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My Easy Claude Code Passive Income AI Automation Setup thumbnail

My Easy Claude Code Passive Income AI Automation Setup

All About AI·
5 min read

Based on All About AI's video on YouTube. If you like this content, support the original creators by watching, liking and subscribing to their content.

TL;DR

Create a Claude Code skill (a dedicated skill file) to encapsulate the workflow logic you want to repeat.

Briefing

A practical “set-and-forget” automation loop can turn Claude Code skills into steady, low-effort side income—by running a headless skill on a timer and wiring the results to actions like bug-bounty monitoring or scheduled email reports. The core method is simple: create a Claude Code skill (a Markdown “skill” file), then trigger it repeatedly from the terminal using a `while true` loop that calls `claude-p` with the skill name and sleeps between runs. The payoff is that the same pattern can support very different workflows without needing a complex server or custom scheduler.

For income, one example centers on the Cali market bug bounty program. The system continuously scans for new bug-bounty opportunities on Cali’s prediction markets, checks and claims relevant items in a structured sequence, and sends an email to the appropriate support address when a qualifying bug is found. The transcript gives a rough payout structure—minor bugs around $25, moderate $50, severe $100, with an additional $10 for pre-listing bugs—and describes the setup as fully autonomous. The creator reports earning roughly $100 to $200 per week at times (with variability), while also noting other projects can make smaller amounts or even lose money.

Technically, the automation is built around three pieces. First, a skill file such as `autoc cali` (stored in a skills directory) contains step-by-step logic: checking for front batches, claiming logs, and grouping by event while following a checklist so runs stay consistent. Second, supporting scripts and data flow handle external inputs—like polling for new markets and writing them to a log (e.g., a `new markets` file). Third, an email automation component (a Python file) integrates into the skill so the workflow can notify the right address when conditions are met.

Once the skill exists, the continuous runner is handled with a terminal loop: `while true; do claude-p /<skill-name>; sleep <seconds>; done` (the transcript uses `sleep 60` as the initial test). After each run finishes, the loop waits and triggers the skill again. Timing is adjustable—switching from 60 seconds to 3,600 seconds (one hour) is suggested for a more useful cadence and for running 24/7.

To demonstrate the same pattern beyond bug bounties, the transcript walks through building an “automail” skill that emails the top five Hacker News posts. The workflow: use Claude Code to create a placeholder skill, then implement steps to fetch the top five posts (including URLs) into a `news.json` file and send an email via a Gmail script using a token JSON for authentication. After updating Claude Code settings to allow the required bash commands, the loop is started again with `claude-p /automail` and a sleep interval. The result is repeated email batches, with the transcript showing that the system can trigger again and send multiple emails per run.

Overall, the key insight is that Claude Code skills plus a simple terminal `while` loop can provide reliable, repeatable automation for monitoring opportunities or distributing curated information—without relying on more fragile third-party scheduling changes—so long as permissions and timing are set correctly.

Cornell Notes

Claude Code skills can be run on a timer to automate recurring tasks that can support side income or useful reporting. The method uses a terminal `while true` loop that repeatedly calls `claude-p` with a slash command for a specific skill, then sleeps for a chosen interval (e.g., 60 seconds for testing, 3,600 seconds for hourly runs). One example monitors the Cali market bug bounty program by scanning for new prediction-market bugs, following a checklist of actions (check batches, claim logs, group by event), and emailing a support address when a bug is found. A second example builds an “automail” skill that fetches the top five Hacker News posts into `news.json` and sends them via Gmail using a token JSON. Proper settings permissions are required to let Claude Code run the needed bash commands.

What is the reusable “automation loop” pattern described, and why does it matter?

The pattern is: create a Claude Code skill, then run it continuously from the terminal with `while true; do claude-p /<skill-name>; sleep <seconds>; done`. This matters because it turns a one-off skill into a scheduled, headless workflow. The transcript emphasizes that the timing is adjustable—`sleep 60` for quick testing and `sleep 3600` (3,600 seconds) for hourly execution—so the same skill can run 24/7 with minimal overhead.

How does the Cali bug-bounty example generate notifications?

The Cali workflow is built around an `autoc cali` skill that scans for new Cali prediction-market bug bounty opportunities. Inside the skill, steps follow a structured checklist: check for front batches, claim the log, then group by event. Supporting scripts poll for new markets and write them to a log (e.g., `new markets`). When the skill identifies qualifying items, it triggers an automated email step to the relevant support address (described as something like `support@cali`).

What role do “skills” and supporting files play in keeping runs consistent?

The skill file holds the step-by-step logic (the transcript mentions a checklist and ordering so results are consistent across runs). Supporting files handle external data and actions: a watcher/poller collects new market information, logs it to a file, and a separate Python component handles email sending. This separation makes the terminal loop simple—`claude-p /<skill-name>`—while the skill orchestrates the rest.

How is the Hacker News email automation set up end-to-end?

First, a placeholder skill is generated (e.g., `automail`). Then the skill is implemented with steps: fetch the top five Hacker News posts (including URLs) and write them to `news.json`, then send an email using a Gmail script. Authentication uses a token JSON. When the skill runs, it executes the fetch step and then the send step, producing an email batch containing the top five posts.

Why are settings permissions mentioned as a necessary step?

The transcript notes that Claude Code must be allowed to run the required bash commands. After updating `settings.json` to permit the relevant commands, the loop successfully produces `news.json` and triggers email sending. Without these permissions, the automation won’t be able to execute the underlying scripts.

Review Questions

  1. How does changing the `sleep` interval in the terminal loop affect the behavior of the automation, and what interval is suggested for more practical reporting?
  2. In the Cali bug-bounty workflow, what are the key ordered steps inside the skill and what external data source feeds the scan?
  3. For the Hacker News automail example, what files are produced (e.g., `news.json`) and what credential type is used to send emails?

Key Points

  1. 1

    Create a Claude Code skill (a dedicated skill file) to encapsulate the workflow logic you want to repeat.

  2. 2

    Run the skill headlessly on a schedule using a terminal `while true` loop that calls `claude-p /<skill-name>` and then `sleep` for a chosen number of seconds.

  3. 3

    Use a structured checklist inside the skill (e.g., check batches, claim logs, group by event) to keep repeated runs consistent.

  4. 4

    Feed the skill with external inputs via polling/watchers that write to log files (such as `new markets` or `news.json`).

  5. 5

    Integrate side actions like email sending by adding a Python-based email step that uses a token JSON for authentication.

  6. 6

    Update Claude Code settings to allow the bash commands required by the automation, otherwise the loop may fail silently.

  7. 7

    Adjust cadence for usefulness: test with short intervals (like 60 seconds) and switch to longer intervals (like 3,600 seconds) for ongoing operation.

Highlights

A single terminal loop—`while true; do claude-p /<skill>; sleep <seconds>; done`—turns Claude Code skills into recurring automations.
The Cali bug-bounty system combines polling for new markets, a checklist-driven skill (`front batches` → `claim log` → `group by event`), and automated email alerts.
The Hacker News automail example produces `news.json` with the top five posts and then sends a Gmail report using a token JSON.
Permissions in `settings.json` are required so Claude Code can execute the bash commands used by the automation.

Topics

  • Claude Code Skills
  • Terminal Automation
  • Bug Bounty Monitoring
  • Gmail Email Automation
  • Hacker News Reporting