search-term-miner
Analyze Search Terms for Better Paid Campaigns
Paid-search exports can hide converting queries and costly irrelevant traffic. This skill turns an export into keyword opportunities, negative keywords, n-gram waste findings, and a reviewable maintenance diff.
Install with my Agent
Copy this request to your Agent. It includes the canonical Skill page and manifest.
Review the Skillstore skill "search-term-miner" from https://skillstore.io/skills/aaron-he-zhu-search-term-miner.md and its manifest at https://skillstore.io/api/skills/aaron-he-zhu-search-term-miner/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.Your Agent should still show its plan and request any confirmation required by the security policy.
Agent-readable resources
Use these links when an AI agent, crawler, or script needs clean context instead of reading the full page.
Test it
Using "search-term-miner". A search-terms export with cost, conversions, and conversion value.
Expected outcome:
- Candidate keyword: "emergency plumbing repair" because it has conversions and strong value.
- Negative review: "free plumbing course" because it has spend and no conversions.
- Waste theme: "course" appears across several non-converting queries.
Using "search-term-miner". A monthly export from a prospecting campaign.
Expected outcome:
- Add: high-intent converting query themes.
- Negate: irrelevant queries after human review.
- Move: queries that need a more specific ad group.
Security Audit
SafeAll 35 static detections are false positives caused by Markdown backticks, relative documentation links, and repository metadata. The skill describes analysis of a user-provided paid-search export and requires confirmation before saving a workspace summary. No executable command, network request, path traversal operation, reconnaissance behavior, or prompt injection attempt was found.
Risk Factors
⚙️ External commands (14)
🌐 Network access (2)
Share & cite this report
Share the versioned assessment report, neutral badge, embed card, and citations. Skillstore reports evidence without deciding whether this Skill is safe.
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https://skillstore.io/skills/aaron-he-zhu-search-term-miner/audits/6?utm_source=security_passport&utm_medium=share&utm_campaign=versioned_reportMarkdown badge
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<a href="https://skillstore.io/skills/aaron-he-zhu-search-term-miner?utm_source=security_passport_badge"><img src="https://skillstore.io/badges/skills/aaron-he-zhu-search-term-miner/security.svg" alt="Skillstore security assessment" loading="lazy"></a>Embed card
<iframe src="https://skillstore.io/embed/skills/aaron-he-zhu-search-term-miner.html" title="Skillstore Security Assessment" sandbox="allow-popups allow-popups-to-escape-sandbox" loading="lazy" referrerpolicy="no-referrer" width="420" height="180"></iframe>Academic citations (APA · BibTeX · CFF)
APA citation
aaron-he-zhu. (2026). search-term-miner security audit report (audit version 6) [Author version 19.0.0]. Skillstore. https://skillstore.io/skills/aaron-he-zhu-search-term-miner/audits/6BibTeX citation
@techreport{aaron-he-zhu-aaron-he-zhu-search-term-miner-2026,
author = {aaron-he-zhu},
title = {search-term-miner security audit report (audit version 6)},
institution = {Skillstore},
year = {2026},
number = {6},
url = {https://skillstore.io/skills/aaron-he-zhu-search-term-miner/audits/6},
note = {Author version 19.0.0}
}CITATION.cff
cff-version: 1.2.0
message: "If you use this Skill, cite its author and this versioned security audit report."
title: "search-term-miner security audit report (audit version 6)"
version: "19.0.0"
type: report
authors:
- name: "aaron-he-zhu"
date-released: "2026-07-27"
url: "https://skillstore.io/skills/aaron-he-zhu-search-term-miner/audits/6"
identifiers:
- type: other
value: "skillstore:aaron-he-zhu-search-term-miner:audit:6"
description: "Skillstore immutable audit report identifier"
Skillstore Score
Why this score Evidence Confidence: MediumWhat You Can Build
Review monthly search-term waste
Find costly non-converting queries and produce a negative-keyword review list.
Discover new keyword themes
Turn proven converting queries into candidate keywords and ad-group themes.
Prepare a client optimization report
Create a clear maintenance diff and n-gram waste summary from a client export.
Try These Prompts
Analyze this search-terms export. List candidate keywords, negative keywords for review, and the evidence for each recommendation.
Mine this export for queries with spend but no conversions. Create an n-gram waste report and group the proposed negatives by theme.
Use this search-terms export to create a maintenance diff with Add, Negate, and Move sections. Include query metrics and state any assumptions.
Compare these two search-terms exports. Identify new converting themes, emerging waste, and changes to the negative-keyword review list.
Best Practices
- Export sufficient date range and include cost, conversion, and conversion-value columns when possible.
- Review negative-keyword recommendations for relevance before applying them.
- Use consistent campaign and match-type context when interpreting query performance.
Avoid
- Do not add every non-converting query as a negative keyword without checking volume and intent.
- Do not treat a small export as conclusive evidence of long-term performance.
- Do not use this skill as a substitute for budget allocation or account-structure planning.
Frequently Asked Questions
What file should I provide?
Can it change my campaigns?
What metrics are most useful?
What is an n-gram waste report?
Should I accept every negative-keyword recommendation?
Does it build campaign structure?
Developer Details
Author
aaron-he-zhuLicense
Apache-2.0
Author version
v19.0.0
Skillstore revision
r2
Repository
https://github.com/aaron-he-zhu/aaron-marketing-skills/tree/main/ad/research/search-term-minerRef
0715a6e09ea875c8e28cb705ce87cc83045e69c1
Maintenance freshness
7/28/2026
Usage
2 downloads · 1 views
File structure
📄 SKILL.md