ai-assist-observability-audit

Tinjau · 60
Diindeks di Registry

17-dimension observability audit with tier activation, health scoring, and cost analysis. Covers logging, metrics, tracing, alerting, SLOs, profiling, security observability, and developer experience. Use when assessing observability posture, identifying telemetry gaps, or optimi

Verified installs0
Star88
Versi1.0.0
Kualitas61/100 · Menjanjikan
Kepercayaan60/100 · Hanya sandbox
Audit74/100 · Perlu ditinjau

Profil aset

Riset dan pekerjaan pengetahuan

Deep research, source comparison, literature review, RAG, knowledge search, and reports.

Lihat kategori

Skenario

Agent riset

I need my agent to research a topic, compare sources, and produce a concise report.

Kecocokan Agent

Claude Code + CLI + Codex

Cocok untuk Codex, Claude Code, Cursor, CLI, atau Agent khusus.

Pasang

Siap

npx skills add jparkerweb/ai-assist-skills --skill ai-assist-observability-audit

Pemeliharaan

Terkini

1 hari sejak push

Risiko

Perlu ditinjau

Lisensi tidak jelas

Kualitas GitHub

88

61/100 Kualitas · 68/100 Kepercayaan

Tag cakupan

RisetAgent risetKeamananagent-skill

Catatan ulasan

Lisensi tidak jelas · Financial research output is not financial advice; require human review before any live investment decision

Kartu adopsi Agent

Kepercayaan, audit, dan kesiapan pemasangan dalam sekali lihat

Skor ini menggabungkan metadata repositori publik, sinyal ulasan OpenAgentSkill, kebaruan pemeliharaan, dan kesiapan pemasangan. Ini adalah sinyal shortlist, bukan pengganti peninjauan manusia.

Kualitas

Menjanjikan
61

Useful candidate, but compare it with alternatives before adopting.

Kepercayaan

Hanya sandbox
60

Kandidat berguna dengan sinyal kepercayaan yang kurang atau bercampur. Gunakan di ruang kerja terisolasi hingga loop hasil membuktikan kecocokan tugas.

Audit

Perlu ditinjau
74

Tinjauan yang dapat dibaca mesin tentang kesiapan pemasangan, metadata keamanan, pemeliharaan, dan risiko adopsi.

Trust Score OpenAgentSkill v5

Tinjauan manusia sebelum pemasangan

Jalankan hanya dalam sandbox dan bandingkan alternatif terdekat sebelum digunakan untuk kerja nyata.

CodexClaude CodeCursorOpenAgentSkill CLI

Star

88 star GitHub

Aktivitas repositori

88 star dan 12 fork

Pemeliharaan

1 hari sejak push

Lisensi

Tidak diketahui

Pasang

npx skills add jparkerweb/ai-assist-skills --skill ai-assist-observability-audit

Keamanan pemasangan

Jalur pemasangan paket atau runtime standar

Cakupan izin

Akses sistem file atau dokumen

Hasil Agent

Belum ada data hasil Agent

Dokumentasi

Usable metadata, review docs

Ringkasan risiko

Tinjau sebelum produksi

  • Repository license is unknown; missing license clarity makes compliance evaluation difficult.
  • Financial research output is not financial advice; require human review before any live investment decision.
  • Lisensi tidak jelas
  • Quality score needs review

Kesiapan pemasangan

Jalur pemasangan tersedia

  • Jalur pemasangan tersedia
  • Bukti repositori tersedia
  • Lisensi tidak jelas
  • Belum ada bukti hasil Agent-Proven

Metadata yang dapat dibaca Agent

Data keputusan yang dapat dibaca mesin untuk skill ini.

Gunakan blok ini atau JSON tersemat untuk memutuskan apakah Agent perlu memasang skill ini, memilih alternatif, atau meminta tinjauan manusia terlebih dahulu.

