,
  metrics.clicks,
  metrics.cost_micros,
  metrics.conversions,
  metrics.conversions_value,
  metrics.all_conversions
FROM search_term_view
WHERE segments.date DURING LAST_30_DAYS
ORDER BY metrics.impressions DESC
LIMIT 1000

Retrieval ladder — if the primary query returns no rows, follow the shared retrieval ladder in data/search-term-retrieval.md. In pmax-fallback mode, use rows for clustering but note that performance metrics are unavailable for intent-class profiling. In limited mode, clustering is blocked — request a UI export.

Supplementary: Campaign and ad group structure (for routing analysis):

sql

SELECT
  campaign.name,
  campaign.advertising_channel_type,
  ad_group.name,
  ad_group.status,
  metrics.impressions,
  metrics.clicks,
  metrics.cost_micros,
  metrics.conversions
FROM ad_group
WHERE campaign.status = 'ENABLED'
  AND ad_group.status = 'ENABLED'
  AND segments.date DURING LAST_30_DAYS
ORDER BY campaign.name, ad_group.name

See data/gaql-recipes.md for additional queries.

Date Range Fallback

If LAST_30_DAYS returns too few terms for meaningful clustering (<20 terms), fall back to LAST_90_DAYS, then all-time. Intent mapping benefits from volume — more search terms means better clustering. Always state the date range used.

Export Mode (no MCP)

Ask the user for:

Search Terms report: last 30 days, all terms (not just top spenders)
Include: Search term, Campaign, Ad group, Impressions, Clicks, Cost, Conversions, Conv. value
Campaign names are essential for routing analysis

See data/export-formats.md for recommended format.

Process

Announce mode (connected/export).
In connected mode, run the shared retrieval ladder (data/search-term-retrieval.md). Report retrieval_mode in the output header.
If pmax-fallback, use rows for clustering but note that performance profiling is unavailable. If limited, clustering is blocked — request a UI export.
Load existing Intent Map from workspace/ads/intent-map.md if it exists.
Identify recurring query clusters and modifiers across all terms.
Classify clusters into intent classes:
- Buyer — high commercial intent, ready to convert
- Comparison — evaluating options, not yet committed
- Informational — learning, researching, no purchase signal
- Navigational — looking for a specific brand/page
- Branded — searching for your brand specifically
- Junk — no plausible path to conversion
For each class: note representative queries, performance profile, and current routing (which campaign/ad group they land in).
Separate high-confidence signals from ambiguous ones.
Infer structural implications — which classes are incorrectly sharing optimization buckets?
Build or update workspace/ads/intent-map.md.
Use the operator summary template when presenting results.

Always Answer

What query patterns signal a likely buyer?
What patterns signal weak or misleading intent?
What traffic types should never be optimized together?
What language repeats among likely winners?
What should be cut, isolated, or tested next?
Where is intent mixing causing structural problems?

Draft Output

Show full SKILL.md (259 more words)Show less

Structure Draft

Trigger: Two or more distinct intent classes are sharing a single campaign or ad group, AND the performance gap between them is significant (e.g., 2x+ CPA difference, or one class converts and the other doesn't).

Create a draft using drafts/templates/structure-draft.md:

Write to workspace/ads/drafts/YYYY-MM-DD-[account-slug]-structure.md
Specify exactly which intent classes to separate, which campaigns/ad groups to split
Include keyword lists or patterns that should route to each new bucket
Update workspace/ads/drafts/_index.md

Negative Draft (secondary)

Trigger: Intent Map reveals a clear junk class that should be excluded account-wide.

Create using drafts/templates/negative-draft.md if the junk class is better solved by exclusion than by structure.

Always update workspace memory:

workspace/ads/intent-map.md — the primary deliverable. Rebuild or update the map.
workspace/ads/queries.md — notable clusters
workspace/ads/findings.md — strategic observations about intent routing

Output Shape

Account Status block — account name, CID, status, date range used, tracking confidence, mode
Data summary (terms analyzed, date range)
Intent Map (classes with representative queries, performance, current routing)
Routing problems (intent classes sharing wrong buckets)
Structural implications (what should be separated)
Emerging patterns (new intent classes forming)
Confidence assessment per class
Drafts created (with paths and summaries)
Memory updates

Rules

Do not confuse underperformance with irrelevance.
Do not recommend negatives where isolation is the better move.
Prefer pattern interpretation over checklist regurgitation.
The Intent Map is the most strategic artifact in the workspace. Treat updates seriously — it compounds across every other skill.
When in doubt between "exclude" and "isolate," prefer isolation. You can always exclude later. You can't un-exclude query data you never saw.

