create-image-fal
Generate or edit an image via any FAL image model (nano-banana edit, gpt-image, flux, ...), ROUTED THROUGH THE fal-proxy so it bills the Ads agent. image_urls…
Scan an AgentMail inbox for newsletter signals using configurable keyword campaigns. Extracts matched keywords, context snippets, and company mentions from incoming emails. Use for monitoring accounting industry newsletters for buying signals like acquisitions, migrations, and
$ npx -y skills add gooseworks-ai/goose-skills --skill newsletter-monitor --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/newsletter-monitorContext preview
The summary Claude sees to decide when to auto-load this skill.
Scan an AgentMail inbox for newsletter signals using configurable keyword campaigns. Extracts matched keywords, context snippets, and company mentions from incoming emails. Use for monitoring accounting industry newsletters for buying signals like acquisitions, migrations, and
name: newsletter-monitor description: > Scan an AgentMail inbox for newsletter signals using configurable keyword campaigns. Extracts matched keywords, context snippets, and company mentions from incoming emails. Use for monitoring accounting industry newsletters for buying signals like acquisitions, migrations, and staffing news.
Scan an AgentMail inbox for newsletter signals using configurable keyword campaigns. Designed for monitoring accounting industry newsletters for buying signals like acquisitions, Sage Intacct migrations, staffing challenges, and technology adoption.
# Set your API key export AGENTMAIL_API_KEY="your_key_here" # Scan inbox with all campaigns (summary view) python3 skills/newsletter-monitor/scripts/scan_newsletters.py --output summary # Scan specific campaign, last 7 days python3 skills/newsletter-monitor/scripts/scan_newsletters.py --campaign acquisitions --days 7 --output summary # JSON output for downstream processing python3 skills/newsletter-monitor/scripts/scan_newsletters.py --output json --limit 50
pip3 install agentmail python-dotenv
Keyword campaigns are defined in `config/campaigns.json`. Each campaign has a description and a list of keywords for case-insensitive substring matching.
Built-in campaigns:
| Flag | Description | Default | |------|-------------|---------| | `--campaign NAME` | Run only a specific campaign | All campaigns | | `--days N` | Only scan emails from last N days | No limit | | `--keywords "a,b,c"` | Custom keywords (overrides campaigns) | Use campaigns.json | | `--output json\|summary` | Output format | `json` | | `--inbox ADDRESS` | Override inbox address | `AGENTMAIL_INBOX` env or `supergoose@agentmail.to` | | `--limit N` | Max messages to fetch | `100` |
Returns an array of matched messages with:
Human-readable report showing matched emails grouped by campaign with snippets and detected companies.
When newsletter signals are found, chain to:
Put your AI agent on the growth team. Research customers and competitors, analyze what is working, create the next campaign, and learn from the result.
Repo: gooseworks-ai/goose-skills
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