ai-assist-observability-audit
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
Profil aset
Riset dan pekerjaan pengetahuan
Deep research, source comparison, literature review, RAG, knowledge search, and reports.
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
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
MenjanjikanUseful candidate, but compare it with alternatives before adopting.
Kepercayaan
Hanya sandboxKandidat berguna dengan sinyal kepercayaan yang kurang atau bercampur. Gunakan di ruang kerja terisolasi hingga loop hasil membuktikan kecocokan tugas.
Audit
Perlu ditinjauTinjauan 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.
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.
Tugas yang sesuai
- Alur kerja Agent riset
- Tim Claude Code
- builders willing to evaluate younger projects
- Sumber pencarian
Agent yang sesuai
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-auditJangan 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
Kandidat yang dapat digunakan, tetapi Agent harus menampilkan catatan izin dan audit sebelum memasang.
Memerlukan persetujuan manusia sebelum memasang ke workspace nyata.
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.
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-auditRencana 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 JSON
/api/agent/resolve?task=Use%20ai-assist-observability-audit%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Teks Resolve
/api/agent/resolve?task=Use%20ai-assist-observability-audit%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Serah-terima pemasangan
/api/skills/jparkerweb-ai-assist-observability-audit/install
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.
Serah-terima pemasangan
/api/skills/jparkerweb-ai-assist-observability-audit/install
Format teks LLM
/api/skills/jparkerweb-ai-assist-observability-audit/install?format=text
Cari alternatif
/api/skills/search?q=ai-assist-observability-audit&limit=3
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-auditMetadata Registry
Profil yang dapat dibaca Agent untuk pemilihan skill otomatis.
API Registry menyediakan sinyal keputusan, kepercayaan, audit, use case, dan pemasangan tanpa mengikis UI.
Manifest
/api/registry/manifest/jparkerweb-ai-assist-observability-audit
Teks LLM
/api/registry/manifest/jparkerweb-ai-assist-observability-audit?format=text
Alias pemasangan
/api/registry/install/jparkerweb-ai-assist-observability-audit
Rekomendasikan
/api/registry/recommend?task=Use%20ai-assist-observability-audit%20in%20an%20agent%20workflow&limit=3
Kecocokan Agent
Agent riset
Tag use case
Platform
Claude Code
Laporan audit
Perlu ditinjau · 74/100
Tinjauan yang dapat dibaca mesin tentang kesiapan pemasangan, metadata keamanan, pemeliharaan, dan risiko adopsi.
Panel keputusan Agent
Fallback candidate for Research agents
Prototype with this skill first; keep a fallback candidate ready.
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
- 1Pasang di Agent sandbox dan jalankan satu tugas Agent riset dari awal hingga akhir.
- 2Compare output quality, latency, and failure behavior against at least one alternative.
- 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.
Adopsi GitHub
Periksa88 star GitHub
Aktivitas star/fork
Periksa88 star dan 12 fork; aktivitas issue tidak tersedia dalam metadata saat ini
Pemeliharaan terbaru
Lulus1 hari sejak push
Kejelasan lisensi
PeriksaTidak 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.
Kecocokan alur kerja
Gunakan skill ini pada skenario berikut
Investigate faster
Research agents
I need my agent to research a topic, compare sources, and produce a concise report.
Build and ship code
Coding agents
I need a coding agent that can understand a repository, edit code, and review pull requests.
Search private knowledge
RAG and knowledge
I need my agent to build a RAG workflow over documents and retrieve reliable context.
Kecocokan alur kerja
Tambahkan ke alur kerja lengkap
Find, compare, and synthesize
Research report agent
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Inspect, patch, and verify code
Coding review agent
A workflow for software agents that inspect repositories, review pull requests, generate tests, and turn findings into shippable patches.
Ingest, retrieve, and cite
RAG knowledge base
A workflow for document-heavy agents that ingest files, create searchable knowledge, retrieve relevant context, and answer with grounded sources.
Daftar alternatif
Bandingkan sebelum memasang
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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
recent repository activity
Audit
Tinjauan pemasangan
Tinjauan pemasangan dan adopsi
- Keamanan
- 75/100
- Pemeliharaan
- 100/100
- Pasang
- 92/100
Bukti tervalidasi Agent
Bukti tervalidasi Agent
Laporan hasil setelah resolve, tinjau, pasang, dan satu eksekusi terbatas.
- 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
Draf berbasis skenario untuk ai-assist-observability-audit, siap untuk posting manual di X.
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
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
Sumber listing
Diindeks Registry
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 iniKlaim 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.
[](https://www.openagentskill.com/skills/jparkerweb-ai-assist-observability-audit)
[](https://www.openagentskill.com/skills/jparkerweb-ai-assist-observability-audit)
[](https://www.openagentskill.com/skills/jparkerweb-ai-assist-observability-audit/audit)
[](https://www.openagentskill.com/skills/jparkerweb-ai-assist-observability-audit)Penulis
jparkerweb
@jparkerweb
Tag
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
- 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
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