evidence-before-after Skill
Use to build the before-and-after visual evidence for a Zava Learning incident. First classify the fault, then render the ONE visual that actually explains what changed — a before/after path or topology diagram for connectivity/config/RBAC faults, or time-series comparison charts for performance/availability faults — p Published by microsoft in sre-agent.
What is evidence-before-after Skill?
Use to build the before-and-after visual evidence for a Zava Learning incident. First classify the fault, then render the ONE visual that actually explains what changed — a before/after path or topology diagram for connectivity/config/RBAC faults, or time-series comparison charts for performance/availability faults — p Published by microsoft in sre-agent. This profile combines repository metadata with install, compatibility, and usage signals so developers can quickly decide whether it fits their agent workflow before opening the source repository.
Automated repository signals based on public metadata such as recency, license, installation evidence, and adoption. These are not a security audit or endorsement.
Key capabilities
- Includes SKILL.md support
- Reusable instructions support
- Data analysis
- Data analysis use cases
Technical details
- Install or run with Copy skill directory
When to use evidence-before-after Skill
- Use it for data analysis.
Built with
Editorial notes
Source
- Creator: microsoft
- Repository: microsoft/sre-agent
- Skill file: labs/zava-learning/sre-config/agent-config/skills/evidence-before-after/SKILL.md
What it does
Use to build the before-and-after visual evidence for a Zava Learning incident. First classify the fault, then render the ONE visual that actually explains what changed — a before/after path or topology diagram for connectivity/config/RBAC faults, or time-series comparison charts for performance/availability faults — p
Skill instructions
Zava Learning — Before / After Evidence Prove impact and recovery with the right visual for the fault — not a chart by reflex. Resource Group: @@RG@@. Services: learner-portal, course-api, assessment-api. Retrieve zava-brand and zava-report-template with SearchMemory and apply the house style. Use the windows and root cause confirmed by rca-analysis. Step 1 — Decide the visual FIRST (do not skip) Classify what actually changed, then pick the visual that explains that. Plotting a smooth metric for a binary/config fault (e.g. "availability before/after" for an NSG block) is misleading and adds no insight — don't do it. | Fault class | What changed | Primary visual | Secondary (only if telemetry shows it) | |---|---|---|---| | Connectivity / config / NSG / App Gateway probe / RBAC | a path or permission was closed → open (binary) | before→after path/topology diagram (ASCII or Mermaid) + a config-state delta table | one short recovery curve (e.g. 502-rate → 0) | | Performance / latency / s
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Frequently asked questions
What is evidence-before-after?
evidence-before-after is a open-source AI agent skill with Copy skill directory. Use to build the before-and-after visual evidence for a Zava Learning incident.
Who is evidence-before-after best for?
evidence-before-after is best for reusing agent instructions, scripts, and references, data analysis workflows.
How do I install evidence-before-after?
Install or run evidence-before-after using Copy skill directory. Check evidence-before-after for the latest setup command.
Is evidence-before-after actively maintained?
evidence-before-after may need a closer maintenance check before production use.
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