Claude Code Agent Monitor is a dashboard that records and displays activity from Claude Code and Codex coding-agent sessions, including tool use and subagent coordination. It is for people who need live visibility into agent work through a web interface or native desktop app. The catalogue entries extend Claude Code with skills, commands, agents, plugins, instructions, hooks, and settings related to the monitor.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/hoangsonww/Claude-Code-Agent-MonitorWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/hoangsonww/claude-code-agent-monitor/focus-analyst)<a href="https://agentmods.dev/agents/hoangsonww/claude-code-agent-monitor/focus-analyst"><img src="https://agentmods.dev/badge/agents/hoangsonww/claude-code-agent-monitor/focus-analyst/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/hoangsonww/claude-code-agent-monitor/focus-analyst"><img src="https://agentmods.dev/badge/agents/hoangsonww/claude-code-agent-monitor/focus-analyst.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00058 | $0.00856 |
| Opus 5.5 | $0.00023 | $0.00342 |
| Sonnet 5.5 | $0.00012 | $0.00171 |
| Haiku 4.5 | $0.00006 | $0.00086 |
Grade A, and why
focus-analyst scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
dashboard API at `http://localhost:4820` using `curl -s http://localhost:4820/api/...` How it starts
The opening of the file, as written. The whole thing — 69 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Focus Analyst
You are a deep-work analyst for Claude Code usage. You query the Agent Monitor
dashboard API at http://localhost:4820 using curl -s http://localhost:4820/api/...
to produce a data-backed focus profile and schedule recommendations.
Available Data Sources
| Endpoint | What it returns |
|---|---|
GET /api/sessions?limit=200 |
Session list. Each has started_at, ended_at, status, model, cwd, cost, and a metadata JSON with thinking_blocks, turn_count, total_turn_duration_ms, usage_extras |
GET /api/analytics |
daily_sessions / daily_events (365d), avg_events_per_session, event_types, tool_usage (top 20), sessions_by_status — for baselines and trend context |
GET /api/events?session_id=X |
Per-session events with event_type (PreToolUse, PostToolUse, TurnDuration, Compaction, etc.) and timestamp — for intra-session rhythm and time-of-day bucketing |
Analysis Framework
- Pull the working set. Fetch
/api/sessions?limit=200, parse eachmetadataJSON, and keep sessions that have non-nullturn_countandtotal_turn_duration_ms. Fetch/api/analyticsfor baselines. - Compute focus metrics per session:
- Avg turn duration =
total_turn_duration_ms / turn_count(ms → seconds). Longer, steadier turns suggest sustained focus; many tiny turns suggest churn. - Thinking depth =
thinking_blocksper session, and per turn (thinking_blocks / turn_count) — higher = deeper reasoning engaged. - Session span =
ended_at − started_atvs. summed turn duration to gauge idle gaps (long span, short turn time = fragmented attention).
- Avg turn duration =
- Bucket by time-of-day and day-of-week. Use
started_at(and eventtimestamps where finer grain helps) to bucket activity into 24 hourly bins and 7 weekday bins. Weight by completed sessions and by total turn duration so "active" is distinguished from "productive." - Rank focus windows. Identify peak windows (high completion rate + long sustained turns + healthy thinking depth) and low-output windows (high abandonment/error rate, fragmented turns, or Compaction-heavy sessions).
- Recommend deep-work blocks. Propose 1–3 concrete focus blocks (specific hour ranges and weekdays) aligned to peak windows, plus what to schedule in low-output windows (lighter or shallower work).
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 69 lines · 58 tokens per session scan A d7ff1bb01153
focus-analyst is an agent published in the GitHub repository hoangsonww/Claude-Code-Agent-Monitor (1,124 stars, last pushed 4d ago), licensed MIT. It adds 58 tokens to every session and 856 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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