skill-010-campaign-priority-experiments

skill-010-campaign-priority-experiments is a skill for Claude Code from TrueClicks/claude-plugins. It costs 31 tokens per session (670 once invoked), scanned A, original, MIT.

A guide for checking Google Ads Shopping campaign priority settings and experiment or draft structure. Shopping campaigns are ad campaigns for products, and priority controls which campaign receives matching traffic.

In plain words
What is it for?
Use it to retrieve Shopping priorities and experiment details, then review campaign status, merchant IDs, dates, and experiment structure.
Why use it?
Incorrect priorities can send traffic to the wrong campaigns and make experiment results unreliable. It identifies the data needed to check these settings.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

Part of the google-ads plugin — 145 skills, 4 commands shipped together

Good fit Use it to retrieve Shopping priorities and experiment details, then review campaign status, merchant IDs, dates, and experiment structure.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/trueclicks/claude-plugins/skill-010-campaign-priority-experiments
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add TrueClicks/claude-plugins --skill skill-010-campaign-priority-experiments
Clone the repo
git clone --depth 1 https://github.com/TrueClicks/claude-plugins

Made for: Claude Code.

Or install google-ads, the plugin that ships this one along with the rest of its 145 skills, 4 commands.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

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README.md
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<a href="https://agentmods.dev/skills/trueclicks/claude-plugins/skill-010-campaign-priority-experiments"><img src="https://agentmods.dev/badge/skills/trueclicks/claude-plugins/skill-010-campaign-priority-experiments.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 31 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 670 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00031 $0.00670
Opus 5.5 $0.00012 $0.00268
Sonnet 5.5 $0.00006 $0.00134
Haiku 4.5 $0.00003 $0.00067

Measured 1mo ago against content hash 00300d9f209b, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

skill-010-campaign-priority-experiments scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

plugins/google-ads/skills/skill-010-campaign-priority-experiments/SKILL.md · 88 lines

How it starts

The opening of the file, as written. The whole thing — 88 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Skill 010: Campaign Priority and Experiment Structure

Purpose

Ensure campaign priorities (especially for Shopping) are correctly configured and that experiments/drafts are properly structured. Incorrect priority settings cause traffic to route to the wrong campaigns, distorting results.

Data Requirements

Data Source: Custom GAQL Required

Standard export includes basic shopping settings but may lack complete priority data. Custom GAQL provides experiment information.

GAQL Query (Shopping priorities):

SELECT
  campaign.id,
  campaign.name,
  campaign.status,
  campaign.shopping_setting.campaign_priority,
  campaign.shopping_setting.merchant_id,
  campaign.advertising_channel_type
FROM campaign
WHERE campaign.advertising_channel_type = 'SHOPPING'
  AND campaign.status != 'REMOVED'

GAQL Query (experiments):

SELECT
  experiment.experiment_id,
  experiment.name,
  experiment.status,
  experiment.type,
  experiment.start_date,
  experiment.end_date
FROM experiment

Run via /google-ads:get-custom with query names shopping_priorities and experiments.

Analysis Steps

  1. Analyze Shopping priorities: List all Shopping campaigns with priorities (0=Low, 1=Medium, 2=High); check for conflicts
  2. Validate priority logic: Higher priority campaigns should have negatives to funnel specific queries
  3. Review experiments: List active experiments; check duration (2-4 weeks recommended) and traffic split
  4. Check experiment best practices: One variable tested, sufficient budget, clear success metrics
  5. Identify issues: Overlapping priorities without differentiation, experiments running too long/short

Thresholds

Condition Severity
Multiple Shopping campaigns with same priority and overlapping products Critical
High priority campaign without negatives Warning
Experiment running > 8 weeks Warning
Experiment < 2 weeks Info
Experiment traffic split uneven (>60/40) Info

Read the full file on GitHub · 88 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 1mo ago First seen · 88 lines · 31 tokens per session scan A 00300d9f209b

Subscribe to this mod's changes

skill-010-campaign-priority-experiments is a skill published in the GitHub repository TrueClicks/claude-plugins (2 stars, last pushed 22d ago), licensed MIT. It adds 31 tokens to every session and 670 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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