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/int2t05/engineering-skills/observabilitynpx skills add int2t05/engineering-skills --skill observabilitygit clone --depth 1 https://github.com/int2t05/engineering-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/int2t05/engineering-skills/observability)<a href="https://agentmods.dev/skills/int2t05/engineering-skills/observability"><img src="https://agentmods.dev/badge/skills/int2t05/engineering-skills/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 | $0.00063 | $0.01687 |
| Opus 5 | $0.00032 | $0.00843 |
| Sonnet 5 | $0.00013 | $0.00337 |
| Haiku 4.5 | $0.00006 | $0.00169 |
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 4d 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 — 101 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Observability and Instrumentation
Code you can't observe is code you can't operate. Instrumentation is written alongside the feature, the same way tests are — if a feature ships without telemetry, the first user-reported bug becomes archaeology instead of a query.
When to use
- Building a feature that will run in production (new service, endpoint, background job, external integration).
- A production incident took too long to diagnose because the system couldn't tell what happened.
- Adding or reviewing alerting rules.
- Reviewing a PR that adds I/O, retries, queues, or cross-service calls.
Not for: Diagnosing a live failure (use debugging) or profiling measured slowness (use performance). Observability is what makes those skills fast next time.
Steps
1. Define "working" before instrumenting
Write down 2–4 questions an on-call engineer will ask about this feature. Every signal you add must answer one of them — if you can't name the questions, you'll log everything and learn nothing.
If the service has no SLO, define one before setting alert thresholds. An SLO turns "is it healthy?" from a feeling into a number — see references/slo-methodology.md for SLI definition, error budgets, and burn-rate alerting.
2. Pick the right signal per question
- Structured log — "what happened in this specific case?" (per-event; grows with traffic)
- Metric — "how often / how fast, in aggregate?" (fixed per series; cheap to query)
- Trace — "where did time go across services?" (per-request; usually sampled)
Rule of thumb: metrics tell you that something is wrong, traces tell you where, logs tell you why.
3. Structured logging
Log events, not prose. Every line is a JSON object with a stable event name and machine-readable fields.
// BAD: string interpolation — unqueryable, inconsistent
logger.info(`Payment ${id} failed for user ${userId} after ${n} retries`);
// GOOD: stable event name + structured fields
logger.warn({ event: 'payment_failed', paymentId: id, provider: 'stripe',
errorCode: err.code, attempt: n }, 'payment failed');
What ships with it
5 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.
- 4d ago First seen · 101 lines · 63 tokens per session scan A 4d37100d40d9
observability is a skill published in the GitHub repository int2t05/engineering-skills (3 stars, last pushed 3d ago), licensed MIT. It adds 63 tokens to every session and 1,687 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 2026-08-31.
Other skills, from other repositories
style-direction
Abrir y operar el companion visual de Selina para elegir una direccion de estilo en proyectos con interfaz. Skill manual: levanta un servidor local y escribe artefactos visuales.
incident-response
Protocolo de respuesta ante incidentes en produccion: triaje, mitigacion, causa raiz y postmortem. Usar ante caidas, errores criticos, incidentes de seguridad o degradacion de servicio.
pr-workflow
Crear pull requests completas con descripcion, labels y reviewers.
sync-project-docs
Usar para sincronizar la documentación viva del proyecto después de una fase. También: actualizar docs/project, índice, architecture.md, compliance.md, threat-model.
write-adr
Usar para escribir o cerrar un Architecture Decision Record. También: ADR, docs/adr, decisión de stack, persistencia, autenticación o límites de arquitectura.
compliance-check
Usar para verificar cumplimiento RGPD, NIS2 y CRA. También: verificar RGPD, cumplimiento normativo, NIS2, CRA, Cyber Resilience Act, protección de datos, regulación europea.