Buka JSON

Tugas yang sesuai

  • Alur kerja Agent riset
  • Tim Claude Code
  • builders willing to evaluate younger projects
  • Sumber pencarian

Agent yang sesuai

CodexClaude CodeCursorOpenAgentSkill CLICLI

Keputusan pemasangan

Perintah
npx skills add jparkerweb/ai-assist-skills --skill ai-assist-observability-audit
Kebijakan
Tinjau
Tinjauan manusia
Ya

Kepercayaan dan risiko

Kepercayaan
60/100
Audit
74/100
Tingkat risiko
Perlu ditinjau

Lingkar hasil

Endpoint
/api/agent/outcome
ID event
resolve
Hasil
5

Perintah pemasangan

npx skills add jparkerweb/ai-assist-skills --skill ai-assist-observability-audit

Jangan gunakan ketika

  • Tim yang membutuhkan SLA dengan dukungan vendor
  • production agents without a repository review
  • Repository license is unknown; missing license clarity makes compliance evaluation difficult.
  • Lisensi tidak jelas
  • Financial research output is not financial advice; require human review before any live investment decision

Keamanan Agent v2

58/100 · Tinjau sebelum memasang

Ditinjau dengan catatan izinTinjau

Kandidat yang dapat digunakan, tetapi Agent harus menampilkan catatan izin dan audit sebelum memasang.

Memerlukan persetujuan manusia sebelum memasang ke workspace nyata.

Selesaikan via API

Sedang

Akses jaringan

Skill kemungkinan mengambil halaman jarak jauh, API, repositori, atau layanan eksternal.

Sedang

Akses sistem file

Skill dapat membaca atau menulis file proyek, dokumen, artefak yang dihasilkan, atau status workspace lokal.

  • Lisensi tidak jelas

Target pemasangan

Pasang skill ini di alur Agent Anda

Gunakan endpoint publik untuk mengambil perintah, checklist keamanan, prompt target, dan tautan kanonis.

skill install

OpenAgentSkill CLI

Resolve policy, run the source installer safely, and report a verified install receipt.

$ npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.2.1/openagentskill-0.2.1.tgz install jparkerweb-ai-assist-observability-audit

Rencana resolusi Agent

Biarkan Agent memverifikasi kecocokan sebelum memasang.

API Resolve mengembalikan skill utama, alternatif, kebijakan keamanan, catatan audit, target pemasangan, dan prompt siap pakai.

Buka rencana teks

Agent harus memeriksa

  • Task fit and alternatives from Resolve API.
  • Audit score, trust score, and safety policy warnings.
  • Install target compatibility for Codex, Claude Code, Cursor, or CLI.

Salin prompt

Task: Use ai-assist-observability-audit in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20ai-assist-observability-audit%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/jparkerweb-ai-assist-observability-audit/install
Install command: npx skills add jparkerweb/ai-assist-skills --skill ai-assist-observability-audit
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.

Serah-terima Agent

Berikan jalur pemasangan kepada Agent, bukan direktori lain.

Gunakan endpoint publik untuk mengambil perintah, checklist keamanan, prompt target, dan tautan kanonis.

Buka API pemasangan

Prompt Agent

Use ai-assist-observability-audit for this task. Review https://www.openagentskill.com/api/skills/jparkerweb-ai-assist-observability-audit/install, then install with: npx skills add jparkerweb/ai-assist-skills --skill ai-assist-observability-audit

Metadata Registry

Profil yang dapat dibaca Agent untuk pemilihan skill otomatis.

API Registry menyediakan sinyal keputusan, kepercayaan, audit, use case, dan pemasangan tanpa mengikis UI.

Buka Manifest

Kecocokan Agent

63/100

Agent riset

Platform

Claude Code

Laporan audit

Perlu ditinjau · 74/100

Tinjauan yang dapat dibaca mesin tentang kesiapan pemasangan, metadata keamanan, pemeliharaan, dan risiko adopsi.