Files

Just SKILL.md in skills/google-ads-intent-map of TheMattBerman/google-ads-copilot.

Open the folder on GitHubat commit 2c253ee

Compare with similar skills

Google Ads Intent Map 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.

Google Ads Intent Map compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Google Ads Intent Map this skillTheMattBerman/google-ads-copilot	238	—	~1.6k	Automated safety check: Pass	MIT	3 mo ago
Google Ads Landing Page Auditnowork-studio/notfair-plugin	3.9k	—	~2.7k	Automated safety check: Pass	MIT	7 days ago
Google Ads API MCP Setupgoogle/skills	21k	—	~6.1k	Automated safety check: Notes	Apache-2.0	today
21 Audit Ads Performanceminhnv0807/ai-business-skills	608	—	~4.6k	Automated safety check: Pass	MIT	26 days ago
Connectindranilbanerjee/digital-marketing-pro	855	1 repos	~2k	Automated safety check: Pass	MIT	4 days ago
Launch Ad Campaignindranilbanerjee/digital-marketing-pro	855	1 repos	~3.9k	Automated safety check: Pass	MIT	4 days ago

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Works with

Questions about Google Ads Intent Map

What does Google Ads Intent Map do?

Build or update a Google Ads Intent Map from search terms, campaign data, and account context. Google Ads Intent Map is an agent skill from TheMattBerman/google-ads-copilot. Build or update a Google Ads Intent Map from search terms, campaign data, and account context.

When should I use Google Ads Intent Map?

Google Ads Intent Map fits situations like: tasks that involve Paid advertising.

How do I install Google Ads Intent Map in Claude Code?

Run `npx skills add TheMattBerman/google-ads-copilot --skill google-ads-intent-map -a claude-code`. Or copy the skill folder (skills/google-ads-intent-map in TheMattBerman/google-ads-copilot) into .claude/skills/google-ads-intent-map in your project. Claude Code loads it when a task matches its description.

How do I install Google Ads Intent Map in Codex?

Run `npx skills add TheMattBerman/google-ads-copilot --skill google-ads-intent-map -a codex`. Or copy the skill folder (skills/google-ads-intent-map in TheMattBerman/google-ads-copilot) into .agents/skills/google-ads-intent-map in your project. Codex loads it when a task matches its description.

Can I use Google Ads Intent Map in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add TheMattBerman/google-ads-copilot --skill google-ads-intent-map -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/google-ads-intent-map, .gemini/skills/google-ads-intent-map, .github/skills/google-ads-intent-map and .opencode/skills/google-ads-intent-map in your project.

What does Google Ads Intent Map need to run?

SKILL.md names no scripts, command-line tools or credentials: Google Ads Intent Map is instructions for the agent only.

Does Google Ads Intent Map access the network?

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.

Is Google Ads Intent Map safe to install?

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. Review the folder before installing.

What licence does Google Ads Intent Map use?

Google Ads Intent Map is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Google Ads Intent Map use?

About 1.6k tokens (SKILL.md is roughly 6.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Google Ads Intent Map?

Skills that share tags, products or a category with Google Ads Intent Map: Google Ads Landing Page Audit (nowork-studio/notfair-plugin, 3.9k stars), Google Ads API MCP Setup (google/skills, 21k stars), 21 Audit Ads Performance (minhnv0807/ai-business-skills, 608 stars) and Connect (indranilbanerjee/digital-marketing-pro, 855 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Google Ads Intent Map?

TheMattBerman (a GitHub user) maintains it in TheMattBerman/google-ads-copilot, which has 238 GitHub stars. The repository holds 16 skills in this directory. The repository was last updated on June 10, 2026.

Source: TheMattBerman/google-ads-copilot on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Google Ads Intent Map

Facts

At a glance

What it does

When your agent uses it

Example prompts

Workflow steps

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

Google Ads Intent Map

Data Acquisition

Connected Mode (MCP available)

Date Range Fallback

Export Mode (no MCP)

Process

Always Answer

Draft Output

Structure Draft

Negative Draft (secondary)

Always update workspace memory:

Output Shape

Rules

Files

Compare with similar skills

Similar skills

More from TheMattBerman/google-ads-copilot

Related

Questions about Google Ads Intent Map