CodeAlive-AI [YOUR_PRODUCT] Context
Before helping, check MEMORY.md for: brand name, competitors, ICP pain phrases.
Follow output preferences from USER.md.
For chat platforms: bullet-point summary of key findings, not raw data.
Social Listening
Track brand mentions, competitor activity, and industry conversations across the web and social media.
Workflow
Step 1: Web Mentions (Exa)
Search for mentions across blogs, forums, news:
orth run exa /search -d '{"query": "SEARCH_QUERY", "numResults": 20, "contents": {"text": true}}'
Query examples:
- Brand monitoring:
"[YOUR_PRODUCT] reviews feedback 2026" - Competitor tracking:
"[COMPETITOR_A] [PAIN_KEYWORDS]" - Pain signals:
"[PAIN_KEYWORDS your buyers complain about]" - Industry trends:
"[YOUR_CATEGORY] enterprise adoption 2026"
Step 2: Twitter/X Activity (Scrape Creators)
Monitor a company or person's tweets:
orth run scrapecreators /v1/twitter/user-tweets -q handle=TARGET_HANDLE
Search Twitter for mentions:
orth run scrapecreators /v1/twitter/search -q query=SEARCH_TERM
Step 3: LinkedIn Activity (Scrape Creators)
Get company page data:
orth run scrapecreators /v1/linkedin/company -q url=https://linkedin.com/company/COMPANY
Step 4: Extract Insights (ScrapeGraph)
For deep analysis of a specific page found in Steps 1-3:
orth run scrapegraph /v1/smartscraper -d '{"website_url": "URL_FROM_RESULTS", "user_prompt": "Extract sentiment, key complaints, praise, and feature requests about the product"}'
Output Format
Monitoring: [what was searched]
Key findings:
- [finding 1 with source]
- [finding 2 with source]
- [finding 3 with source]
Sentiment: [positive/negative/mixed]
Action items:
- [what to do based on findings]
Monitoring Playbooks
Brand Monitoring
- Exa search:
"BRAND_NAME reviews feedback" - Twitter search: brand mentions
- Summarize sentiment + key themes
Competitor Watch
- Exa search:
"COMPETITOR launch announcement funding" - Twitter: competitor handle tweets
- Analyze what they're shipping and saying
Pain Signal Detection
- Exa search: ICP pain phrases from MEMORY.md
- Twitter search: problem-related keywords
- Identify potential outbound targets
Buyer Language Mining
- Exa search:
"switched from X to Y" OR "looking for alternative to X" - Extract exact phrases buyers use
- Feed into positioning-messaging and cold-email skills
Tips
- Include year in Exa queries for fresh results (e.g., "2026")
- Use Exa
contents.text: trueto get actual content, not just links - Scrape Creators for social, Exa for web — use both for full picture
- Track consistently — set up periodic monitoring, not one-off searches
Related Skills
- signal-scanner — automated buying signal detection (uses social-listening as data source)
- competitor-research — structured competitive analysis with pricing/team
- content-strategy — plan content based on listening findings
- cold-email — write outreach based on pain signals discovered
- exa-company-research — deeper web research on specific companies
- exa-x-search — X/Twitter search via Exa