Lihat laporan auditLihat laporan evaluasi

Panel keputusan Agent

Fallback candidate for Research agents

Prototype with this skill first; keep a fallback candidate ready.

63
Kesiapan
Prototipe
Tahap

Peran di stack

Kandidat cadangan

Kecocokan utama

Agent riset

Label kepercayaan

Buat prototipe dulu

Jalur pemasangan

Perintah siap

Gunakan saat

  • Alur kerja Agent riset
  • Tim Claude Code
  • builders willing to evaluate younger projects

Bukti

  • recent repository activity
  • install command or GitHub repo available
  • profil kualitas 61/100
  • 9 event interaksi OpenAgentSkill

tinjau dulu

  • Repository license is unknown; missing license clarity makes compliance evaluation difficult.

Jalur implementasi

  1. 1Pasang di Agent sandbox dan jalankan satu tugas Agent riset dari awal hingga akhir.
  2. 2Compare output quality, latency, and failure behavior against at least one alternative.
  3. 3Promote it into production only after reviewing repository permissions, license, and maintenance signals.

Profil kepercayaan

Hanya sandbox

Kandidat berguna dengan sinyal kepercayaan yang kurang atau bercampur. Gunakan di ruang kerja terisolasi hingga loop hasil membuktikan kecocokan tugas.

60
Trust Score OpenAgentSkill

Adopsi GitHub

Periksa

88 star GitHub

Aktivitas star/fork

Periksa

88 star dan 12 fork; aktivitas issue tidak tersedia dalam metadata saat ini

Pemeliharaan terbaru

Lulus

1 hari sejak push

Kejelasan lisensi

Periksa

Tidak diketahui

Sinyal positif

  • Tinjauan AI disetujui
  • Jalur pemasangan tersedia
  • Bukti repositori tersedia
  • Repositori yang baru dipelihara
  • Perintah pemasangan tidak memiliki pola berisiko tinggi yang jelas
  • Loop hasil siap tetapi membutuhkan eksekusi Agent nyata pertama

Tinjau sebelum memasang

  • Repository license is unknown; missing license clarity makes compliance evaluation difficult.
  • Financial research output is not financial advice; require human review before any live investment decision.
  • Lisensi tidak jelas
  • Quality score needs review
  • GitHub adoption: 88 GitHub stars
  • Stars/forks activity: 88 stars, 12 forks; issue activity unavailable in current metadata
  • License clarity: Unknown
  • Belum ada laporan hasil Agent nyata
  • Tinjauan manusia diperlukan sebelum pemasangan tanpa pengawasan

Tindakan yang disarankan

Jalankan hanya dalam sandbox dan bandingkan alternatif terdekat sebelum digunakan untuk kerja nyata.

Profil kualitas

Menjanjikan kandidat untuk alur kerja Agent

Useful candidate, but compare it with alternatives before adopting.

61
Star GitHub
88
Keterkinian
1 hari lalu
Siap dipasang
Ya
Lisensi
Tidak diketahui
Tinjau sebelum memasang: Repository license is unknown; missing license clarity makes compliance evaluation difficult.

Kecocokan alur kerja

Gunakan skill ini pada skenario berikut

Kecocokan alur kerja

Tambahkan ke alur kerja lengkap

Daftar alternatif

Bandingkan sebelum memasang

Similar skills that may fit this task.

Bandingkan semua

Ringkasan

--- name: ai-assist-observability-audit description: "17-dimension observability audit with tier activation, health scoring, and cost analysis. Covers logging, metrics, tracing, alerting, SLOs, profiling, security observability, and developer experience. Use when assessing observability posture, identifying telemetry gaps, or optimizing observability costs." argument-hint: "[dimension or scope]" ---

# OBSERVABILITY AUDIT

**Objective:** Produce a tier-activated, cost-aware observability posture assessment with health score and prioritized improvement plan across 17 dimensions. **When to use:** Assessing observability posture, identifying telemetry gaps, auditing cost efficiency, preparing for production readiness, optimizing observability spend.

