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 agentmods add skills/mendixlabs/mxcli/analyze-runtimenpx skills add mendixlabs/mxcli --skill analyze-runtimegit clone --depth 1 https://github.com/mendixlabs/mxcliWhat 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 | $0.00068 | $0.02928 |
| Opus 5 | $0.00034 | $0.01464 |
| Sonnet 5 | $0.00014 | $0.00586 |
| Haiku 4.5 | $0.00007 | $0.00293 |
Grade A, and why
analyze-runtime 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 yesterday.
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.
curl -s http://127.0.0.1:8090/prometheus | grep -E 'connectionbus_|handler_requests|sessions_|taskqueue_' How it starts
The opening of the file, as written. The whole thing — 227 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Analyze an App's Runtime Behavior — Logs, Metrics, Traces, Catalog
Overview
When you need to understand what an app actually does at runtime — why a page is slow, which microflow dominates cost, what hits the database, whether an error is network or logic — the signals live in four places. This skill is the procedure for collecting them and, crucially, joining them, because the useful questions cross sources that no single tool answers alone.
| Signal | Where | How you get it |
|---|---|---|
Logs (server stack traces + your LOG output) |
<projectDir>/.mxcli/runtime.log |
mxcli run --local tees it automatically |
| Metrics (throughput, DB counts, sessions, queues) | /prometheus on the admin port |
mxcli run --local --metrics |
| Traces (per-microflow / per-activity spans + timings) | console→runtime.log, or an OTLP collector |
mxcli run --local --trace / --trace-otlp |
| Model shape (activities, complexity, refs, XPath) | .mxcli/catalog.db (SQLite) |
mxcli … "refresh catalog full" then SELECT … FROM CATALOG.* |
When to Use This Skill
- A page/microflow is slow and you need to find where the time goes.
- You want to know which entities/queries the app actually hits, and how often.
- A server-side error shows only a generic dialog in the browser.
- You're profiling and need a flame chart, or want cost correlated with model shape.
Prerequisite: run the app with the fast local loop — see run-local. Everything
below assumes mxcli run --local (add the flags noted per signal).
1. Logs — the first stop for errors
run --local writes the runtime log to <projectDir>/.mxcli/runtime.log (override
--runtime-log, - disables). It carries JVM stdout/stderr and the application
log — server stack traces, your microflow/nanoflow LOG output, and the DB
synchronization counts at startup.
mxcli run --local -p app.mpr
tail -f .mxcli/runtime.log
Gotchas:
- Nanoflow
LOGlands under theClient_Nanoflownode, not the node name you declared — a filter built around microflow node names silently drops it.LOG DEBUGfrom a nanoflow is dropped server-side (browser console only). Seewrite-nanoflows. - A spike in "Executing N database synchronization command(s)" on an unchanged model
is a red flag (see the
create or modifydata-loss class of bug).
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.
- yesterday First seen · 227 lines · 68 tokens per session scan A d2844227fb74
analyze-runtime is a skill published in the GitHub repository mendixlabs/mxcli (115 stars, last pushed 2d ago), licensed Apache-2.0. It adds 68 tokens to every session and 2,928 once invoked, about $0.0003 per session on Opus 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 2026-08-30.
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