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.
npx skills add hoangsonww/Claude-Code-Agent-Monitor --skill benchmarkgit 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/skills/hoangsonww/claude-code-agent-monitor/benchmark)<a href="https://agentmods.dev/skills/hoangsonww/claude-code-agent-monitor/benchmark"><img src="https://agentmods.dev/badge/skills/hoangsonww/claude-code-agent-monitor/benchmark/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/skills/hoangsonww/claude-code-agent-monitor/benchmark"><img src="https://agentmods.dev/badge/skills/hoangsonww/claude-code-agent-monitor/benchmark.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00076 | $0.00818 |
| Opus 5.5 | $0.00030 | $0.00327 |
| Sonnet 5.5 | $0.00015 | $0.00164 |
| Haiku 4.5 | $0.00008 | $0.00082 |
Grade A, and why
benchmark scanned grade A with 0 findings 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 68 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Benchmark
Score a session against the rolling population average and report its percentile on cost, tokens, tool count, and complexity using Agent Monitor data.
Input
The user provides: $ARGUMENTS
This may be:
- A single session ID — benchmark that session
- "latest" — benchmark the most recent session
- "latest N" — benchmark the N most recent sessions, each vs the average
- empty — benchmark the most recent session (default)
Data Sources
| Endpoint | Returns |
|---|---|
GET /api/sessions?limit=N |
Population of sessions with cost, model, started_at, metadata (turn_count, total_turn_duration_ms) — builds the rolling baseline |
GET /api/pricing/cost/{sessionId} |
{ total_cost, breakdown:[{ input_tokens, output_tokens, cache_read_tokens, cache_write_tokens, cost }] } — the target session's cost and tokens |
GET /api/workflows/{sessionId} |
complexity (score), stats (tool/event counts), toolFlow (distinct tools used) — the target session's tool count and complexity |
GET /api/analytics |
avg_events_per_session, tool_usage, daily_sessions — corroborates population-level averages |
Report Sections
1. Build the Baseline
Fetch the population with GET /api/sessions?limit=200 (the rolling set). For each
session gather cost (GET /api/pricing/cost/{id} or the list cost field), total
tokens (sum of the 4 token types from the pricing breakdown), tool count and
complexity (GET /api/workflows/{id}). Compute mean, median, and standard
deviation for each metric across the population.
2. Measure the Target
For the requested session, pull the same four metrics:
- Cost —
total_costfromGET /api/pricing/cost/{id}. - Total tokens —
input + output + cache_read + cache_writesummed from the breakdown. - Tool count — distinct/total tools from
GET /api/workflows/{id}stats/toolFlow. - Complexity score —
complexity.scorefromGET /api/workflows/{id}.
3. Percentile and Deviation
For each metric report the target's percentile within the population (share of
sessions at or below it) and its z-score (value − mean) / stddev. Label each:
below average / typical / above average / outlier (|z| > 2).
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 68 lines · 76 tokens per session scan A 0c41d3188c78
benchmark is a skill published in the GitHub repository hoangsonww/Claude-Code-Agent-Monitor (1,121 stars, last pushed 3d ago), licensed MIT. It adds 76 tokens to every session and 818 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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