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 julianobarbosa/claude-code-skills --skill opentelemetrygit clone --depth 1 https://github.com/julianobarbosa/claude-code-skillsWrote 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/julianobarbosa/claude-code-skills/opentelemetry)<a href="https://agentmods.dev/skills/julianobarbosa/claude-code-skills/opentelemetry"><img src="https://agentmods.dev/badge/skills/julianobarbosa/claude-code-skills/opentelemetry/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/julianobarbosa/claude-code-skills/opentelemetry"><img src="https://agentmods.dev/badge/skills/julianobarbosa/claude-code-skills/opentelemetry.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Data Exfiltration · line 31 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
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 | $0.00052 | $0.01416 |
| Opus 5 | $0.00026 | $0.00708 |
| Sonnet 5 | $0.00010 | $0.00283 |
| Haiku 4.5 | $0.00005 | $0.00142 |
Grade A, and why
opentelemetry 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 8d 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.
curl -X POST http://otel-collector:4318/v1/traces \ How it starts
The opening of the file, as written. The whole thing — 195 lines — stays where its author put it; the contents beside it link to each section on GitHub.
OpenTelemetry Implementation Guide
Overview
OpenTelemetry (OTel) is a vendor-neutral observability framework for instrumenting, generating, collecting, and exporting telemetry data (traces, metrics, logs). This skill provides guidance for implementing OTEL in Kubernetes environments.
Quick Start
Deploy OTEL Collector on Kubernetes
# Add Helm repo
helm repo add open-telemetry https://open-telemetry.github.io/opentelemetry-helm-charts
helm repo update
# Install with basic config
helm install otel-collector open-telemetry/opentelemetry-collector \
--namespace monitoring --create-namespace \
--set mode=daemonset
Send Test Data via OTLP
# gRPC endpoint: 4317, HTTP endpoint: 4318
curl -X POST http://otel-collector:4318/v1/traces \
-H "Content-Type: application/json" \
-d '{"resourceSpans":[]}'
Core Concepts
Signals: Three types of telemetry data:
- Traces: Distributed request flows across services
- Metrics: Numerical measurements (counters, gauges, histograms)
- Logs: Event records with structured/unstructured data
Collector Components:
- Receivers: Accept data (OTLP, Prometheus, Jaeger, Zipkin)
- Processors: Transform data (batch, memory_limiter, k8sattributes)
- Exporters: Send data (prometheusremotewrite, loki, otlp)
- Extensions: Add capabilities (health_check, pprof, zpages)
Collector Configuration
Basic Pipeline Structure
config:
receivers:
otlp:
protocols:
grpc:
endpoint: ${env:MY_POD_IP}:4317
http:
endpoint: ${env:MY_POD_IP}:4318
processors:
batch:
timeout: 10s
send_batch_size: 1024
memory_limiter:
check_interval: 5s
limit_percentage: 80
spike_limit_percentage: 25
exporters:
prometheusremotewrite:
endpoint: "http://prometheus:9090/api/v1/write"
loki:
endpoint: "http://loki:3100/loki/api/v1/push"
service:
pipelines:
metrics:
receivers: [otlp]
processors: [memory_limiter, batch]
exporters: [prometheusremotewrite]
logs:
receivers: [otlp]
processors: [memory_limiter, batch]
exporters: [loki]
traces:
receivers: [otlp]
processors: [memory_limiter, batch]
exporters: [otlp/tempo]
What ships with it
7 files 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.
- 8d ago First seen · 195 lines · 52 tokens per session scan A 82970879cf8e
opentelemetry is a skill published in the GitHub repository julianobarbosa/claude-code-skills (10 stars, last pushed 16d ago), licensed MIT. It adds 52 tokens to every session and 1,416 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 2026-09-03.
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