observability-audit

observability-audit is a skill for Claude Code, Codex from Nordic-AI/production-readiness-skills. It costs 106 tokens per session (3,848 once invoked), scanned A, original, Apache-2.0.

A review of whether a running software system produces useful logs, measurements, traces, alerts, and support instructions. These signals help developers and on-call engineers understand failures from outside the system.

In plain words
What is it for?
Use it to review logging, metrics, distributed tracing, error reporting, alert rules, and operational runbooks. It can recommend improvements or add code-level instrumentation.
Why use it?
It finds missing or overly noisy information that makes bugs, outages, and incidents hard to investigate. It checks whether the available signals can lead to clear action.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to review logging, metrics, distributed tracing, error reporting, alert rules, and operational runbooks. It can recommend improvements or add code-level instrumentation.

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Install with agentmods
npx agentmods add skills/nordic-ai/production-readiness-skills/observability-audit
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 Nordic-AI/production-readiness-skills --skill observability-audit
Clone the repo
git clone --depth 1 https://github.com/Nordic-AI/production-readiness-skills

Made for: Claude Code, Codex.

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 observability-audit

README.md
[![agentmods](https://agentmods.dev/badge/skills/nordic-ai/production-readiness-skills/observability-audit/github.svg)](https://agentmods.dev/skills/nordic-ai/production-readiness-skills/observability-audit)
Your own site
<a href="https://agentmods.dev/skills/nordic-ai/production-readiness-skills/observability-audit"><img src="https://agentmods.dev/badge/skills/nordic-ai/production-readiness-skills/observability-audit/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 observability-audit

Your own site · 80×15
<a href="https://agentmods.dev/skills/nordic-ai/production-readiness-skills/observability-audit"><img src="https://agentmods.dev/badge/skills/nordic-ai/production-readiness-skills/observability-audit.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 106 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,848 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 $0.00106 $0.03848
Opus 5 $0.00053 $0.01924
Sonnet 5 $0.00021 $0.00770
Haiku 4.5 $0.00011 $0.00385

Measured 12d ago against content hash caa5afbd8f5a, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

observability-audit 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 12d 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/observability-audit/SKILL.md · 355 lines

How it starts

The opening of the file, as written. The whole thing — 355 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Observability Audit

You review whether the running system can be understood from the outside — by an SRE staring at dashboards at 3am, by a developer triaging a bug report, by an auditor tracing a regulatory incident. Observability is not about having logs; it's about being able to answer questions you didn't know you'd ask.

Inputs

From orchestrator: scope_tier, stack_summary, entry points, gitnexus_indexed.

Mode detection

  • Plan mode — report observability gaps with concrete additions recommended.
  • Edit mode — apply code-level instrumentation. Runbooks and dashboard configs can be scaffolded but require the user to hook them into their actual observability stack.

Thresholds by tier

Tier Structured logs Metrics Traces Alerts Runbooks
prototype advisory optional optional advisory not required
team required — structured + correlation IDs required — RED per endpoint recommended required on critical errors + SLO burn recommended for critical flows
scalable required — structured + correlation + sampling discipline required — RED + USE + business KPIs required — OTel traces across services required — SLO-based, on-call rotation required per critical flow

Review surface

1. Logging

A. Format
  • Structured logging required at team+ tier. JSON or logfmt, not plain text. Look for winston, pino, zap, zerolog, logrus, log/slog, structlog, loguru, SLF4J + Logback JSON encoder, Serilog JSON formatter, etc.
  • Check for console.log / print / fmt.Println used for production logging — almost always an anti-pattern.
  • Log lines must be parseable as a single record (no multi-line logs without proper framing; stack traces in a single field).
B. Correlation
  • Every request/job/message must have a correlation ID (trace-id / request-id / correlation-id) threaded through all logs for that unit of work.
  • Check middleware / interceptors for X-Request-ID propagation.
  • Async boundaries (queue publish → consume) must carry correlation IDs in message metadata.
  • User context (tenant-id, user-id) logged on authenticated requests — with PII discipline (see data-protection-audit overlap).

Read the full file on GitHub · 355 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. 12d ago First seen · 355 lines · 106 tokens per session scan A caa5afbd8f5a

Subscribe to this mod's changes

observability-audit is a skill published in the GitHub repository Nordic-AI/production-readiness-skills (2 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 106 tokens to every session and 3,848 once invoked, about $0.0005 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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