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
Supply asset profile
Research and knowledge work
Deep research, source comparison, literature review, RAG, knowledge search, and reports.
Scenario
Research agents
I need my agent to research a topic, compare sources, and produce a concise report.
Agent fit
Claude Code + CLI + Codex
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add jparkerweb/ai-assist-skills --skill ai-assist-observability-audit
Maintenance
fresh
2d since push
Risk
Needs review
License is unclear
GitHub quality
88
61/100 Quality · 68/100 Trust
Coverage tags
Review notes
License is unclear · Financial research output is not financial advice; require human review before any live investment decision
Agent adoption scorecard
Trust, audit, and install readiness at a glance
These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.
Quality
PromisingUseful candidate, but compare it with alternatives before adopting.
Trust
Sandbox onlyUseful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
Audit
Needs reviewA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Human review before install
Run only in a sandbox and compare close alternatives before using it for real work.
Stars
88 GitHub stars
Repo activity
88 stars, 12 forks
Maintenance
2d since push
License
Unknown
Install
npx skills add jparkerweb/ai-assist-skills --skill ai-assist-observability-audit
Install safety
standard package or runtime install path
Permission surface
filesystem or document access
Agent outcomes
No agent outcome data yet
Docs
Usable metadata, review docs
Risk summary
Review before production
- 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.
- License is unclear
- Quality score needs review
Install readiness
Install path available
- Install path is available
- Repository evidence is available
- License is unclear
- No Agent Proven outcome evidence yet
Agent-readable metadata
Machine-readable decision data for this skill.
Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.
Suited tasks
- Research agents workflows
- Claude Code teams
- builders willing to evaluate younger projects
- Search sources
Suited agents
Install decision
- Command
- npx skills add jparkerweb/ai-assist-skills --skill ai-assist-observability-audit
- Policy
- review
- Human review
- yes
Trust and risk
- Trust
- 60/100
- Audit
- 74/100
- Risk level
- Needs review
Outcome loop
- Endpoint
- /api/agent/outcome
- Event ID
- resolve
- Outcomes
- 5
Install command
npx skills add jparkerweb/ai-assist-skills --skill ai-assist-observability-auditDo not use when
- teams that need a vendor-supported SLA
- production agents without a repository review
- Repository license is unknown; missing license clarity makes compliance evaluation difficult.
- License is unclear
- Financial research output is not financial advice; require human review before any live investment decision
Agent safety v2
58/100 · Review before install
Usable candidate, but the agent should surface permission and audit notes before installation.
Require human approval before installing into a real workspace.
medium
Network access
Skill likely fetches remote pages, APIs, repositories, or external services.
medium
Filesystem access
Skill may read or write project files, documents, generated artifacts, or local workspace state.
- License is unclear
Install targets
Install this skill in your agent workflow
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
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-auditAgent resolve plan
Let an agent verify fit before installing.
The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.
Open JSON
/api/agent/resolve?task=Use%20ai-assist-observability-audit%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20ai-assist-observability-audit%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/jparkerweb-ai-assist-observability-audit/install
Agent should check
- 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.
Copy 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.Agent handoff
Give an agent the install path, not another directory page.
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
Install handoff
/api/skills/jparkerweb-ai-assist-observability-audit/install
LLM text format
/api/skills/jparkerweb-ai-assist-observability-audit/install?format=text
Find alternatives
/api/skills/search?q=ai-assist-observability-audit&limit=3
Agent prompt
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-auditRegistry metadata
Agent-readable profile for automatic skill selection.
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
Manifest
/api/registry/manifest/jparkerweb-ai-assist-observability-audit
LLM text
/api/registry/manifest/jparkerweb-ai-assist-observability-audit?format=text
Install alias
/api/registry/install/jparkerweb-ai-assist-observability-audit
Recommend
/api/registry/recommend?task=Use%20ai-assist-observability-audit%20in%20an%20agent%20workflow&limit=3
Agent fit
Research agents
Use-case tags
Platforms
Claude Code
Audit report
Needs review · 74/100
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Fallback candidate for Research agents
Prototype with this skill first; keep a fallback candidate ready.
