observability-and-instrumentation

observability-and-instrumentation is a skill for Claude Code, Codex from seaworld008/Commonly-used-high-value-skills. It costs 31 tokens per session (2,722 once invoked), scanned A, a copy of observability-and-instrumentation, MIT.

A workflow for adding logs, measurements, traces, and alerts so production software shows what it is doing and why.

In plain words
What is it for?
Use it when building services, endpoints, background jobs, or integrations, or when reviewing code that adds retries, queues, or calls between services.
Why use it?
It makes failures and slow or unreliable behavior easier to investigate after deployment.

Skill for Claude CodeCodex

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

Good fit Use it when building services, endpoints, background jobs, or integrations, or when reviewing code that adds retries, queues, or calls between services.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/seaworld008/commonly-used-high-value-skills/observability-and-instrumentation
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 seaworld008/Commonly-used-high-value-skills --skill observability-and-instrumentation
Clone the repo
git clone --depth 1 https://github.com/seaworld008/Commonly-used-high-value-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-and-instrumentation

README.md
[![agentmods](https://agentmods.dev/badge/skills/seaworld008/commonly-used-high-value-skills/observability-and-instrumentation/github.svg)](https://agentmods.dev/skills/seaworld008/commonly-used-high-value-skills/observability-and-instrumentation)
Your own site
<a href="https://agentmods.dev/skills/seaworld008/commonly-used-high-value-skills/observability-and-instrumentation"><img src="https://agentmods.dev/badge/skills/seaworld008/commonly-used-high-value-skills/observability-and-instrumentation/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-and-instrumentation

Your own site · 80×15
<a href="https://agentmods.dev/skills/seaworld008/commonly-used-high-value-skills/observability-and-instrumentation"><img src="https://agentmods.dev/badge/skills/seaworld008/commonly-used-high-value-skills/observability-and-instrumentation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 31 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,722 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 95% copy Near-identical to another mod 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 $0.00031 $0.02722
Opus 5 $0.00015 $0.01361
Sonnet 5 $0.00006 $0.00544
Haiku 4.5 $0.00003 $0.00272

Measured 5d ago against content hash c5e23550d345, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

observability-and-instrumentation 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 5d 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.

Origin

This is a copy

95% identical to observability-and-instrumentation — 58 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

openclaw-skills/observability-and-instrumentation/SKILL.md · 223 lines

How it starts

The opening of the file, as written. The whole thing — 223 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Observability and Instrumentation

Overview

Code you can't observe is code you can't operate. Observability is the ability to answer "what is the system doing and why?" from the outside, using the telemetry the code emits. Instrumentation is not a post-launch add-on — it's 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 any feature that will run in production
  • Adding a new service, endpoint, background job, or external integration
  • A production incident took too long to diagnose ("we couldn't tell what happened")
  • Setting up or reviewing alerting rules
  • Reviewing a PR that adds I/O, retries, queues, or cross-service calls

NOT for:

  • Diagnosing a failure happening right now — use the debugging-and-error-recovery skill (observability is what makes that skill fast next time)
  • Profiling and optimizing measured slowness — use the performance-optimization skill
  • Launch-day monitoring checklists and rollback triggers — see the shipping-and-launch skill; this skill covers the instrumentation that feeds them

Process

1. Define "working" before instrumenting

Telemetry without a question is noise. Before adding any instrumentation, write down 2–4 questions an on-call engineer will ask about this feature:

FEATURE: checkout payment retry
QUESTIONS ON-CALL WILL ASK:
1. What fraction of payments succeed on first attempt vs after retry?
2. When a payment fails permanently, why? (provider error? timeout? validation?)
3. Is the payment provider slower than usual?
→ Every signal below must help answer one of these.

If you can't name the questions, you're not ready to instrument — you'll log everything and learn nothing.

2. Pick the right signal for each question

Signal Answers Cost profile Example
Structured log "What happened in this specific case?" Per-event; grows with traffic payment_failed with provider error code
Metric "How often / how fast, in aggregate?" Fixed per series; cheap to query p99 latency of provider calls
Trace "Where did time go across services?" Per-request; usually sampled One slow checkout, broken down by hop

Read the full file on GitHub · 223 lines

Files

What ships with it

7 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.

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. 5d ago Changed · +7 lines · -35 tokens per session c5e23550d345
  2. 9d ago First seen · 216 lines · 66 tokens per session scan A d814e7fb3ef0

Subscribe to this mod's changes

observability-and-instrumentation is a skill published in the GitHub repository seaworld008/Commonly-used-high-value-skills (70 stars, last pushed 5d ago), licensed MIT. It adds 31 tokens to every session and 2,722 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 95% identical to observability-and-instrumentation, differing in 58 lines, and is treated as a copy.

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