> Subscribe to and scan industry newsletters for buying signals, competitor mentions, ICP pain-point language, and market shifts. Parses incoming newsletter emails via AgentMail, matches against keyword campaigns, and delivers a weekly digest of actionable signals. Use when a marketing team wants to turn newsletter subscriptions into an ongoing intelligence feed without manual reading.
npx skills add https://github.com/gooseworks-ai/goose-skills --skill newsletter-signal-scanner
Turn your newsletter subscriptions into a structured intelligence feed. Monitors an AgentMail inbox for incoming newsletters, extracts signal-relevant content by keyword campaign, and delivers a weekly digest of what matters — competitor mentions, ICP pain language, market shifts, and emerging topics.
sponsored-newsletter-finder to discover others.Save campaign config to the current working directory as newsletter-signals.json (or user-specified path).
{
"inbox_id": "<agentmail_inbox_id>",
"keyword_campaigns": {
"competitors": ["Clay", "Apollo", "Outreach", "Salesloft"],
"pain_language": ["pipeline is down", "outbound isn't working", "SDR ramp"],
"market_shifts": ["AI SDR", "GTM engineer", "agent-led"],
"brand_mentions": ["YourCompany", "yourcompany.com"]
},
"newsletters": [
{"name": "Exit Five", "from_domain": "exitfive.com"},
{"name": "The GTM Newsletter", "from_domain": "gtmnewsletter.com"}
],
"output": {
"format": "markdown",
"path": "newsletter-signals-[DATE].md"
}
}
Use the AgentMail API (agentmail.dev) to fetch new emails from the monitored inbox:
Fetch emails from inbox <inbox_id> since <last_scan_date>
Filter to: known newsletter senders (match against newsletters config)
For each email:
For each newsletter email, scan for keyword matches:
for email in emails:
matches = {}
for campaign, keywords in keyword_campaigns.items():
found = []
for keyword in keywords:
if keyword.lower() in email.body.lower():
# Extract context: 50 chars before + keyword + 50 chars after
context = extract_context(email.body, keyword)
found.append({"keyword": keyword, "context": context})
if found:
matches[campaign] = found
email.signal_matches = matches
Only include emails with at least one keyword match in the digest.
For each matched email, extract clean signal snippets:
Competitor mention example:
> Newsletter: The GTM Newsletter | Date: 2026-03-05
> Campaign: competitors
> Keyword: "Clay"
> Context: "...teams that use Clay for enrichment are seeing 3x better personalization rates compared to..."
Pain language example:
> Newsletter: Exit Five | Date: 2026-03-04
> Campaign: pain_language
> Keyword: "outbound isn't working"
> Context: "...a lot of founders telling me outbound isn't working the way it used to. The reply rates I'm seeing..."
# Newsletter Signal Digest — Week of [DATE]
## Summary
- Newsletters scanned: [N]
- Emails with signals: [N]
- Top trending topic: [topic]
---
## Competitor Mentions
### Clay
- **[Newsletter Name]** — [Date]
> "[Context snippet]"
Source: [email subject] | [URL if available]
### [Other Competitor]
...
---
## ICP Pain Language
Signals suggesting your ICP is feeling pain your product solves:
- **[Newsletter Name]** — [Date]
> "[Context snippet]"
— Relevance: [why this matters]
---
## Market Shift Signals
Emerging topics gaining newsletter coverage:
- **"[Topic]"** — mentioned in [N] newsletters this week
> "[Context snippet]"
---
## Your Brand Mentions
[Any mentions of your company or product]
---
## Recommended Actions
1. [Specific action based on signals — e.g., "Exit Five is covering AI SDR fatigue — good moment to publish our take"]
2. [Competitive response if needed]
Save to the current working directory as newsletter-signals-[YYYY-MM-DD].md (or user-specified path).
For first-time setup, subscribe the AgentMail address to target newsletters:
Run weekly (Monday morning recommended):
# Every Monday at 7am — before the team's standup
0 7 * * 1 python3 run_skill.py newsletter-signal-scanner --client <client-name>
| Component | Cost |
|-----------|------|
| AgentMail inbox | Depends on AgentMail pricing |
| Email parsing + keyword matching | Free (local logic) |
| Total | Near-zero ongoing cost |
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Take gooseworks-ai/newsletter-signal-scanner from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.
The instructions reference pip.
Without those the skill loads but fails at the first command.