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/kouroshez/coding-os/observabilitynpx skills add kouroshez/coding-os --skill observabilitygit clone --depth 1 https://github.com/kouroshez/coding-osWhat 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 | $0.00124 | $0.03309 |
| Opus 5 | $0.00062 | $0.01655 |
| Sonnet 5 | $0.00025 | $0.00662 |
| Haiku 4.5 | $0.00012 | $0.00331 |
Grade A, and why
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 2d 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 — 290 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Observability — Logs, Traces, Metrics, SLOs
A practical playbook for instrumenting production code so an incident at 03:00 takes minutes, not hours. Aligned with OpenTelemetry 1.x (the 2026 industry standard) and the SRE workbook's golden-signal approach.
When to Use This Skill
- Adding logging / tracing / metrics to a new service.
- Designing dashboards before launch — observability built in, not bolted on.
- Choosing between OpenTelemetry, Datadog APM, Honeycomb, Grafana Stack, Sentry.
- Defining SLO / SLI / error-budget policy for a feature.
- Writing or reviewing alert rules — a good alert wakes a human at 03:00 for the right reason.
- Investigating "we have logs but can't find the bug" or "alerts fire constantly so nobody reads them."
Skip when: writing a one-off script or a dev-only tool with no production lifetime.
The Three Pillars + One
Industry consensus (2020s onward) is three pillars + traces-as-glue:
| Pillar | Question it answers | Tools |
|---|---|---|
| Metrics | "How is the system doing right now?" — counters, gauges, histograms | Prometheus, Datadog Metrics, CloudWatch Metrics |
| Logs | "What exactly happened for this request?" — structured events | Loki, ELK, Datadog Logs, CloudWatch Logs |
| Traces | "How did the work flow across services?" — spans + parent-child links | Jaeger, Tempo, Datadog APM, Honeycomb |
| Profiles (emerging fourth) | "Why is the CPU/memory burning?" — continuous profiling | Pyroscope, Parca, Datadog Profiler |
Always use OpenTelemetry (OTel) as the instrumentation layer. Send to whatever backend you pick. This decouples vendor choice from code — switching from Datadog to Honeycomb becomes a config change, not a rewrite. OTel SDK is stable for traces, metrics, and logs in 2026 across Python, TypeScript, Go, Java.
Golden Signals (Google SRE Book)
Every service has four metrics worth tracking, no matter what it does:
| Signal | What | Why |
|---|---|---|
| Latency | P50 / P95 / P99 of successful responses | Slow → users churn |
| Traffic | Requests per second / events per second | Capacity planning, anomaly baseline |
| Errors | Rate of failed requests (5xx for HTTP) | Reliability bottom line |
| Saturation | "How full" — CPU%, mem%, queue depth, connection pool used | Predicts incidents before they fire |
What ships with it
3 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.
- 2d ago First seen · 290 lines · 124 tokens per session scan A 924f96868392
observability is a skill published in the GitHub repository kouroshez/coding-os (6 stars, last pushed 2d ago), licensed Apache-2.0. It adds 124 tokens to every session and 3,309 once invoked, about $0.0006 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 2026-08-31.
Other skills, from other repositories
potpie-source-ingestion
Use when the user explicitly asks to ingest, refresh, or deeply understand a repository, PR, issue, ticket, runbook, incident report, document, or web link into Potpie. The harness performs todo-driven discovery, uses local/GitHub/integration tools and read-only subagents when available, builds evidence-backed…
potpie-repo-baseline
Use when establishing, refreshing, or deeply understanding a repository's baseline memory in Potpie: purpose, application type, features, services/modules, environments, deploy shape, dependencies, API contracts, datastores, integrations, ownership, and explicit preferences. The harness reads authored and…
graph-mutation-plan
Cookbook for composing an applygraphmutations plan — stable entitykey patterns, the canonical label/edge vocabulary, evidence/invalidation/confidence discipline, and a worked example. Load this when building a non-trivial mutation plan.
obsidian-layout-adjustment
Workflow for working with the user on changing how Obsidian looks using CSS snippets. Use this whenever the user asks to restyle Obsidian, tune a vault's visual layout, adjust tabs, sidebars, note surfaces, properties, backlinks, graph panes, file explorer rows, icons, links, shadows, active states, or CSS snippets.…
alfworld-locate-target-object
Navigates to a suspected location and identifies a target object. Use when your goal requires finding a specific object (e.g., "potato", "plate") and its location is not immediately known. Moves to a relevant receptacle (like a fridge or cabinet), checks its contents, and outputs the object's location or confirms its…
scienceworld-growth-focuser
Use when you have planted a seed or need to track a plant's growth stage (sprouting, flowering, reproduction). Applies the 'focus on' action to a specific plant or biological entity to signal intent and monitor its development. Trigger after planting or when you need to observe life cycle progression in the…