Analyze Claude Code usage trends over time using the Agent Monitor's analytics API — daily session counts, daily event counts, token volumes by type, model distribution, tool usage rankings, and…

MITAuto-check passed

Install Usage Trends

skills CLI
$ npx skills add hoangsonww/Claude-Code-Agent-Monitor --skill usage-trends -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install hoangsonww/Claude-Code-Agent-Monitor usage-trends --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/hoangsonww/Claude-Code-Agent-Monitor.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/ccam-analytics/skills/usage-trends .claude/skills/usage-trends && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
usage-trends
GitHub stars
1.1k
Token cost
~843 tokens
SKILL.md length
259 words
Files
2
Skills in repo
78
Repo updated
First seen
Licence
MIT

At a glance

Analyze Claude Code usage trends over time using the Agent Monitor's analytics API — daily session counts, daily event counts, token volumes by type, model distribution, tool usage rankings, and…

  • Works in 6 steps: Daily Activity Trend → Token Volume Trends → Tool Usage Ranking → …
  • SKILL.md covers Input, Data Sources, Trend Analyses to Produce and Output
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Usage Trends is an agent skill from hoangsonww/Claude-Code-Agent-Monitor. Analyze Claude Code usage trends over time using the Agent Monitor's analytics API — daily session counts, daily event counts, token volumes by type, model distribution, tool usage rankings, and agent/event type distributions across 365-day retention windows.

Its SKILL.md is about 840 tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files (for example `agents/openai.yaml`).

The repository describes itself as: 🚀 A real-time monitoring dashboard for Claude Code & Codex, built with SQLite3, Node.js, Express, React, Vite, TailwindCSS, & WebSockets. It tracks sessions, agent activity… The licence is MIT.

Example prompts

  • “/usage-trends”

Workflow steps

6 steps, taken from the step headings in SKILL.md.

  1. Daily Activity Trend
  2. Token Volume Trends
  3. Tool Usage Ranking
  4. Model Distribution
  5. Session Health Distribution
  6. Event Type Distribution

What it can do on your machine

Read from SKILL.md and the folder at commit 1a10d68. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are json).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Usage Trends loads about 843 tokens when it runs. Until then it costs about 68 tokens; SKILL.md has 259 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~68
When it runs · the whole SKILL.md, loaded when a task matches
~843

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from hoangsonww/Claude-Code-Agent-Monitor at commit 1a10d68, republished under its MIT licence (© hoangsonww). 259 words, ~843 tokens.

Download SKILL.mdSave it as .claude/skills/usage-trends/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
usage-trends
description
Analyze Claude Code usage trends over time using the Agent Monitor's analytics API — daily session counts, daily event counts, token volumes by type, model distribution, tool usage rankings, and agent/event type distributions across 365-day retention windows.

Analyze usage patterns and trends from the Agent Monitor analytics data.

Input

The user provides: $ARGUMENTS

Options: "last 7 days", "last 30 days", "last quarter", "peak hours", "tool trends", "model usage".

Data Sources

EndpointReturns
GET /api/analyticsComprehensive analytics object (see schema below)
GET /api/stats{ total_sessions, active_sessions, active_agents, total_agents, total_events, events_today, ws_connections, agents_by_status, sessions_by_status }
GET /api/sessions?limit=200Full session records with timestamps and metadata
Analytics response schema (GET /api/analytics)
json
{
  "overview": { "total_sessions", "active_sessions", "active_agents", "total_agents", "total_events" },
  "tokens": {
    "total_input": N, "total_output": N,
    "total_cache_read": N, "total_cache_write": N
  },
  "tool_usage": [{ "tool_name": "...", "count": N }],  // top 20
  "daily_events": [{ "date": "YYYY-MM-DD", "count": N }],  // 365 days
  "daily_sessions": [{ "date": "YYYY-MM-DD", "count": N }],  // 365 days
  "agent_types": [{ "subagent_type": "task"|"explore"|null, "count": N }],
  "event_types": [{ "event_type": "PreToolUse"|"PostToolUse"|..., "count": N }],
  "avg_events_per_session": N,
  "total_subagents": N,
  "sessions_by_status": { "active": N, "completed": N, "error": N, "abandoned": N },
  "agents_by_status": { "working": N, "completed": N, "error": N, ... }
}

Trend Analyses to Produce

1. Daily Activity Trend

Plot daily_sessions and daily_events for the requested period. Compute:

  • Average sessions/day and events/day
  • Week-over-week delta (%)
  • Peak day and quietest day

From analytics tokens (baselines are pre-summed into totals at the DB level):

