aeo-recommend

You are generating AI visibility recommendations for the user. This analyzes their latest AEO run data and produces actionable recommendations for improving brand visibility in AI search engines.

Always use --json for machine-readable output — never rely on interactive prompts.

Step 1: Pre-Flight Check

Verify setup exists:

cat .goose-aeo.yml 2>/dev/null || echo "NOT_FOUND"

If .goose-aeo.yml doesn't exist, tell the user: "AEO hasn't been set up yet. Say 'set up AEO' or use /aeo-setup to get started."

If it exists, check the current state:

npx goose-aeo status --json

Show the user a brief summary: company name, number of queries, number of previous runs. If there are no runs, tell the user: "No runs found. Use /aeo-run to run an analysis first."

Step 2: Generate Recommendations

npx goose-aeo recommend --json

This calls the OpenAI API to synthesize analysis data into recommendations. Tell the user it's generating and may take a moment.

Step 3: Present Results

Parse the JSON and present a conversational summary to the user. Do NOT just dump raw JSON. Structure it like this:

Overall Summary:

• Start with the summary paragraph from the response. This gives the big picture of the brand's AI visibility position.

Visibility Gaps: For each gap, explain:

• The topic/theme where the brand is missing
• Which queries are affected
• Which competitors are being mentioned instead
• The specific recommendation

Source Opportunities: For each opportunity, explain:

• Which domain/site is frequently cited by AI engines
• How many times it was cited
• The specific action item for getting featured there

Competitor Insights: For each insight, explain:

• Which competitor is outperforming and in what queries
• Any relevant excerpts showing how they're being mentioned
• What they might be doing differently

Step 4: Offer Next Steps

Based on the recommendations, offer the user these options:

1. "Want me to draft content for any of these gaps?" — If there are visibility gaps around specific topics, offer to create blog posts, landing pages, or FAQ content.
2. "Want me to create a comparison page?" — If competitors are being mentioned instead, offer to draft a vs/comparison page.
3. "Want me to write a guest post pitch for [domain]?" — If there are source opportunities with specific domains, offer to draft an outreach email or guest post pitch.
4. "Want me to update your queries?" — If the recommendations suggest new query angles, offer to add them.
5. "See the dashboard" — Suggest opening npx goose-aeo dashboard for visual exploration.

Error Handling

• If the recommendation generation fails with an API key error, tell the user to check their GOOSE_AEO_OPENAI_API_KEY environment variable.
• If there are no analysis results, suggest running /aeo-run first.
• If the LLM response fails to parse, it will retry automatically. If it still fails, tell the user and suggest trying again.