SEO-AEO Keyword Research

Overview

This public intake copy packages

plugins/antigravity-awesome-skills-claude/skills/seo-aeo-keyword-research

https://github.com/sickn33/antigravity-awesome-skills

Use it when the operator needs the upstream workflow, support files, and repository context to stay intact while the public validator and private enhancer continue their normal downstream flow.

This intake keeps the copied upstream files intact and uses

metadata.json

ORIGIN.md

SEO-AEO Keyword Research

Imported source sections that did not map cleanly to the public headings are still preserved below or in the support files. Notable imported sections: How It Works, Common Pitfalls, Limitations.

When to Use This Skill

Use this section as the trigger filter. It should make the activation boundary explicit before the operator loads files, runs commands, or opens a pull request.

• Use when you need to build a keyword strategy for a new topic or niche
• Use when you want to find AEO question queries for AI engine citation
• Use when you need to prioritise which keywords to target first
• Use when you want to check for keyword cannibalization before writing content
• Use when the request clearly matches the imported source intent: Researches and prioritises SEO keywords with AEO question queries, difficulty tiers, cannibalization checks, and a content map. Activate when the user wants to find keywords, research search terms, or build a keyword....
• Use when the operator should preserve upstream workflow detail instead of rewriting the process from scratch.

Operating Table

metadata.json

ORIGIN.md

SKILL.md

SKILL.md

## Related Skills

Workflow

This workflow is intentionally editorial and operational at the same time. It keeps the imported source useful to the operator while still satisfying the public intake standards that feed the downstream enhancer flow.

1. Confirm the user goal, the scope of the imported workflow, and whether this skill is still the right router for the task.
2. Read the overview and provenance files before loading any copied upstream support files.
3. Load only the references, examples, prompts, or scripts that materially change the outcome for the current request.
4. Execute the upstream workflow while keeping provenance and source boundaries explicit in the working notes.
5. Validate the result against the upstream expectations and the evidence you can point to in the copied files.
6. Escalate or hand off to a related skill when the work moves out of this imported workflow's center of gravity.
7. Before merge or closure, record what was used, what changed, and what the reviewer still needs to verify.

Imported Workflow Notes

Imported: Overview

Identifies high-value SEO keywords and AEO question-based queries for a topic. Produces keyword tiers (easy wins to long-term goals), search intent classification, cannibalization checks, and a content production map — all from a single topic input.

Part of the SEO-AEO Engine — an open-source AI-powered content growth system.

Imported: How It Works

Step 1: Extract Seed Keywords

Identify 3–5 core terms that anchor the topic's search territory. Go beyond the obvious head term to include adjacent terms the audience actually uses.

Step 2: Expand Into Tiers

Sort all keywords into three tiers:

• Tier 1 — Low-to-moderate difficulty. Target first.
• Tier 2 — Medium difficulty. Build toward after Tier 1 content is live.
• Tier 3 — High difficulty. Long-term goals only.

Step 3: Generate AEO Keywords

Produce question-based keywords that AI engines surface in direct answers and People Also Ask boxes. For each AEO keyword, specify the answer format to use (definition sentence, numbered steps, comparison table, direct number).

Step 4: Run Cannibalization Check

Flag any two keywords similar enough to split traffic if targeted on separate pages. Recommend which page should own which term.

Step 5: Build Content Map

Recommend content type and production order for all Tier 1 and Tier 2 keywords.

Examples

Example 1: Ask for the upstream workflow directly

Use @seo-aeo-keyword-research to handle <task>. Start from the copied upstream workflow, load only the files that change the outcome, and keep provenance visible in the answer.

Explanation: This is the safest starting point when the operator needs the imported workflow, but not the entire repository.

Example 2: Ask for a provenance-grounded review

Review @seo-aeo-keyword-research against metadata.json and ORIGIN.md, then explain which copied upstream files you would load first and why.

Explanation: Use this before review or troubleshooting when you need a precise, auditable explanation of origin and file selection.

Example 3: Narrow the copied support files before execution

Use @seo-aeo-keyword-research for <task>. Load only the copied references, examples, or scripts that change the outcome, and name the files explicitly before proceeding.

Explanation: This keeps the skill aligned with progressive disclosure instead of loading the whole copied package by default.

Example 4: Build a reviewer packet

Review @seo-aeo-keyword-research using the copied upstream files plus provenance, then summarize any gaps before merge.

