Install
$ agentstack add skill-shawnla90-gtm-coding-agent-reddit-onboard ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ● Environment & secrets Used
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
reddit-onboard
Turns a new signup into a personalized Notion doc that routes them through the public Reddit playbook.
The division of labor: shawnos.ai/reddit is the method, public and free. The Notion doc is their route through it — what to read first, what their real data says, what applies to their market. Never re-explain the playbook in the doc. Link to it.
Inputs
A name, email, or company. Everything else comes from your records.
Before you write a word
Read FACTCHECK.md in this directory. Every rule in it maps to a claim that shipped once and was false. The short version: every number traces to a query, behavioral claims come from raw analytics events rather than derived columns, a narrow proxy never proves a broad claim, platform mechanics get attributed or cut, and a client doc describes what works instead of grading their setup.
Steps
1. Pull their real record
Query your CRM or signup store for the person: name, email, offer description, tracked keywords, tracked subreddits, tier, signup date, first-result date, activity.
> Gotcha: read the primary record, not an enrichment table. Enrichment providers routinely miss small and local operators; a workflow keyed on an enrichment row will report that a real signup does not exist. Read the source table directly.
2. Read their event stream before forming any opinion
Never write about what someone did from a summary row alone. Pull the raw event stream from your product analytics, ordered by timestamp, and read the whole thing before writing a sentence about their behavior.
You are looking for the moment the product worked for them, and what preceded it. That moment is the opening of the doc.
> One trial user's summary row implied their subreddit setup was wrong. The raw stream showed they had added three subs and gotten their first opportunity 19 minutes later. The first draft of the doc would have told them their setup was broken half an hour after it produced their first result. Derived columns lie; events do not.
3. Suggest rings, never verdicts
Compare what they track against their own offer description. Signups often track practitioner subs — rooms where they work — which are genuinely useful for reading competitors and saturation. Say that. Then suggest a second ring where their buyers talk, framed as an experiment to run:
buyer's trade → the business layer → local (only if geography is a real advantage).
Lift the pain in their own words out of their offer description and point out it is a thing people post, not a thing to write copy about.
Never assert a sub's rules, size, or gate you have not checked. Suggest candidates and make them verify. Checking the gate is the skill you're teaching; doing it for them removes the lesson. Never invent names — if you can't verify it, cut it.
4. Write the doc
Structure that works: open with their real result (or the fastest path to a first result), then their two rings, then a reading order through the playbook with deep links, then next experiments. Keep it short; the playbook carries the method.
Hard style rules: no em-dashes, no hedge words, no define-by-negation, no invented anecdotes. State claims directly.
5. Verify the deep links
The doc deep-links shawnos.ai/reddit# sections. Verify every anchor against the live page before shipping — section numbering shifts when sections are added.
Anchors: journey account-ramp karma-engine post-types comments karma-gating link-map the-ask staying-alive ai-citations llmo delegation newsletter
6. Push to Notion
python3 https://github.com/shawnla90/ClearboxGTM/blob/main/scripts/push_notion.py --file doc.md --title " · Reddit for " --parent
Re-publish without breaking a shared URL:
python3 https://github.com/shawnla90/ClearboxGTM/blob/main/scripts/push_notion.py --file doc.md --inplace
Gotchas:
- Token:
NOTION_API_TOKENenv var (or~/.env.notion). - The integration must be shared into the parent page or it 401s.
- Share-to-web is a manual UI toggle. The API can't publish. Flip it yourself.
- Custom markdown:
> 🎯 text→ colored callout,- [ ]→ checkbox,::: bookmark→ card.
Never
- Re-explain the playbook in the doc. Link to it. The page is the method.
- Tell them their setup is wrong. Describe what works and what to try next. If their data shows a result, open with the result.
- Put their event stream in the deliverable. You will know things from their analytics they would not recognize as their own visible result. Use that to decide what to write; reference only what they'd recognize.
- Ship a doc without reading the raw event stream first (step 2).
Related
FACTCHECK.md— the gate. Read it first.shawnos.ai/reddit— the public playbook the doc routes through../clearbox-onboard/— the offer pack that precedes this (form fields done right)https://github.com/shawnla90/ClearboxGTM/blob/main/scripts/push_notion.py— the publish mechanic
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: shawnla90
- Source: shawnla90/gtm-coding-agent
- License: MIT
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.