Agent Pulse

Name: Agent Pulse
Author: jane-o-o-o-o

jane-o-o-o-o/agent-pulse-skills

26.4k installs
1 repo stars
Updated May 28, 2026
jane-o-o-o-o/agent-pulse-skills

agent-pulse is an agent skill that Use Agent Pulse to inspect local AI-agent activity across Hermes, Claude Code, Codex, DeepSeek, OpenClaw, Copilot, Aider, Qwen, OpenCode, Goose, Cursor, Antigra.

About

Use Agent Pulse to inspect local AI-agent activity across Hermes, Claude Code, Codex, DeepSeek, OpenClaw, Copilot, Aider, Qwen, OpenCode, Goose, Cursor, Antigravity, and Amp logs. Use when the user asks about AI-agent sessions, tokens, tool/search calls, model usage, estimated cost, budgets, forecasts, health checks, reports, setup diagnosis, web/API/metrics exports, or MCP integration. --- name: agent-pulse description: Use Agent Pulse to inspect local AI-agent activity across Hermes, Claude Code, Codex, DeepSeek, OpenClaw, Copilot, Aider, Qwen, OpenCode, Goose, Cursor, Antigravity, and Amp logs. Use when the user asks about AI-agent sessions, tokens, tool/search calls, model usage, estimated cost, budgets, forecasts, health checks, reports, setup diagnosis, web/API/metrics exports, or MCP integration. --- # Agent Pulse ## Purpose Use the installed `agent-pulse` CLI as the source of truth for local AI-agent activity. The PyPI package is `agentpulse-cli`, while the command remains `agent-pulse`.

Start with `agent-pulse doctor --json` only when the user asks why data is missing, asks for setup help, or a normal dat
Use JSON output whenever possible. Summarize the fields that matter: sessions, tokens, tools, search calls, model breakd
Use time filters for scoped questions. Default to 24 hours for "recent" and 168 hours for "this week":
Use platform filters when the user asks about a specific agent system:
For cost questions, pair summary, model, and top-session views:

Agent Pulse by the numbers

26,406 all-time installs (skills.sh)
+2,313 installs in the week ending Jul 28, 2026 (Skillselion tracking)
Ranked #38 of 4,386 Backend & APIs skills by installs in the Skillselion catalog
Security screen: LOW risk (skills.sh audit)
Data as of Jul 28, 2026 (Skillselion catalog sync)

At a glance

agent-pulse capabilities & compatibility

Capabilities: start with `agent pulse doctor json` only when · use json output whenever possible. summarize the · use time filters for scoped questions. default t · use platform filters when the user asks about a · for cost questions, pair summary, model, and top
Use cases: documentation

From the docs

What agent-pulse says it does

--- # Agent Pulse ## Purpose Use the installed `agent-pulse` CLI as the source of truth for local AI-agent activity.

SKILL.md

The PyPI package is `agentpulse-cli`, while the command remains `agent-pulse`.

SKILL.md

Prefer running commands and summarizing their output over reading the Agent Pulse source code.

SKILL.md

Start with `agent-pulse doctor --json` only when the user asks why data is missing, asks for setup help, or a normal data command returns no sessions.

SKILL.md

npx skills add https://github.com/jane-o-o-o-o/agent-pulse-skills --skill agent-pulse

Add your badge

Show developers this skill is listed on Skillselion. Paste this into your README.

[![Listed on Skillselion](https://skillselion.com/badge/skills/jane-o-o-o-o/agent-pulse-skills/agent-pulse.svg)](https://skillselion.com/skills/jane-o-o-o-o/agent-pulse-skills/agent-pulse)

Installs	26.4k
repo stars	★ 1
Security audit	3 / 3 scanners passed
Last updated	May 28, 2026
Repository	jane-o-o-o-o/agent-pulse-skills ↗

What problem does agent-pulse solve for developers using this skill?

Who is it for?

Developers who need agent-pulse patterns described in the cached skill documentation.

Skip if: Skip when docs are empty or the task is outside the skill's documented scope.

When should I use this skill?

What you get

Actionable workflows and conventions from SKILL.md for agent-pulse.

JSON usage snapshots
Cost and health reports
Exported HTML metrics

By the numbers

Documents 13 supported -P/--platform source keys
Snapshot helper aggregates 10 metric subcommand areas
SKILL.md maps 7 user-question categories to CLI commands

Files

SKILL.mdMarkdownGitHub ↗

Agent Pulse

Purpose

Use the installed agent-pulse CLI as the source of truth for local AI-agent activity. The PyPI package is agentpulse-cli, while the command remains agent-pulse. Prefer running commands and summarizing their output over reading the Agent Pulse source code.

