Atlas / Skills / nwave-ai / Nw Post Mortem Framework

Nw Post Mortem FrameworkSAFE

skills/nwave-ai/nw-post-mortem-framework

AI agents that guide you from idea to working code, with you in control at every step.

Verdict
SAFE
Grade
B
Trust score
89 /100
Version
—
Hosts
—
License
MIT
Stars
617
01

Overview

AI agents that guide you from idea to working code, with you in control at every step.

Read from source at commit 1a864ec81cdeOBSERVED · 2026-10-14
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02

What it tells the agent

The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.

---
name: nw-post-mortem-framework
description: Blameless post-mortem structure, incident timeline reconstruction, response evaluation, and organizational learning
user-invocable: false
disable-model-invocation: true
---

# Post-Mortem Framework

## Principles

- **Blameless**: focus on systems/processes, not individuals. People make reasonable decisions given available info.
- **Evidence-based**: every finding backed by logs, metrics, or documented actions
- **Action-oriented**: every finding produces concrete, assigned action item
- **Learning-focused**: capture what worked alongside what failed

## Post-Mortem Document Structure

```markdown
# Post-Mortem: [Incident Title]

**Date**: [incident date]
**Duration**: [start to resolution]
**Severity**: [P0-P3]
**Author**: [analyst]

## Summary
[2-3 sentence overview: what happened, impact, resolution]

## Timeline
| Time | Event | Source |
|------|-------|--------|
| HH:MM | [event] | [log/metric/report] |

## Impact
- Users affected: [number/percentage]
- Duration of impact: [time]
- Business impact: [quantified if possible]
- Systems affected: [list]

## Root Cause Analysis
[5 Whys analysis with evidence at each level]

## Detection and Response
- Time to detect: [duration] -- [how detected]
- Time to respond: [duration] -- [first action]
- Time to mitigate: [duration] -- [mitigation applied]
- Time to resolve: [duration] -- [permanent fix]

## What Went Well
- [positive observations about detection, response, recovery]

## What Could Be Improved
- [areas where detection, response, recovery fell short]

## Action Items
| ID | Action | Owner | Priority | Due Date |
|----|--------|-------|----------|----------|
| 1 | [specific action] | [team/person] | [P0-P3] | [date] |

## Lessons Learned
- [key takeaways for the organization]
```

## Incident Timeline Reconstruction

### Sources
1. Monitoring alerts/dashboards (timestamps) | 2. Deployment logs/CI-CD records
3. Communication channels (Slack, email, incident) | 4. VCS (commits, merges, deploys) | 5. User reports/support tickets

### Quality Checks
Events chronological with verified timestamps | gaps >5 min noted/explained | decision points identified with available info | causal relationships noted

## Response Effectiveness Evaluation

### Detection
Detected by monitoring or users? | Duration onset-to-detection? | Existing alerts relevant? Missing?

### Escalation
Right team at right time? | Procedures followed? | Communication clear to stakeholders?

### Resolution
Mitigation effective? | Rollback considered/viable? | Duration mitigation-to-permanent-fix?

## Organizational Learning

### Knowledge Capture
Document root causes as reusable patterns | update runbooks | share in retrospectives

### Process Improvements
Update monitoring/alerting per detection gaps | revise deployment per rollback effectiveness | strengthen testing for failure scenario

### Action Item Tracking
Every item has owner + due date | track in standups/sprint reviews | verify effectiveness post-deployment
03

Trust audit

SAFEgrade B · trust 89/100 Nothing in the source contradicts what it says it does. Grade A is reserved for packages that have also passed the behavioural sandbox.

LayerWhat it checksResult
L0Provenance & inventoryPASS
L1Static analysis of the codeNA
L2Instruction surface (what it tells the agent)PASS
L3Class-specific surfacePASS
L4Behavioural (sandbox)SKIPPED

What the source does

Filesystem
none-observed
Network
none-observed
Shell
none-observed
Dependencies
pinned
Secrets in source
none-found

Findings (0)

No findings outside the package's declared scope.

Gates applied: no_behavioural_pass.

Audited 2026-10-14 · audit v0.4.1 · source sha 1a864ec81cdefull audit observations/trust-audit/skill/nwave-ai__nw-post-mortem-framework.json · Report an issue / request a re-scan
04

Audit history

Every audit this skill has had.

DateSourceVerdictGradeScoreChange
2026-10-141a864ec81cdeSAFEB89first audit
05

Questions

What does the Nw Post Mortem Framework skill do?

AI agents that guide you from idea to working code, with you in control at every step.

Is Nw Post Mortem Framework safe to install?

The audit found nothing in the source that contradicts what it says it does, and graded it B (89/100). Grade A is held back for packages that have also passed a sandboxed behavioural run, which is why a clean skill reads B.

What can Nw Post Mortem Framework access on my machine?

The audit observed no filesystem, network or shell use at all in its source.

How current is this page?

The grade is for one exact copy of the source (1a864ec81cde), read on 2026-10-14. The repository is watched, and a new audit runs when it changes — this is the first audit.

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