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/yonatangross/orchestkit/monitoring-observabilitynpx skills add yonatangross/orchestkit --skill monitoring-observabilitygit clone --depth 1 https://github.com/yonatangross/orchestkitWrote 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/yonatangross/orchestkit/monitoring-observability)<a href="https://agentmods.dev/skills/yonatangross/orchestkit/monitoring-observability"><img src="https://agentmods.dev/badge/skills/yonatangross/orchestkit/monitoring-observability.svg" alt="Measured on agentmods" 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 | $0.00069 | $0.02374 |
| Opus 5 | $0.00034 | $0.01187 |
| Sonnet 5 | $0.00014 | $0.00475 |
| Haiku 4.5 | $0.00007 | $0.00237 |
Grade A, and why
monitoring-observability 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 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.
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 — 162 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Monitoring & Observability
A wrap around Prometheus, Grafana, OpenTelemetry and Langfuse, not a re-teaching of them. This
skill carries OrchestKit's delta (version floors, house decisions, scars) and points at the
vendor for everything else. Start at references/ork-delta.md.
Upstream coverage (do not restate)
These topics are fully covered first-party. Read the source, do not add a local copy.
| Topic | First-party source |
|---|---|
| Prometheus metric types, RED method, cardinality, PromQL | https://prometheus.io/docs/practices/ |
| Alertmanager grouping, inhibition, escalation, runbooks | https://prometheus.io/docs/alerting/latest/configuration/ |
| Grafana dashboards, Loki and LogQL, Promtail | https://grafana.com/docs/ |
| OpenTelemetry spans, sampling, context propagation | https://opentelemetry.io/docs/ |
Langfuse Python SDK (@observe, as_type, score_current_span, should_export_span, LangfuseMedia) |
https://langfuse.com/docs/sdk/python |
| Langfuse v2 to v4 Python and v3 to v5 JS migration paths | https://langfuse.com/docs/sdk/python/v4-migration |
| Langfuse self-hosting (ClickHouse, Redis, S3, Helm) | https://langfuse.com/docs/deployment/self-host |
| Langfuse cost tracking, model pricing, Metrics API v2 | https://langfuse.com/docs/model-usage-and-cost |
| Langfuse scores, online evaluators, annotation queues, prompt management | https://langfuse.com/docs/scores/overview |
| Langfuse framework integrations (LangChain, LangGraph, CrewAI, Pydantic AI, Bedrock, LiveKit) | https://langfuse.com/docs/integrations |
| Agent Graphs, observation types, rendered tool calls | https://langfuse.com/docs/tracing-features/agent-graphs |
| PSI, KS test, KL and JS divergence, Wasserstein, embedding drift | https://www.evidentlyai.com/blog/data-drift-detection-large-datasets |
| EWMA control charts | https://www.itl.nist.gov/div898/handbook/pmc/section3/pmc324.htm |
| structlog, Winston, correlation IDs, log sampling | https://www.structlog.org/en/stable/ |
What ships with it
26 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.
- examples/orchestkit-monitoring-dashboard.md 14 KB
- metadata.json 539 B
- references/dashboards.md 1.2 KB
- references/dev-agent-lens.md 5.4 KB
- references/evaluation-scores.md 6.6 KB
- references/experiments-api.md 14 KB
- references/langfuse-js-v5.md 5.0 KB
- references/metrics-collection.md 6.7 KB
- references/ork-delta.md 5.3 KB
- references/session-tracking.md 6.9 KB
- references/structured-logging.md 1.4 KB
- rules/_sections.md 1.3 KB
- rules/_template.md 339 B
- rules/llm-langfuse-traces.md 6.4 KB
- rules/monitoring-grafana.md 3.1 KB
- rules/silent-alerting.md 2.4 KB
- rules/silent-degraded-quality.md 3.0 KB
- rules/silent-tool-skipping.md 1.9 KB
- scripts/alerting-rules.yml 3.1 KB
- scripts/callback-handler.py 8.7 KB runs code
- scripts/health-checks.ts 2.6 KB runs code
- scripts/observe-decorator.py 5.7 KB runs code
- scripts/opentelemetry-tracing.ts 3.8 KB runs code
- scripts/prometheus-metrics.ts 3.3 KB runs code
- scripts/structured-logging.ts 3.3 KB runs code
- test-cases.json 3.4 KB
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 · 162 lines · 69 tokens per session scan A 62fe96d36354
monitoring-observability is a skill published in the GitHub repository yonatangross/orchestkit (225 stars, last pushed yesterday), licensed MIT. It adds 69 tokens to every session and 2,374 once invoked, about $0.0003 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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