Always enable UTF-8 on Windows before running commands because Agent Pulse output contains emoji and box drawing:

$env:PYTHONUTF8='1'
$env:PYTHONIOENCODING='utf-8'

If agent-pulse is not on PATH, ask before installing dependencies. If the user approves, install the PyPI package or try running from a local project checkout:

pip install agentpulse-cli

python -m agent_pulse.cli --version

Source Keys

Use -P/--platform when the user asks about one agent tool instead of all local data:

hermes, claude, codex, deepseek, openclaw, copilot, aider, qwen,
opencode, goose, cursor, antigravity, amp

Choose Commands

Use this command selection table first:

User wants	Run
Current status	`agent-pulse status --json`
Full dashboard	`agent-pulse --json` or `agent-pulse --no-banner`
Demo data	`agent-pulse demo --json`
Setup diagnosis	`agent-pulse doctor --json`
Recent sessions	`agent-pulse --json --hours 24 --limit 20`
Top sessions	`agent-pulse top --sort tokens --json`
Top expensive sessions	`agent-pulse top --sort cost --json --hours 168`
Model cost analysis	`agent-pulse models --json`
Model ranking	`agent-pulse leaderboard --json --rank-by efficiency`
Cost savings	`agent-pulse optimize --json`
Budget status	`agent-pulse budget --json`
Cost forecast	`agent-pulse forecast --json`
Cost anomaly check	`agent-pulse anomaly --json`
Health/CI check	`agent-pulse health --json`
Composite score	`agent-pulse score --json`
Search sessions	`agent-pulse search "<query>" --json`
Compare periods	`agent-pulse compare --json`
Compare projects	`agent-pulse compare-projects --json`
Activity calendar	`agent-pulse heatmap --json`
Smart recommendations	`agent-pulse insights --json`
Prometheus metrics	`agent-pulse metrics --format prometheus`
Export report	`agent-pulse export -f markdown` or `agent-pulse export-html`
Web dashboard	`agent-pulse web --port 8765`
REST API	`agent-pulse api --port 8766`
MCP tools	`agent-pulse mcp --list-tools`

If the installed command lacks an option, run agent-pulse <command> --help and adapt.

Workflow

1. Start with agent-pulse doctor --json only when the user asks why data is missing, asks for setup help, or a normal data command returns no sessions. 2. Use JSON output whenever possible. Summarize the fields that matter: sessions, tokens, tools, search calls, model breakdown, source breakdown, estimated cost, warnings. 3. Use time filters for scoped questions. Default to 24 hours for "recent" and 168 hours for "this week":

agent-pulse status --json --hours 24
agent-pulse --json --hours 168 --limit 50

4. Use platform filters when the user asks about a specific agent system:

agent-pulse --json -P codex --hours 24
agent-pulse --json -P claude --hours 24
agent-pulse top --json -P aider --sort cost
agent-pulse status --json -P cursor

5. For cost questions, pair summary, model, and top-session views:

agent-pulse status --json --hours 24
agent-pulse models --json --hours 24
agent-pulse top --sort cost --json --hours 24
agent-pulse optimize --json --hours 168

6. For trend and risk questions, use forecast/history/compare/anomaly:

agent-pulse forecast --json
agent-pulse history --json
agent-pulse compare --json
agent-pulse anomaly --json

7. For setup, use the discovery commands before guessing paths:

agent-pulse doctor --json
agent-pulse scan --json --details
agent-pulse config show

Interpreting Results

Treat total_cost_usd as an estimate based on Agent Pulse's local model pricing table.
Report both cost and token volume; low-cost models can still have very high token usage.
Distinguish sources such as codex, claude, hermes, deepseek, openclaw, aider, cursor, opencode, and goose.
Mention if doctor reports missing optional sources, missing dev_root, or optional web dependencies.
If no sessions appear, check doctor, then try a wider time window such as --hours 168.
Check whether the user asked for a source (-P) filter, a model filter, or a project comparison before giving overall totals.
If a command emits plain text instead of JSON or fails because an installed version is older, run agent-pulse <command> --help and use the closest supported option.

Reports

For a short human-readable answer, run JSON commands and summarize.

For artifacts, prefer:

agent-pulse report --period daily
agent-pulse export -f markdown
agent-pulse export-html

Do not invent exact savings or costs. Use the CLI output.

Integrations

Use the web and API extras only when the user asks for a browser dashboard or programmatic server. Ask before installing missing extras:

pip install "agentpulse-cli[web]"
agent-pulse web --port 8765
agent-pulse api --port 8766

For monitoring pipelines:

agent-pulse metrics --format prometheus
agent-pulse health --cost-limit 100 --token-limit 1000000 --json

MCP

Use MCP mode when the user wants other AI clients to query Agent Pulse:

agent-pulse mcp --list-tools
agent-pulse mcp

When explaining MCP, mention that it exposes tools such as status, forecast, top sessions, model analytics, optimization, health, search, and leaderboard.

Local Helper

This skill includes scripts/run_agent_pulse_snapshot.py, which runs a compact set of JSON-friendly Agent Pulse checks and prints a combined summary:

python scripts/run_agent_pulse_snapshot.py --hours 24 --days 7

interface:
  display_name: "Agent Pulse"
  short_description: "Inspect AI-agent sessions, tokens, model costs, and health."
  default_prompt: "Use $agent-pulse to summarize my recent AI-agent sessions, token usage, model costs, health, and forecast."

