Nw Post Mortem FrameworkSAFE
AI agents that guide you from idea to working code, with you in control at every step.
Overview
AI agents that guide you from idea to working code, with you in control at every step.
1a864ec81cdeOBSERVED · 2026-10-14What 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
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.
| Layer | What it checks | Result |
|---|---|---|
| L0 | Provenance & inventory | PASS |
| L1 | Static analysis of the code | NA |
| L2 | Instruction surface (what it tells the agent) | PASS |
| L3 | Class-specific surface | PASS |
| L4 | Behavioural (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.
1a864ec81cdefull audit observations/trust-audit/skill/nwave-ai__nw-post-mortem-framework.json · Report an issue / request a re-scanAudit history
Every audit this skill has had.
| Date | Source | Verdict | Grade | Score | Change |
|---|---|---|---|---|---|
| 2026-10-14 | 1a864ec81cde | SAFE | B | 89 | first audit |
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.