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Automate Anything with Cron

The daily briefing bot tutorial covers the basics. This guide goes further — five real-world automation patterns you can adapt for your own workflows.

For the full feature reference, see Scheduled Tasks (Cron).

Key Concept

Cron jobs run in fresh agent sessions with no memory of your current chat. Prompts must be completely self-contained — include everything the agent needs to know.

---

Pattern 1: Website Change Monitor

Watch a URL for changes and get notified only when something is different.

The script parameter is the secret weapon here. A Python script runs before each execution, and its stdout becomes context for the agent. The script handles the mechanical work (fetching, diffing); the agent handles the reasoning (is this change interesting?).

Create the monitoring script:

mkdir -p ~/.hermes/scripts

~/.hermes/scripts/watch-site.py

import hashlib, json, os, urllib.request

URL = "https://example.com/pricing"
STATE_FILE = os.path.expanduser("~/.hermes/scripts/.watch-site-state.json")

# Fetch current content
req = urllib.request.Request(URL, headers={"User-Agent": "Hermes-Monitor/1.0"})
content = urllib.request.urlopen(req, timeout=30).read().decode()
current_hash = hashlib.sha256(content.encode()).hexdigest()

# Load previous state
prev_hash = None
if os.path.exists(STATE_FILE):
    with open(STATE_FILE) as f:
        prev_hash = json.load(f).get("hash")

# Save current state
with open(STATE_FILE, "w") as f:
    json.dump({"hash": current_hash, "url": URL}, f)

# Output for the agent
if prev_hash and prev_hash != current_hash:
    print(f"CHANGE DETECTED on {URL}")
    print(f"Previous hash: {prev_hash}")
    print(f"Current hash: {current_hash}")
    print(f"\nCurrent content (first 2000 chars):\n{content[:2000]}")
else:
    print("NO_CHANGE")

Set up the cron job:

/cron add "every 1h" "If the script output says CHANGE DETECTED, summarize what changed on the page and why it might matter. If it says NO_CHANGE, respond with just [SILENT]." --script ~/.hermes/scripts/watch-site.py --name "Pricing monitor" --deliver telegram

The [SILENT] Trick

When the agent's final response contains [SILENT], delivery is suppressed. This means you only get notified when something actually happens — no spam on quiet hours.

---

Pattern 2: Weekly Report

Compile information from multiple sources into a formatted summary. This runs once a week and delivers to your home channel.

/cron add "0 9 * * 1" "Generate a weekly report covering:

1. Search the web for the top 5 AI news stories from the past week
2. Search GitHub for trending repositories in the 'machine-learning' topic
3. Check Hacker News for the most discussed AI/ML posts

Format as a clean summary with sections for each source. Include links.
Keep it under 500 words — highlight only what matters." --name "Weekly AI digest" --deliver telegram

From the CLI:

hermes cron create "0 9 * * 1" \
  "Generate a weekly report covering the top AI news, trending ML GitHub repos, and most-discussed HN posts. Format with sections, include links, keep under 500 words." \
  --name "Weekly AI digest" \
  --deliver telegram

The 0 9 * * 1 is a standard cron expression: 9:00 AM every Monday.

---

Pattern 3: GitHub Repository Watcher

Monitor a repository for new issues, PRs, or releases.

/cron add "every 6h" "Check the GitHub repository NousResearch/hermes-agent for:
- New issues opened in the last 6 hours
- New PRs opened or merged in the last 6 hours
- Any new releases

Use the terminal to run gh commands:
  gh issue list --repo NousResearch/hermes-agent --state open --json number,title,author,createdAt --limit 10
  gh pr list --repo NousResearch/hermes-agent --state all --json number,title,author,createdAt,mergedAt --limit 10

Filter to only items from the last 6 hours. If nothing new, respond with [SILENT].
Otherwise, provide a concise summary of the activity." --name "Repo watcher" --deliver discord

Self-Contained Prompts

Notice how the prompt includes the exact gh commands. The cron agent has no memory of previous runs or your preferences — spell everything out.

---

Pattern 4: Data Collection Pipeline

Scrape data at regular intervals, save to files, and detect trends over time. This pattern combines a script (for collection) with the agent (for analysis).

