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 jabrena/plinth --skill 182-java-observability-metrics-micrometergit clone --depth 1 https://github.com/jabrena/plinthWrote 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/jabrena/plinth/182-java-observability-metrics-micrometer)<a href="https://agentmods.dev/skills/jabrena/plinth/182-java-observability-metrics-micrometer"><img src="https://agentmods.dev/badge/skills/jabrena/plinth/182-java-observability-metrics-micrometer/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/jabrena/plinth/182-java-observability-metrics-micrometer"><img src="https://agentmods.dev/badge/skills/jabrena/plinth/182-java-observability-metrics-micrometer.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 | $0.00109 | $0.00690 |
| Opus 5 | $0.00055 | $0.00345 |
| Sonnet 5 | $0.00022 | $0.00138 |
| Haiku 4.5 | $0.00011 | $0.00069 |
Grade A, and why
182-java-observability-metrics-micrometer 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 7d 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 — 63 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Java Metrics Observability with Micrometer
Implement effective Java metrics instrumentation with Micrometer by defining meaningful service-level metrics, controlling cardinality, selecting the right meter type, and exposing production-ready telemetry for dashboards and alerting.
What is covered in this Skill?
- Metrics-first observability with Micrometer in Java applications
- Meter selection: Counter, Timer, DistributionSummary, Gauge, LongTaskTimer
- Naming and tagging conventions with low-cardinality dimensions
- Cardinality and meter lifecycle safeguards to prevent time-series explosion
- Histogram/percentile strategy and SLO-oriented metrics design
- Integration guidance for Actuator + Prometheus/OpenTelemetry pipelines
- Testing and verification of metrics registration and values
Scope: Application-level metrics design and instrumentation quality for Java services, with emphasis on operationally useful and cost-efficient telemetry.
Constraints
Metrics instrumentation must be operationally safe, low-cardinality, and validated. Poor tag design or excessive meter creation can degrade observability systems and increase costs.
- LOW CARDINALITY FIRST: Never tag metrics with unbounded values (userId, UUID, raw URL, full exception message)
- RIGHT METER TYPE: Use Counter for monotonically increasing events, Timer for latency, Gauge for point-in-time state, and DistributionSummary for sampled values
- BEFORE APPLYING: Read the reference for good/bad instrumentation examples and anti-patterns
- VERIFY: Run
./mvnw clean verifyormvn clean verifyafter changes
When to use this skill
- Improve metrics
- Apply Micrometer
- Add metrics observability
- Refactor Micrometer instrumentation
- Add Micrometer timers counters or gauges to Java services
Workflow
- Define measurement goals and meter contract
Identify key service indicators (throughput, latency, error ratio, saturation) and map each to stable metric names, units, and low-cardinality tags.
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.
- 7d ago First seen · 63 lines · 109 tokens per session scan A c53315eaae83
182-java-observability-metrics-micrometer is a skill published in the GitHub repository jabrena/plinth (438 stars, last pushed yesterday), licensed Apache-2.0. It adds 109 tokens to every session and 690 once invoked, about $0.0005 per session on Opus 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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