"""Run a compact Agent Pulse usage snapshot."""

from __future__ import annotations

import argparse
import json
import os
import shutil
import subprocess
import sys


def command_base() -> list[str]:
    if shutil.which("agent-pulse"):
        return ["agent-pulse"]
    return [sys.executable, "-m", "agent_pulse.cli"]


def run(args: list[str], timeout: int) -> dict:
    env = os.environ.copy()
    env.setdefault("PYTHONUTF8", "1")
    env.setdefault("PYTHONIOENCODING", "utf-8")
    cmd = command_base() + args
    try:
        proc = subprocess.run(
            cmd,
            text=True,
            stdout=subprocess.PIPE,
            stderr=subprocess.STDOUT,
            env=env,
            check=False,
            timeout=timeout,
        )
    except subprocess.TimeoutExpired as exc:
        raw_output = (exc.stdout or "").strip() if isinstance(exc.stdout, str) else ""
        return {
            "command": " ".join(cmd),
            "exit_code": None,
            "timed_out": True,
            "timeout_seconds": timeout,
            "output": raw_output or f"Command timed out after {timeout} seconds.",
        }

    raw = proc.stdout.strip()
    parsed = None
    if raw:
        try:
            parsed = json.loads(raw)
        except json.JSONDecodeError:
            parsed = raw
    return {"command": " ".join(cmd), "exit_code": proc.returncode, "timed_out": False, "output": parsed}


def main() -> int:
    parser = argparse.ArgumentParser(description="Run a compact Agent Pulse JSON snapshot.")
    parser.add_argument("--hours", type=int, default=24, help="Recent activity window in hours.")
    parser.add_argument("--days", type=int, default=7, help="Trend/insight window in days.")
    parser.add_argument("--limit", type=int, default=10, help="Top-session limit.")
    parser.add_argument(
        "--command-timeout",
        type=int,
        default=20,
        help="Timeout in seconds for each Agent Pulse subcommand.",
    )
    args = parser.parse_args()

    hours = str(args.hours)
    days = str(args.days)
    limit = str(args.limit)
    trend_hours = str(args.days * 24)
    timeout = args.command_timeout

    snapshot = {
        "doctor": run(["doctor", "--json"], timeout),
        f"status_{args.hours}h": run(["status", "--json", "--hours", hours], timeout),
        "top_cost": run(
            ["top", "--sort", "cost", "--json", "--hours", trend_hours, "--limit", limit],
            timeout,
        ),
        "models": run(["models", "--json", "--hours", trend_hours], timeout),
        "leaderboard": run(["leaderboard", "--json", "--hours", trend_hours], timeout),
        "forecast": run(["forecast", "--json", "--days", days], timeout),
        "health": run(["health", "--json"], timeout),
        "score": run(["score", "--json", "--hours", trend_hours], timeout),
        "budget": run(["budget", "--json"], timeout),
        "insights": run(["insights", "--json", "--days", days], timeout),
    }
    print(json.dumps(snapshot, indent=2, ensure_ascii=False))
    return 0


if __name__ == "__main__":
    raise SystemExit(main())

Related skills

Lark Openapi ExplorerInstantly explore, test, and generate calls against the full Lark (Feishu) OpenAPI surface without leaving their agent workflow.471k

Lark EventConsume real-time events from Lark/Feishu as structured NDJSON streams inside AI agent workflows.382k15.8k

Lark Openapi ExplorerWhen an existing Lark/Feishu skill or CLI command cannot fulfill a specific requirement and they need to discover and invoke the exact native OpenAPI endpoint.381k15.8k

Just ScrapeQuickly search, crawl, extract structured JSON, or monitor web pages without writing custom scraping code.245k37

Lark AppsQuery the current visibility and permission scope of a Lark (Feishu) app without writing HTTP client code.230k15.8k

SupabaseGet accurate, up-to-date Supabase implementation guidance across database, auth, realtime, storage, edge functions and vector search without relying on outd182k2.4k

How it compares

Use agent-pulse for local coding-agent session and cost telemetry; use cloud APM tools when monitoring deployed application runtime instead of IDE agent logs.

Agent Pulse

About

Agent Pulse by the numbers

agent-pulse capabilities & compatibility

What agent-pulse says it does

Add your badge

What problem does agent-pulse solve for developers using this skill?

Who is it for?

When should I use this skill?

What you get

By the numbers

Files

Agent Pulse

Purpose

Source Keys

Choose Commands

Workflow

Interpreting Results

Reports

Integrations

MCP

Local Helper

Related skills

How it compares

FAQ

What does agent-pulse do?

When should I use agent-pulse?

Is agent-pulse safe to install?

About

Agent Pulse by the numbers

agent-pulse capabilities & compatibility

What agent-pulse says it does

Add your badge

What problem does agent-pulse solve for developers using this skill?

Who is it for?

When should I use this skill?

What you get

By the numbers

Files

Agent Pulse

Purpose

Source Keys

Choose Commands

Workflow

Interpreting Results

Reports

Integrations

MCP

Local Helper

Related skills

How it compares

FAQ

What does agent-pulse do?

When should I use agent-pulse?

Is agent-pulse safe to install?

This week in AI coding