Start all responses with '📡 [Obs Audit Step X: Name]'

## Role

Senior observability engineer auditing 17 dimensions — foundational telemetry, operational readiness, security observability, cost governance, and developer experience. Ensure exactly the right amount of observability: not more (waste), not less (blind spots).

## Context

**AGENTS.md check:** If `./AGENTS.md` exists, read it for observability-relevant conventions and deployment patterns. If missing, warn and proceed with standard practices.

**Spec awareness:** If `specs/` has active work, verify observability changes don't conflict with in-progress implementation.

**Stack detection:** Detect from imports/configs: logging, metrics, tracing, APM vendor, profiling, service mesh, MQ, databases. Research best practices and cost models for detected stack.

**Input:** `$ARGUMENTS` — optional dimension name/group and scope (directory, service, or "full"). Default: full audit, all activated dimensions.

## Rules

1. **Observability has real cost.** Every log, metric, trace costs money — evaluate cost/benefit for every finding. 2. **Log levels are a cost lever.** Production WARN+. DEBUG/INFO only in dev or behind dynamic flag. 3. **Cardinality kills budgets.** Calculate label products (e.g., 1K x 20 x 10 x 3 = 600K series). Flag high-cardinality. 4. **Traces should be sampled.** Head/tail-based sampling per traffic volume. 100% sampling in prod is almost always wrong. 5. **Sensitive data in telemetry is ALWAYS Critical.** PII/credentials/tokens in logs, traces, labels — no exceptions, no downgrades. 6. **Structured logs only.** JSON/logfmt, one line per event. Unstructured logging is a finding. 7. **Gaps as important as waste.** Missing observability on critical paths = incident response failures. 8. **Tier activation mandatory.** Match dimensions to detected project tier — never audit non-applicable dimensions. 9. **Standards are the benchmark.** Research current versions of OpenTelemetry, Prometheus, OpenSLO, DORA, NIST logging guidance, OpenCost at audit time. Never assume a specific version is current. 10. **Cross-cutting cost analysis mandatory.** Dedicated cost step across ALL telemetry types — not optional. 11. **Alert-readiness matters.** Observability without actionable alerts is data hoarding. 12. **Chat-only output.** Present ALL findings in chat. Never create files without explicit user permission.

## Process

### Step 1: Context & Stack Detection

1. Read AGENTS.md, run `git status`, detect stack from imports and configs 2. Detect: logging framework, metrics library, tracing SDK, APM vendor, profiling tools, message queues, databases, service mesh 3. Research best practices and cost models for detected stack; parse arguments for focus/scope

> 📡 [Obs Audit Step 1: Context & Stack Detection] Stack: [logging] + [metrics] + [tracing]. Vendor: [APM]. Tier: [tier]. Conditional: [none/MQ/DB].

### Step 2: Tier Activation & Audit

Read `references/dimensions.md` for the tier activation table, tier detection signals, and per-dimension check definitions.

1. Classify project tier using detection signals from dimensions.md 2. Build activated dimension list based on tier 3. Audit each activated dimension in order: UNIVERSAL, SERVICE, DISTRIBUTED, Conditional

> 📡 [Obs Audit Step 2: Tier Activation & Audit] Tier: [TIER]. Active: [N]/17. Maturity: [Foundation/Advanced].

### Step 3: Cost Analysis (Cross-Cutting)

Read `references/scoring.md` for the cost analysis framework, vendor rate ranges, and estimation methodology.

1. Aggregate costs across logging, metrics, tracing, profiling, infrastructure 2. Identify top 5 highest-cost sources with file:line references 3. Recommend: log level changes, label reduction, sampling adjustments, retention tiering 4. Present before/after estimates where data supports it

### Step 4: Findings Report & Score

Read `references/scoring.md` for health score calculation, group weights, and severity definitions.