Explanation: This is useful when the PR is waiting for human review and you want a repeatable audit packet.

Imported Usage Notes

Imported: Examples

Example 1: SaaS Product

Input: topic = "remote project management software" audience = "engineering managers and startup founders" goal = "convert" Output: Tier 1 Keywords:

"remote project management software" | Medium volume | Difficulty: 38 "project management tool remote teams" | Low volume | Difficulty: 29

AEO Keywords:

"What is the best project management software for remote teams?" → Answer format: Comparison table "How does remote project management work?" → Answer format: Numbered steps

Content Map:

Landing page → "remote project management software" Pillar blog → "complete guide to remote project management" Cluster article → "how to manage remote engineering teams"

Example 2: Fintech App

Input: topic = "automated budgeting app" audience = "millennials managing personal finances" goal = "all" Output: Tier 1 Keywords:

"automated budgeting app" | Medium volume | Difficulty: 33 "automatic savings app" | Low volume | Difficulty: 24

AEO Keywords:

"What is the best budgeting app for millennials?" → Answer format: Comparison table "How does automated budgeting work?" → Answer format: Numbered steps

Best Practices

Treat the generated public skill as a reviewable packaging layer around the upstream repository. The goal is to keep provenance explicit and load only the copied source material that materially improves execution.

• ✅ Do: Target Tier 1 keywords first — build authority before going after competitive terms
• ✅ Do: Use AEO keywords in FAQ sections and definition blocks for AI engine citation
• ✅ Do: Validate estimated volume and difficulty with a live tool (Ahrefs, SEMrush) before committing
• ❌ Don't: Target two keywords on the same page if cannibalization is flagged
• ❌ Don't: Use volume as the only prioritisation signal — difficulty and intent matter more
• Keep the imported skill grounded in the upstream repository; do not invent steps that the source material cannot support.
• Prefer the smallest useful set of support files so the workflow stays auditable and fast to review.

Imported Operating Notes

Imported: Best Practices

• ✅ Do: Target Tier 1 keywords first — build authority before going after competitive terms
• ✅ Do: Use AEO keywords in FAQ sections and definition blocks for AI engine citation
• ✅ Do: Validate estimated volume and difficulty with a live tool (Ahrefs, SEMrush) before committing
• ❌ Don't: Target two keywords on the same page if cannibalization is flagged
• ❌ Don't: Use volume as the only prioritisation signal — difficulty and intent matter more

Troubleshooting

Problem: The operator skipped the imported context and answered too generically

Symptoms: The result ignores the upstream workflow in

plugins/antigravity-awesome-skills-claude/skills/seo-aeo-keyword-research

metadata.json

ORIGIN.md

Problem: The imported workflow feels incomplete during review

Symptoms: Reviewers can see the generated

SKILL.md

Problem: The task drifted into a different specialization

Symptoms: The imported skill starts in the right place, but the work turns into debugging, architecture, design, security, or release orchestration that a native skill handles better. Solution: Use the related skills section to hand off deliberately. Keep the imported provenance visible so the next skill inherits the right context instead of starting blind.

Related Skills

• @00-andruia-consultant-v2

  - Use when the work is better handled by that native specialization after this imported skill establishes context.

• @10-andruia-skill-smith-v2

  - Use when the work is better handled by that native specialization after this imported skill establishes context.

• @20-andruia-niche-intelligence-v2

  - Use when the work is better handled by that native specialization after this imported skill establishes context.

• @2d-games

  - Use when the work is better handled by that native specialization after this imported skill establishes context.

Additional Resources

Use this support matrix and the linked files below as the operator packet for this imported skill. They should reflect real copied source material, not generic scaffolding.

references

references/n/a

examples

examples/n/a

scripts

scripts/n/a

agents

agents/n/a

assets

assets/n/a

Imported Reference Notes

Imported: Additional Resources

• SEO-AEO Engine Repository
• Full Keyword Research SKILL.md

Imported: Common Pitfalls

• Problem: High-volume keyword chosen but impossible to rank for early on Solution: Always cross-check volume with difficulty. Tier 1 should have difficulty under 45.

• Problem: AEO keywords ignored in favour of traditional search terms Solution: AEO keywords drive AI engine citation — include at least 5 in every research run.

Imported: Limitations

• Use this skill only when the task clearly matches the scope described above.
• Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
• Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.