Role in stack
Fallback candidate
Primary fit
Research agents
Trust label
Prototype first
Install path
Command ready
Use when
- Research agents workflows
- Claude Code teams
- builders willing to evaluate younger projects
Evidence
- recent repository activity
- install command or GitHub repo available
- 61/100 quality profile
- 9 OpenAgentSkill engagement events
review first
- Repository license is unknown; missing license clarity makes compliance evaluation difficult.
Implementation path
- 1Install it in a sandbox agent and run one Research agents task end to end.
- 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.
Trust profile
Sandbox only
Useful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
GitHub adoption
CHECK88 GitHub stars
Stars/forks activity
CHECK88 stars, 12 forks; issue activity unavailable in current metadata
Recent maintenance
PASS2d since push
License clarity
CHECKUnknown
Good signals
- AI review approved
- Install path is available
- Repository evidence is available
- Recently maintained repository
- Install command has no obvious high-risk pattern
- Outcome loop is ready but needs first real agent run
Review before install
- 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.
- License is unclear
- 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
- No real agent outcome reports yet
- Human review required before unattended installation
Recommended action
Run only in a sandbox and compare close alternatives before using it for real work.
Quality profile
Promising candidate for agent workflows
Useful candidate, but compare it with alternatives before adopting.
Workflow fit
Use this skill in these scenarios
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.
Workflow fit
Add it to a complete workflow
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.
Alternative shortlist
Compare before you install
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Overview
--- 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.
Technical details
- Version
- 1.0.0
- License
- Unknown
- Last updated
- Aug 21, 2026
- Published
- Aug 21, 2026
Decision snapshot
Fallback candidate
recent repository activity
Audit
Install review
Install and adoption review
- Security
- 75/100
- Maintenance
- 100/100
- Install
- 92/100
Agent-proven evidence
Agent-proven evidence
Outcome reports after resolve, review, install, and one narrow run.
- Success rate
- —
- Recent failure
- —
- Outcomes
- 0
- Output quality
- —
- Failed
- 0
- Not relevant
- 0
- Installs
- 0
- Risk blocked
- 0
- Setup needed
- 0
- Production
- 0
No agent outcome data yet. The first agent run can report success, setup needs, risk blocks, failure, or not-relevant through /api/agent/outcome.
Install
Add to agent workflow
Free and open source. Review the report before installing into production agents.
Growth loop
Share kit
Scenario-led draft for ai-assist-observability-audit, ready for a manual X post.
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
Optional reply with install command
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
Listing source
Registry indexed
This listing was indexed from public sources and is not marked official until a maintainer claim is approved.
- Creator
- jparkerweb
- Indexed by
- OpenAgentSkill community index
Attribution links to the public repository or creator profile. Creators can claim the listing to update ownership signals.
Claim this skillOwner claim
Claim this skill listing
This Registry indexed listing is attributed to jparkerweb but is not marked official yet. Claim it to add a verified owner signal and make future launch, install, and audit updates easier to trust.
Creator backlink kit
Add the evidence badges to your README
Show the canonical listing, current trust and audit signals, and real Agent-Proven evidence where developers evaluate the repository.
[](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)Author
jparkerweb
@jparkerweb
Tags
Platform fit
Health signals
- GitHub stars
- 88
- Quality score
- 37/100
- Last GitHub push
- Aug 20, 2026
- Framework hints
- Unknown
- OpenAgentSkill views
- 9
- Install copies
- 0
- Outbound clicks
- 0
Community signal
Share whether this skill looks useful for your agent workflow. Aggregated feedback improves rankings over time.
Trust & safety
Sandbox only
- GitHub adoption88 GitHub starsCHECK
- Stars/forks activity88 stars, 12 forks; issue activity unavailable in current metadataCHECK
- Recent maintenance2d since pushPASS
- License clarityUnknownCHECK
- README/SKILL.md completenessPublic metadata needs stronger README/SKILL.md contextINFO
- Dependency/runtime riskno major dependency risk hints in public metadataPASS
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