parallel-monitor

Continuously track the web for changes via the Parallel Monitor API. Creates a recurring research task that runs on a cadence and emits events on change — with optional webhook delivery. Use for 'monitor', 'track', 'watch', or 'alert me when' requests.

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Install skill "parallel-monitor" with this command: npx skills add normallygaussian/parallel-monitor

Parallel Monitor

Continuously track the web for changes. A monitor is a recurring research task that runs on a cadence (hourly / daily / weekly / every two weeks) and emits an event each cycle. Optionally deliver events to a webhook.

When to Use

Trigger this skill when the user asks for:

  • "monitor [thing]", "track changes to [thing]", "watch [page/topic]"
  • "alert me when [X] changes / files / launches / posts"
  • "keep an eye on [pricing page / competitor / SEC filings]"
  • Recurring research that should re-run automatically without re-prompting

Use Search for one-off lookups; use Monitor when the user wants ongoing observation.

Quick Start

parallel-cli monitor create "Track price changes for iPhone 16 Pro" --json

CLI Reference

Basic Usage

parallel-cli monitor create "<objective>" [options]
parallel-cli monitor list --json
parallel-cli monitor get mon_xxx --json
parallel-cli monitor update mon_xxx [options] --json
parallel-cli monitor delete mon_xxx
parallel-cli monitor events mon_xxx --json
parallel-cli monitor simulate mon_xxx --json

Common Flags (create / update)

FlagDescription
-c, --cadencehourly, daily (default), weekly, every_two_weeks
--webhook <url>Webhook URL for event delivery (required for simulate)
--output-schema <json>JSON schema for structured event output
--jsonOutput as JSON

Examples

Create a basic monitor (daily cadence):

parallel-cli monitor create "Track new SEC filings from Tesla" --json

Hourly monitor with webhook delivery:

parallel-cli monitor create "New AI funding announcements" \
  --cadence hourly \
  --webhook https://example.com/hooks/funding \
  --json

Structured-output monitor:

parallel-cli monitor create "Track iPhone 16 Pro pricing on apple.com" \
  --output-schema '{"properties":{"price_usd":{"type":"number"},"in_stock":{"type":"boolean"}}}' \
  --json

List existing monitors (default 10):

parallel-cli monitor list --json

Inspect events from a monitor:

parallel-cli monitor events mon_xxx --json

Test webhook delivery without waiting for a real cycle:

parallel-cli monitor simulate mon_xxx --json

(simulate requires a --webhook was set on the monitor; otherwise it errors.)

Update cadence on an existing monitor:

parallel-cli monitor update mon_xxx --cadence weekly --json

Delete a monitor:

parallel-cli monitor delete mon_xxx

Best-Practice Prompting

Objective

Write 1-3 sentences describing:

  • What signal the monitor should look for (e.g., "price changes", "new filings", "site outage")
  • What "change" means (numeric threshold, new entity appearing, status flip)
  • Source preference if relevant (e.g., "from sec.gov", "on the official pricing page")

Cadence

Pick the slowest cadence that still catches the signal in time:

  • hourly — breaking news, pricing fluctuations, status pages
  • daily (default) — most ongoing tracking
  • weekly / every_two_weeks — slow-moving topics, regulatory filings, executive changes

Output Schema (optional)

Provide a JSON schema when you want structured per-event output (e.g., {price_usd, in_stock}). The Monitor API will populate that schema each cycle, making downstream automation easier.

Response Format

monitor create and monitor list return JSON with fields like:

  • monitor_idmon_xxx
  • objective — the natural-language description
  • cadence — current schedule
  • webhook — delivery URL (if set)
  • created_at / updated_at — timestamps
  • last_event_at — most recent event timestamp (if any)

monitor events returns an array of {event_id, observed_at, output} objects.

Output Handling

When relaying monitor results to the user:

  • Always echo the monitor_id so the user can manage the monitor later
  • Default monitor list to -n 10 to avoid megabyte-scale dumps in long-lived workspaces
  • For events output, summarize the trend across cycles, not just the latest event

Running Out of Context?

For long-running monitor management sessions, save state and use sessions_spawn:

parallel-cli monitor list --json -o /tmp/monitors.json

Then spawn a sub-agent:

{
  "tool": "sessions_spawn",
  "task": "Read /tmp/monitors.json and produce a summary of active monitors grouped by cadence.",
  "label": "monitor-summary"
}

Error Handling

Exit CodeMeaning
0Success
1Unexpected error (network, parse)
2Invalid arguments
3API error (non-2xx)

Prerequisites

Requires parallel-cli (installed and authenticated). If parallel-cli --version fails, or if a later command fails with an authentication error, tell the user to see https://docs.parallel.ai/integrations/cli and stop.

References

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