Files
hermes-agent/website/docs/guides/automate-with-cron.md
Teknium 3db6b9cc87 feat(cron): add no_agent mode for script-only cron jobs (watchdog pattern) (#19709)
* feat(cron): add no_agent mode for script-only cron jobs (watchdog pattern)

Adds a no_agent=True option to the cronjob system. When enabled, the
scheduler runs the attached script on schedule and delivers its stdout
directly to the job's target — no LLM, no agent loop, no token spend.
This is the classic bash-watchdog pattern (memory alert every 5 min,
disk alert every 15 min, CI ping) reimplemented as a first-class Hermes
primitive instead of a systemd timer + curl + bot token triplet living
outside the system.

## What

  hermes cron create "every 5m" \
    --no-agent \
    --script memory-watchdog.sh \
    --deliver telegram \
    --name memory-watchdog

Agent tool:

  cronjob(action='create',
          schedule='every 5m',
          script='memory-watchdog.sh',
          no_agent=True,
          deliver='telegram')

Semantics:
- Script stdout (trimmed) → delivered verbatim as the message
- Empty stdout          → silent tick (no delivery; watchdog pattern)
- wakeAgent=false gate  → silent tick (same gate LLM jobs use)
- Non-zero exit/timeout → delivered as an error alert
                          (broken watchdogs shouldn't fail silently)
- No LLM ever invoked; no tokens spent; no provider fallback applied

## Implementation

cron/jobs.py
  * create_job gains no_agent: bool = False
  * prompt becomes Optional (no_agent jobs don't need one)
  * Validation: no_agent=True requires a script at create time
  * Field roundtrips via load_jobs / save_jobs / update_job

cron/scheduler.py
  * run_job: new short-circuit branch at the top that runs the script,
    wraps its output into the (success, doc, final_response, error)
    tuple downstream delivery already expects, and returns before any
    AIAgent import or construction
  * _run_job_script: picks interpreter by extension — .sh/.bash run
    under /bin/bash, anything else under sys.executable (Python).
    Shell support unlocks the bash-watchdog pattern without wrapping
    scripts in Python. Extension is explicit; we deliberately do NOT
    trust the file's own shebang. Path-containment guard (scripts dir)
    unchanged.

tools/cronjob_tools.py
  * Schema: new no_agent boolean property with clear trigger guidance
  * cronjob() accepts no_agent and validates mode-specific shape:
    - no_agent=True requires script; prompt/skills optional
    - no_agent=False keeps the existing 'prompt or skill required' rule
  * update path rejects flipping no_agent=True on a job without a script
  * _format_job surfaces no_agent in list output
  * Handler lambda forwards no_agent from tool args

hermes_cli/main.py, hermes_cli/cron.py
  * 'hermes cron create --no-agent' and edit's --no-agent / --agent
    pair for toggling at CLI parity with the agent tool
  * Existing --script help text updated to describe both modes
  * List / create / edit output now shows 'Mode: no-agent (...)' when set

## Tests

tests/cron/test_cron_no_agent.py — 18 tests covering:
  * create_job: no_agent shape, validation, field persistence
  * update_job: flag roundtrip across reload
  * cronjob tool: schema validation, update toggling, mode-specific
    requirements, prompt-relaxation rule
  * run_job short-circuit:
    - success path delivers stdout verbatim
    - empty stdout → SILENT_MARKER (no delivery downstream)
    - wakeAgent=false gate → silent
    - script failure → error alert
    - run_job does NOT import AIAgent (verified via mock)
  * _run_job_script:
    - .sh executes via bash (no shebang required)
    - .bash executes via bash
    - .py still runs via sys.executable (regression)
    - path-traversal still blocked (security regression)

All 18 new tests pass. 341/342 pre-existing cron tests still pass; the
one failure (test_script_empty_output_noted) was already broken on main
and is unrelated to this change.

## Docs

website/docs/guides/cron-script-only.md — new dedicated guide covering
the watchdog pattern, interpreter rules, delivery mapping, worked
examples (memory / disk alerts), and the comparison table vs hermes send,
regular LLM cron jobs, and OS-level cron.

website/docs/user-guide/features/cron.md — new 'No-agent mode' section
in the cron feature reference, cross-linked to the guide.

website/docs/guides/automate-with-cron.md — new tip box pointing users
to no-agent mode when they don't need LLM reasoning.

## Compatibility

- Existing jobs: unchanged. no_agent defaults to False, existing code
  paths untouched until the flag is set.
- Schema additive only; older jobs.json without the field load fine
  via .get() with False default.
- New CLI flags are opt-in and don't alter existing flag behavior.

* fix(cron): lazy-import AIAgent + SessionDB so no_agent ticks pay zero

The unconditional `from run_agent import AIAgent` + SessionDB() init at
the top of run_job() meant every no_agent tick still paid the full agent
module load cost (~300ms + transitive imports + DB open) even though it
never touched any of that machinery.

Move both to live under the default (LLM) path, after the no_agent
short-circuit has returned. Now a no_agent tick's sys.modules stays
clean — verified end-to-end:

    assert 'run_agent' not in sys.modules  # before
    run_job(no_agent_job)
    assert 'run_agent' not in sys.modules  # after

The existing mock-based unit test (test_run_job_no_agent_never_invokes_aiagent)
kept passing because patch() replaces the class AFTER import; the leak
was only visible via real subprocess-style verification. End-to-end
demo confirmed: agent calls cronjob(no_agent=True) → script runs →
stdout delivered → no LLM machinery loaded.

* docs(cron): tighten no_agent tool schema — defaults, silent semantics, pick rule

Previous description buried the important bits in one long sentence.
Agents could plausibly miss three things an LLM-facing schema should
make unmissable:

1. What the default is — now first sentence + JSON Schema `default: false`
2. What 'silent run' actually means for the user — now spelled out:
   'nothing is sent to the user and they won't see anything happened'
3. When to pick True vs False — now a concrete decision rule with
   examples on both sides (watchdogs/metrics/pollers → True;
   summarize/draft/pick/rephrase → False)

Also adds explicit 'prompt and skills are ignored when True' since the
agent could otherwise still pass them out of habit.

No behavior change — schema text only.
2026-05-04 12:31:01 -07:00

9.8 KiB

sidebar_position, title, description
sidebar_position title description
11 Automate Anything with Cron Real-world automation patterns using Hermes cron — monitoring, reports, pipelines, and multi-skill workflows

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).

:::info 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. :::

:::tip Don't need the LLM? Use no-agent mode. For recurring watchdogs where the script already produces the exact message you want to send (memory alerts, disk alerts, CI pings, heartbeats), skip the LLM entirely with script-only cron jobs. Zero tokens, same scheduler. :::


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
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

:::tip 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

:::warning 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).

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. Supported formats: relative delays (30m), intervals (every 2h), standard cron expressions (0 9 * * *), and ISO timestamps (2025-06-15T09:00:00). Natural language like daily at 9am is not supported — use 0 9 * * * instead.


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