Nexus devops obs
SEO
npx -y skills add Shuwanito/SkillsMP --skill nexus-devops-obsAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
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- no licenseNo license file was found in the repository. Code published without one is not open source by default, so using it at work is a question for whoever answers licensing questions where you are.
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What its author says it does
Copied from the file, not written here
Predictive observability engineering agent. Use when you need cognitive tracing, SLO/SLA monitoring, predictive alerting, chaos engineering, or to eliminate observability blind spots and noisy alerts. Designs proactive monitoring that detects issues before they impact users.
The file declares its own license as proprietary. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.
SKILL.md
1.6 KB, 212 tokens by cl100k_base, as published. Nobody here has run it
ObservaBot
Capabilities
- Cognitive tracing design for distributed systems
- SLO/SLA definition, monitoring, and burn-rate alerting
- Predictive alerting using anomaly detection
- Chaos engineering experiment design and execution
- Observability blind spot identification and remediation
- Alert noise reduction and signal-to-noise optimization
Workflow
- Audit current observability stack for blind spots and noisy alerts
- Define or refine SLOs/SLAs aligned with business objectives
- Research predictive alerting and cognitive tracing techniques
- Design tracing and monitoring improvements
- Propose chaos engineering experiments to validate resilience
- Optimize alert rules to reduce noise and improve signal
- Document observability recommendations in shared memory
Guidelines
- Never modify target application code directly
- All proposals require peer review
- Every SLO must have a corresponding error budget and burn-rate alert
- Prefer predictive alerts over reactive threshold-based alerts
- Validate observability changes with chaos engineering before rollout
Gives 0 of the 12 instructions most monitoring observability skills give in 212 tokens
Counted across 481 of the 483 authors here whose files we hold, read 2026-08-06
- link every alert to a runbookin 43 of 481, across 35 files
- use structured json loggingin 36 of 481, across 31 files
- alert on user-facing symptomsin 20 of 481, across 15 files
- emit structured JSON logs with stable event namesin 18 of 481, across 13 files
- propagate trace context across boundariesin 16 of 481
- use histograms for latency trackingin 14 of 481, across 9 files
- use OpenTelemetry for distributed tracingin 13 of 481, across 8 files
- include a correlation ID on every log linein 13 of 481, across 8 files
- Define service level objectivesin 10 of 481, across 7 files
- Call useAzureMonitor before importing other modulesin 9 of 481, across 2 files
- stop and ask for clarification if inputs are missingin 9 of 481, across 2 files
- define on-call questions before adding telemetryin 9 of 481, across 4 files
Said here and by no other author read
- audit current observability stack for blind spots and noisy alerts
- define or refine SLOs and SLAs
- research predictive alerting and cognitive tracing techniques
- design tracing and monitoring improvements
- propose chaos engineering experiments
- optimize alert rules to reduce noise
Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.