Claude Skill

live-watch

Polls the Agent Monitor /api/stats endpoint several times over a short window and reports the live deltas in active_sessions, active_agents, events_today, and ws_connections so you can see activity moving in real time. Use when watching the dashboard for live changes rather than

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hoangsonww/claude-code-agent-monitor 1014 238 forks MIT Updated 1d ago

Part of hoangsonww/claude-code-agent-monitor — 86 skills

Install

skills CLI

npx skills add https://github.com/hoangsonww/Claude-Code-Agent-Monitor/tree/master/plugins/ccam-dashboard/skills/live-watch

Claude Code

claude plugin marketplace add https://llmmart.ai/marketplace.json && claude plugin install hoangsonww-claude-code-agent-monitor@llmmart

Git git clone https://github.com/hoangsonww/Claude-Code-Agent-Monitor.git

The skills CLI installs just this skill, for any of its supported agents. Claude Code installs the whole hoangsonww/claude-code-agent-monitor collection as a plugin from our marketplace. Git is the plain clone.

Skill manifest

Live Watch

Watch the dashboard's live counters change over a short window by polling /api/stats a few times and reporting the deltas.

Input

The user provides: $ARGUMENTS

Interpreted as the watch shape: number of polls and/or interval (e.g. 5x3s = 5 samples 3 seconds apart). Defaults when empty: 5 samples, ~3 seconds apart (a ~15-second window). A bare number means that many samples at the default interval; a bare duration means the default sample count at that interval.

Data Sources

Endpoint	Returns
`GET /api/stats` (polled)	`{ total_sessions, active_sessions, active_agents, total_agents, total_events, events_today, ws_connections, agents_by_status, sessions_by_status }`

Method

Poll GET /api/stats once per interval for the configured number of samples, recording the timestamp and the four watched counters each time. Pace the polls with a short wait between requests; keep the total window short (seconds, not minutes) so it stays interactive.

If the very first poll fails to connect, the dashboard is down — stop and tell the user to start it with npm start (or npm run dev) from the repo root, then retry.

Report Sections

1. Watch Window

State the sample count, interval, and total elapsed window.

2. Sample Timeline

A Markdown table — one row per poll — with columns: #, time, active_sessions, active_agents, events_today, ws_connections.

3. Deltas

For each of the four watched counters, report the net change from the first to the last sample using ▲ (increase), ▼ (decrease), or = (no change). Note any mid-window spikes or dips visible in the timeline.

4. Verdict

One line: is the dashboard actively receiving traffic (counters moving) or idle (flat) over the window?

Output

Compact Markdown. The timeline table is the centerpiece.
Cite real values from each poll — never interpolate or invent samples.
Deltas use ▲/▼/= with the signed numeric change, e.g. events_today: ▲ +7.
Keep it scannable in a terminal — no padding beyond the table.

Files (claude-code-agent-monitor)

agents

openai.yaml 258 B

interface:
  display_name: "Live Watch"
  short_description: "Polls the Agent Monitor /api/stats endpoint several times..."
  default_prompt: "Use $live-watch to inspect CCAM data and complete this workflow safely."
policy:
  allow_implicit_invocation: true

SKILL.md 2.4 KB

---
name: live-watch
description: >
  Polls the Agent Monitor /api/stats endpoint several times over a short window
  and reports the live deltas in active_sessions, active_agents, events_today,
  and ws_connections so you can see activity moving in real time. Use when
  watching the dashboard for live changes rather than a one-time snapshot.
---

# Live Watch

Watch the dashboard's live counters change over a short window by polling
`/api/stats` a few times and reporting the deltas.

## Input

The user provides: **$ARGUMENTS**

Interpreted as the watch shape: number of polls and/or interval (e.g. `5x3s` =
5 samples 3 seconds apart). Defaults when empty: **5 samples, ~3 seconds apart**
(a ~15-second window). A bare number means that many samples at the default
interval; a bare duration means the default sample count at that interval.

## Data Sources

| Endpoint | Returns |
|----------|---------|
| `GET /api/stats` (polled) | `{ total_sessions, active_sessions, active_agents, total_agents, total_events, events_today, ws_connections, agents_by_status, sessions_by_status }` |

## Method

Poll `GET /api/stats` once per interval for the configured number of samples,
recording the timestamp and the four watched counters each time. Pace the polls
with a short wait between requests; keep the total window short (seconds, not
minutes) so it stays interactive.

If the very first poll fails to connect, the dashboard is down — stop and tell
the user to start it with `npm start` (or `npm run dev`) from the repo root,
then retry.

## Report Sections

### 1. Watch Window
State the sample count, interval, and total elapsed window.

### 2. Sample Timeline
A Markdown table — one row per poll — with columns:
`#`, `time`, `active_sessions`, `active_agents`, `events_today`, `ws_connections`.

### 3. Deltas
For each of the four watched counters, report the net change from the first to
the last sample using ▲ (increase), ▼ (decrease), or `=` (no change). Note any
mid-window spikes or dips visible in the timeline.

### 4. Verdict
One line: is the dashboard actively receiving traffic (counters moving) or idle
(flat) over the window?

## Output

- Compact Markdown. The timeline table is the centerpiece.
- Cite real values from each poll — never interpolate or invent samples.
- Deltas use ▲/▼/= with the signed numeric change, e.g. `events_today: ▲ +7`.
- Keep it scannable in a terminal — no padding beyond the table.