  • Total tokens: total_input, total_output, total_cache_read, total_cache_write
  • Cache efficiency over time: total_cache_read / (total_cache_read + total_input) — trending up = improving
  • Output intensity: total_output / total_input ratio — high = Claude is verbose
3. Tool Usage Ranking

From tool_usage (top 20 tools by event count):

  • Bar chart data (tool name → count)
  • Tool diversity: unique tools used
  • Subagent spawns: count of "Agent" tool uses (each = a subagent launched)
4. Model Distribution

From agent_types + per-session model field:

  • Which models are used most frequently
  • Subagent type distribution: main (null) vs task vs explore vs code-review
5. Session Health Distribution

From sessions_by_status:

  • Completion rate: completed / total × 100
  • Error rate: error / total × 100
  • Abandoned rate: abandoned / total × 100
6. Event Type Distribution

From event_types:

  • PreToolUse/PostToolUse ratio (should be ~1:1; gap = tools failing)
  • Compaction frequency relative to session count
  • APIError count (quota hits, rate limits, overloaded)

Output

Markdown with tables and ASCII trend indicators (▲▼→). Include period comparison when applicable.

© hoangsonww, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file in plugins/ccam-analytics/skills/usage-trends of hoangsonww/Claude-Code-Agent-Monitor.

  • SKILL.md
  • agents/openai.yaml

Open the folder on GitHubat commit 1a10d68

Compare with similar skills

Usage Trends next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Usage Trends compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Usage Trends this skillhoangsonww/Claude-Code-Agent-Monitor1.1k—~843Automated safety check: PassMIT
Qdrant Monitoringgithub/awesome-copilot40k1 repos~276Automated safety check: PassMIT
Monitoring Capture ServicePostHog/posthog40k—~5kAutomated safety check: PassCustom licence
Monitoring Ingestion PipelinePostHog/posthog40k—~9.1kAutomated safety check: PassCustom licence
Agent Performance Monitorruvnet/ruflo74k2 repos~4.9kAutomated safety check: PassMIT
Monitor Streamruvnet/ruflo74k—~188Automated safety check: PassMIT

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Questions about Usage Trends

What does Usage Trends do?

Analyze Claude Code usage trends over time using the Agent Monitor's analytics API — daily session counts, daily event counts, token volumes by type, model distribution, tool usage rankings, and…. Usage Trends is an agent skill from hoangsonww/Claude-Code-Agent-Monitor. Analyze Claude Code usage trends over time using the Agent Monitor's analytics API — daily session counts, daily event counts, token volumes by type, model distribution, tool usage rankings, and agent/event type distributions across 365-day retention windows.

How do I install Usage Trends in Claude Code?

Run `npx skills add hoangsonww/Claude-Code-Agent-Monitor --skill usage-trends -a claude-code`. Or copy the skill folder (plugins/ccam-analytics/skills/usage-trends in hoangsonww/Claude-Code-Agent-Monitor) into .claude/skills/usage-trends in your project. Claude Code loads it when a task matches its description.

How do I install Usage Trends in Codex?

Run `npx skills add hoangsonww/Claude-Code-Agent-Monitor --skill usage-trends -a codex`. Or copy the skill folder (plugins/ccam-analytics/skills/usage-trends in hoangsonww/Claude-Code-Agent-Monitor) into .agents/skills/usage-trends in your project. Codex loads it when a task matches its description.

Can I use Usage Trends in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add hoangsonww/Claude-Code-Agent-Monitor --skill usage-trends -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/usage-trends, .gemini/skills/usage-trends, .github/skills/usage-trends and .opencode/skills/usage-trends in your project.

What does Usage Trends need to run?

SKILL.md names no scripts, command-line tools or credentials: Usage Trends is instructions for the agent only.

Does Usage Trends access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Usage Trends safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Usage Trends use?

Usage Trends is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Usage Trends use?

About 843 tokens (SKILL.md is roughly 3.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Usage Trends?

Skills that share tags, products or a category with Usage Trends: Qdrant Monitoring (github/awesome-copilot, 40k stars), Monitoring Capture Service (PostHog/posthog, 40k stars), Monitoring Ingestion Pipeline (PostHog/posthog, 40k stars) and Agent Performance Monitor (ruvnet/ruflo, 74k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Usage Trends?

hoangsonww (a GitHub user) maintains it in hoangsonww/Claude-Code-Agent-Monitor, which has 1,054 GitHub stars. The repository holds 78 skills in this directory. The repository was last updated on October 8, 2026.

Source: hoangsonww/Claude-Code-Agent-Monitor on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.