backend-observability

backend-observability is a skill for Claude Code from contactandrewchl-wq/turtle-mcp. It costs 53 tokens per session (980 once invoked), scanned A, original, MIT.

A set of backend observability guidelines for structured logs, time-based metrics, and distributed traces. Observability means collecting information that helps explain what a service is doing and why it failed.

In plain words
What is it for?
Use it when creating services or sensitive endpoints, investigating incidents, designing alerts and dashboards, or adding request IDs, JSON logs, metrics, and traces.
Why use it?
It helps developers investigate incidents and monitor services with consistent, connected data. It also defines appropriate log levels and warns against recording passwords, tokens, cookies, and personal data.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the turtle plugin — 26 skills shipped together

Good fit Use it when creating services or sensitive endpoints, investigating incidents, designing alerts and dashboards, or adding request IDs, JSON logs, metrics, and traces.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/contactandrewchl-wq/turtle-mcp/backend-observability
Install

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.

Any agent
npx skills add contactandrewchl-wq/turtle-mcp --skill backend-observability
Clone the repo
git clone --depth 1 https://github.com/contactandrewchl-wq/turtle-mcp

Made for: Claude Code.

Or install turtle, the plugin that ships this one along with the rest of its 26 skills.

Wrote 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.

agentmods badge for backend-observability

README.md
[![agentmods](https://agentmods.dev/badge/skills/contactandrewchl-wq/turtle-mcp/backend-observability/github.svg)](https://agentmods.dev/skills/contactandrewchl-wq/turtle-mcp/backend-observability)
Your own site
<a href="https://agentmods.dev/skills/contactandrewchl-wq/turtle-mcp/backend-observability"><img src="https://agentmods.dev/badge/skills/contactandrewchl-wq/turtle-mcp/backend-observability/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.

agentmods 80×15 button for backend-observability

Your own site · 80×15
<a href="https://agentmods.dev/skills/contactandrewchl-wq/turtle-mcp/backend-observability"><img src="https://agentmods.dev/badge/skills/contactandrewchl-wq/turtle-mcp/backend-observability.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 53 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 980 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00053 $0.00980
Opus 5 $0.00026 $0.00490
Sonnet 5 $0.00011 $0.00196
Haiku 4.5 $0.00005 $0.00098

Measured 10d ago against content hash 5fd191bf5c2a, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

backend-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 10d 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.

skills/backend-observability/SKILL.md · 101 lines

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.

Backend observability

Cuándo usar

  • Crear un servicio nuevo o un endpoint sensible.
  • Investigar un incidente y faltan datos.
  • Definir alertas o dashboards.

Pilares

  1. Logs — eventos discretos, con contexto, estructurados (JSON).
  2. Métricas — series temporales agregables.
  3. Trazas — el camino de un request por varios servicios.

Sin los tres, falta una pata: logs sin métricas no escalan, métricas sin trazas no explican causa.

Logs

  • Estructurados ({"ts":..., "level":..., "msg":..., "request_id":..., ...}), nunca strings sueltos.
  • Niveles bien usados:
    • DEBUG — detalle de desarrollo. Off en producción.
    • INFO — eventos esperados (request servido, job ok). Bajo volumen.
    • WARN — anomalía recuperada (reintento, fallback). Mirar tendencias.
    • ERROR — fallo no recuperado en un request/job. Debería alertar si sube.
    • FATAL — el proceso no puede continuar.
  • Un log por evento de negocio. No logs decorativos cada 3 líneas.
  • request_id propagado en todo log de la cadena. Si no podés correlacionar, no podés debuggear.

Qué NUNCA loguear

  • Contraseñas, tokens, claves, header Authorization, cookies de sesión.
  • PII completa: número de tarjeta, RUT/DNI, mail, teléfono. Hashear o truncar si hace falta.
  • Cuerpo de request/response salvo en debug local explícito.
  • Stack traces a clientes (sí internamente).

Métricas — Four Golden Signals

Para todo servicio:

  1. Latency — p50, p95, p99 por endpoint. Promedio miente.
  2. Traffic — requests/seg, por ruta y método.
  3. Errors — tasa de 5xx (y 4xx interesantes como 429).
  4. Saturation — CPU, memoria, conexiones a BD, cola.

Para jobs: éxito/falla/duración/cola.

Convenciones

  • Histogramas, no solo contadores, para latencias.
  • Cardinalidad bajo control: user_id como label rompe Prometheus.
  • Nombres consistentes: http_request_duration_seconds, db_query_duration_seconds.

Trazas

  • OpenTelemetry como estándar. Cliente + auto-instrumentación + exportador a Jaeger/Tempo/Honeycomb.
  • Propagá traceparent entre servicios.
  • Span por unidad de trabajo significativa (request, query, llamada externa, job).
  • Atributos útiles: http.route, db.statement (sanitizado), messaging.destination.

Read the full file on GitHub · 101 lines

Changes

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.

  1. 10d ago First seen · 101 lines · 53 tokens per session scan A 5fd191bf5c2a

Subscribe to this mod's changes

backend-observability is a skill published in the GitHub repository contactandrewchl-wq/turtle-mcp (2 stars, last pushed 2mo ago), licensed MIT. It adds 53 tokens to every session and 980 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.

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