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 OctoPerf/octoperf-claude-plugins --skill octoperf-monitoringgit clone --depth 1 https://github.com/OctoPerf/octoperf-claude-pluginsWrote 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/octoperf/octoperf-claude-plugins/octoperf-monitoring)<a href="https://agentmods.dev/skills/octoperf/octoperf-claude-plugins/octoperf-monitoring"><img src="https://agentmods.dev/badge/skills/octoperf/octoperf-claude-plugins/octoperf-monitoring/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/octoperf/octoperf-claude-plugins/octoperf-monitoring"><img src="https://agentmods.dev/badge/skills/octoperf/octoperf-claude-plugins/octoperf-monitoring.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 | $0.00000 | $0.04356 |
| Opus 5 | $0.00000 | $0.02178 |
| Sonnet 5 | $0.00000 | $0.00871 |
| Haiku 4.5 | $0.00000 | $0.00436 |
Grade A, and why
octoperf-monitoring 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 12d 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 — 317 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Monitoring — watch servers during a load test
Collect infrastructure metrics (OS, database, web/app server, JMX, Prometheus, New Relic, SLA) while a scenario runs, so a slow or failing test can be tied to what the monitored systems were doing. Read this before creating or configuring a monitor.
Mental model
- A monitor (
MonitorConnection) watches one external target — a Linux host, a database, nginx/Tomcat, a JMX endpoint, … — during runs of a project's scenarios. Monitors are project-scoped. - A monitor runs through an agent: the agent opens the connection (SSH / JDBC / JMX / HTTP) to the target and samples counters. Agents are workspace-scoped — pick one from the workspace that owns the monitor's project.
- Reachability is the whole point: the chosen agent must be able to reach
the target (same network, DNS, ports). For a Linux host the agent often runs
on that host (SSH to
localhost); for a database it must reach the JDBC endpoint. An agent that can't reach the target only produces connection errors — that is whatcheck_monitor_connectioncatches. - Credentials are write-only: they are sent when creating a monitor and are
never returned by
get_monitor/list_monitors_by_project.
How a monitor fits a run (why it matters)
You don't attach a monitor to a scenario — it's automatic:
- Every ENABLED monitor of the project is collected on every scenario
run of that project (disable one with
update_monitorto exclude it from runs without deleting it). There is no per-scenario wiring. - Most monitors ship with default counters and default thresholds; a breached threshold raises a monitoring alarm during the run. The SLA monitor is the same mechanism applied to the test's own metrics (response time, error rate) — perf alerts while the test runs.
- The values and alarms show up in the bench report (live and final). Read them
with
get_report_monitors_table_values(one row per connection of the run: its counters, its alarm count, the worst severity),get_report_threshold_alarms(each breach),get_report_textual_monitors(string-valued counters), and the genericget_report_*_valuestools for the numeric curves. - Adding a monitoring chart to a report is an MCP move too, not a UI-only one:
patch_bench_reportaccepts aLineChartReportItemwhose metric is{id: MONITORING, type: NUMBER_COUNTER}filtered onconnectionNameandcounterPath— both are tag valuesget_report_monitors_table_valueshands back ready to use. Seeoctoperf://skills/report-item-editing.
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.
- 12d ago First seen · 317 lines · 0 tokens per session scan A c5ea8d6119ee
octoperf-monitoring is a skill published in the GitHub repository OctoPerf/octoperf-claude-plugins (0 stars, last pushed 5d ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 4,356 tokens. 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 2026-08-31.
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