~/.hermes/scripts/collect-prices.py

import json, os, urllib.request
from datetime import datetime

DATA_DIR = os.path.expanduser("~/.hermes/data/prices")
os.makedirs(DATA_DIR, exist_ok=True)

# Fetch current data (example: crypto prices)
url = "https://api.coingecko.com/api/v3/simple/price?ids=bitcoin,ethereum&vs_currencies=usd"
data = json.loads(urllib.request.urlopen(url, timeout=30).read())

# Append to history file
entry = {"timestamp": datetime.now().isoformat(), "prices": data}
history_file = os.path.join(DATA_DIR, "history.jsonl")
with open(history_file, "a") as f:
    f.write(json.dumps(entry) + "\n")

# Load recent history for analysis
lines = open(history_file).readlines()
recent = [json.loads(l) for l in lines[-24:]]  # Last 24 data points

# Output for the agent
print(f"Current: BTC=${data['bitcoin']['usd']}, ETH=${data['ethereum']['usd']}")
print(f"Data points collected: {len(lines)} total, showing last {len(recent)}")
print(f"\nRecent history:")
for r in recent[-6:]:
    print(f"  {r['timestamp']}: BTC=${r['prices']['bitcoin']['usd']}, ETH=${r['prices']['ethereum']['usd']}")

/cron add "every 1h" "Analyze the price data from the script output. Report:
1. Current prices
2. Trend direction over the last 6 data points (up/down/flat)
3. Any notable movements (>5% change)

If prices are flat and nothing notable, respond with [SILENT].
If there's a significant move, explain what happened." \
  --script ~/.hermes/scripts/collect-prices.py \
  --name "Price tracker" \
  --deliver telegram

The script does the mechanical collection; the agent adds the reasoning layer.

---

Pattern 5: Multi-Skill Workflow

Chain skills together for complex scheduled tasks. Skills are loaded in order before the prompt executes.

# Use the arxiv skill to find papers, then the obsidian skill to save notes
/cron add "0 8 * * *" "Search arXiv for the 3 most interesting papers on 'language model reasoning' from the past day. For each paper, create an Obsidian note with the title, authors, abstract summary, and key contribution." \
  --skill arxiv \
  --skill obsidian \
  --name "Paper digest"

From the tool directly:

cronjob(
    action="create",
    skills=["arxiv", "obsidian"],
    prompt="Search arXiv for papers on 'language model reasoning' from the past day. Save the top 3 as Obsidian notes.",
    schedule="0 8 * * *",
    name="Paper digest",
    deliver="local"
)

Skills are loaded in order — arxiv first (teaches the agent how to search papers), then obsidian (teaches how to write notes). The prompt ties them together.

---

Managing Your Jobs

# List all active jobs
/cron list

# Trigger a job immediately (for testing)
/cron run <job_id>

# Pause a job without deleting it
/cron pause <job_id>

# Edit a running job's schedule or prompt
/cron edit <job_id> --schedule "every 4h"
/cron edit <job_id> --prompt "Updated task description"

# Add or remove skills from an existing job
/cron edit <job_id> --skill arxiv --skill obsidian
/cron edit <job_id> --clear-skills

# Remove a job permanently
/cron remove <job_id>

---

Delivery Targets

The --deliver flag controls where results go:

Target	Example	Use case
origin	--deliver origin	Same chat that created the job (default)
local	--deliver local	Save to local file only
telegram	--deliver telegram	Your Telegram home channel
discord	--deliver discord	Your Discord home channel
slack	--deliver slack	Your Slack home channel
Specific chat	--deliver telegram:-1001234567890	A specific Telegram group
Threaded	--deliver telegram:-1001234567890:17585	A specific Telegram topic thread

---

Tips

Make prompts self-contained. The agent in a cron job has no memory of your conversations. Include URLs, repo names, format preferences, and delivery instructions directly in the prompt.

Use [SILENT] liberally. For monitoring jobs, always include instructions like "if nothing changed, respond with [SILENT]." This prevents notification noise.

Use scripts for data collection. The script parameter lets a Python script handle the boring parts (HTTP requests, file I/O, state tracking). The agent only sees the script's stdout and applies reasoning to it. This is cheaper and more reliable than having the agent do the fetching itself.

Test with /cron run. Before waiting for the schedule to trigger, use /cron run <job_id> to execute immediately and verify the output looks right.

Schedule expressions. Human-readable formats like every 2h, 30m, and daily at 9am all work alongside standard cron expressions like 0 9 * * *.

---

For the complete cron reference — all parameters, edge cases, and internals — see Scheduled Tasks (Cron).