Read `references/output-template.md` for finding format, summary table, positive observations, improvement plan, fix options, and session-end format.

1. Calculate health score using group weights and N/A redistribution 2. Rank findings by severity (Critical → Warning → Suggestion) 3. Present: stack summary, dimension findings with evidence, summary table, positive observations (3-5), health score, improvement plan (P1/P2/P3 with cost impact), fix options

### Self-Verification Checklist

> Canonical version in `references/output-template.md`. Brief version here for quick reference.

- [ ] All activated dimensions audited; N/A documented - [ ] Tier activation justified with codebase signals - [ ] Cardinality cost analysis for all custom metrics with labels - [ ] Sensitive data scan: logs, trace attributes, metric labels - [ ] Gap analysis: missing observability on critical paths - [ ] Cross-cutting cost analysis across ALL telemetry types - [ ] Every finding has file:line and cost impact where applicable

### Session End

``` 📡 [Obs Audit Complete]

**Score:** [XX]/100. Tier: [tier]. Dims: [N]/17. Cost impact: [summary]. ```

**Next steps (ask user — do not auto-execute):** - Save report to `specs/audit-reports/obs-audit-<date>.md`? - Implement fixes? (by priority) - Related: `/ai-assist-security-audit`, `/ai-assist-tech-debt`, `/ai-assist-test-audit`

## Recovery

| Issue | Solution | |-------|----------| | No observability stack detected | Critical gap; recommend stack for project type and language | | Cannot estimate costs without vendor info | Report cardinality/volume without dollar amounts; note limitation | | Microservices with different stacks | Audit each separately; aggregate in summary | | No production config visible | Audit code patterns; note limitation | | Tier unclear | Default SERVICE; note ambiguity | | Too many dimensions for context | Prioritize Telemetry Foundation + Sensitive Data |

## Important Reminders

**Response format:** Every response starts with `📡 [Obs Audit Step X: Name]`

**Hard rules:** Observability has real cost. Sensitive data in telemetry is ALWAYS Critical. Cardinality: always calculate series count. Tier activation mandatory.

**Process rules:** Cost analysis mandatory and cross-cutting. Gaps as important as waste. Standards: OpenTelemetry, Prometheus, OpenSLO, DORA, NIST logging guidance, OpenCost — research current versions at runtime.

**Related:** `/ai-assist-security-audit` for security posture, `/ai-assist-tech-debt` for codebase health, `/ai-assist-test-audit` for test coverage gaps.

Detail teknis

Versi
1.0.0
Lisensi
Unknown
Pembaruan terakhir
21 Agu 2026
Diterbitkan
21 Agu 2026

Ringkasan keputusan

Kandidat cadangan

63
Siap
Prototipe
Tahap

recent repository activity

Audit

Tinjauan pemasangan

Tinjauan pemasangan dan adopsi

74
Perlu ditinjau
Keamanan
75/100
Pemeliharaan
100/100
Pasang
92/100
Buka audit lengkapLihat laporan evaluasi

Bukti tervalidasi Agent

Bukti tervalidasi Agent

Laporan hasil setelah resolve, tinjau, pasang, dan satu eksekusi terbatas.

0
Terbukti
Needs first agent runPasang otomatis: tinjau duluTerakhir: Tidak diketahui
Tingkat sukses
Kegagalan terbaru
Hasil
0
Kualitas output
Gagal
0
Tidak relevan
0
Pemasangan
0
Diblokir risiko
0
Perlu penyiapan
0
Produksi
0

Belum ada data hasil Agent. Eksekusi pertama dapat melaporkan keberhasilan, kebutuhan setup, blok risiko, kegagalan, atau tidak relevan melalui /api/agent/outcome.

