Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add shawnla90/gtm-coding-agent --skill reddit-onboardgit clone --depth 1 https://github.com/shawnla90/gtm-coding-agentWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/shawnla90/gtm-coding-agent/reddit-onboard)<a href="https://agentmods.dev/skills/shawnla90/gtm-coding-agent/reddit-onboard"><img src="https://agentmods.dev/badge/skills/shawnla90/gtm-coding-agent/reddit-onboard.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Rogue Agent · line 17 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00082 | $0.01297 |
| Opus 5 | $0.00041 | $0.00648 |
| Sonnet 5 | $0.00016 | $0.00259 |
| Haiku 4.5 | $0.00008 | $0.00130 |
Grade A, and why
reddit-onboard scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 90 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 90 lines · 82 tokens per session scan A b660304cba08
reddit-onboard is a skill published in the GitHub repository shawnla90/gtm-coding-agent (141 stars, last pushed 5d ago), licensed MIT. It adds 82 tokens to every session and 1,297 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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