Pasang

Tambahkan ke alur Agent

Gratis dan sumber terbuka. Tinjau laporan sebelum memasang pada Agent produksi.

Siklus pertumbuhan

Kit berbagi

X

Draf berbasis skenario untuk ai-assist-observability-audit, siap untuk posting manual di X.

Catatan kurator
ai-assist-observability-audit: 17-dimension observability audit with tier activation, health scoring, and cost analysis. Cov...

88 stars

https://www.openagentskill.com/skills/jparkerweb-ai-assist-observability-audit?ref=x
Buka draf X
Balasan opsional dengan perintah pemasangan
Listing + install path for ai-assist-observability-audit:
https://www.openagentskill.com/skills/jparkerweb-ai-assist-observability-audit?ref=x

Install: npx skills add jparkerweb/ai-assist-skills --skill ai-assist-observability-audit
Buka draf balasan

Sumber listing

Diindeks Registry

Dapat diklaim

Listing ini diindeks dari sumber publik dan belum ditandai resmi hingga klaim pemelihara disetujui.

Kreator
jparkerweb
Diindeks oleh
Indeks komunitas OpenAgentSkill

Atribusi menautkan ke repositori publik atau profil kreator. Kreator dapat mengklaim listing untuk memperbarui sinyal kepemilikan.

Klaim skill ini

Klaim pemilik

Klaim listing skill ini

Listing Diindeks Registry ini dikaitkan dengan jparkerweb, tetapi belum ditandai resmi. Klaim untuk menambahkan sinyal pemilik terverifikasi dan membuat pembaruan peluncuran, pemasangan, serta audit berikutnya lebih tepercaya.

Kit backlink kreator

Tambahkan badge bukti ke README Anda

Tampilkan listing kanonis, sinyal kepercayaan dan audit saat ini, serta bukti Agent-Proven nyata di tempat pengembang mengevaluasi repositori.

[![Listed on OpenAgentSkill](https://www.openagentskill.com/api/badge/jparkerweb-ai-assist-observability-audit?metric=listed&label=Listed)](https://www.openagentskill.com/skills/jparkerweb-ai-assist-observability-audit)
[![OpenAgentSkill Trust](https://www.openagentskill.com/api/badge/jparkerweb-ai-assist-observability-audit?metric=trust&label=Trust)](https://www.openagentskill.com/skills/jparkerweb-ai-assist-observability-audit)
[![OpenAgentSkill Audit](https://www.openagentskill.com/api/badge/jparkerweb-ai-assist-observability-audit?metric=audit&label=Audit)](https://www.openagentskill.com/skills/jparkerweb-ai-assist-observability-audit/audit)
[![Agent Proven](https://www.openagentskill.com/api/badge/jparkerweb-ai-assist-observability-audit?metric=proven&label=Agent%20Proven)](https://www.openagentskill.com/skills/jparkerweb-ai-assist-observability-audit)

Penulis

J

jparkerweb

@jparkerweb

Kecocokan platform

Sinyal kesehatan

Star GitHub
88
Skor kualitas
37/100
Push GitHub terakhir
20 Agu 2026
Petunjuk framework
Tidak diketahui
Tampilan OpenAgentSkill
9
Salinan pemasangan
0
Klik keluar
0

Sinyal komunitas

Bagikan apakah skill ini bermanfaat untuk alur kerja Agent Anda. Masukan gabungan meningkatkan peringkat dari waktu ke waktu.

Kepercayaan & keamanan

Hanya sandbox

60
  • Adopsi GitHub88 star GitHubPeriksa
  • Aktivitas star/fork88 star dan 12 fork; aktivitas issue tidak tersedia dalam metadata saat iniPeriksa
  • Pemeliharaan terbaru1 hari sejak pushLulus
  • Kejelasan lisensiTidak diketahuiPeriksa
  • Kelengkapan README/SKILL.mdMetadata publik memerlukan konteks README/SKILL.md yang lebih kuatInfo
  • Risiko dependensi/runtimeTidak ada petunjuk risiko dependensi besar dalam metadata publikLulus