vibe-gap-analysis
SkillDev toolsAssesses production readiness or audits a codebase against its specs. Supports quick static mode, deep 17-dimension audit, or single-dimension focus.
Instructions available. Your AI can read the instructions. Execution depends on the setup they require.
Account requirements not reviewed. Check the skill instructions before use; ahel provides instructions and does not run this skill.
Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.
Then ask your AI: use the vibe-gap-analysis skill
What this skill tells your AI
The instructions your AI receives, as published by ash1794/vibe-engineering in plugins/vibe-engineering/skills/vibe-gap-analysis/SKILL.md and read by ahel’s review.
Cynical gap analysis comparing specs/architecture to actual implementation. Three modes from fast to exhaustive. Works with any project that has architecture docs and implementation code.
When to Use This Skill
- Before launching to production
- After a major refactor to verify nothing was lost
- When inheriting a codebase and need to assess completeness
- Periodic production readiness audits
- When stakeholders ask "how done are we?"
When NOT to Use This Skill
- Greenfield projects with no specs yet (write specs first)
- Simple bug fixes or feature additions
- Frontend-only or design-only reviews
Usage
/vibe-gap-analysis # Quick static (5 structural dimensions)
/vibe-gap-analysis --deep # Full 17-dimension audit with parallel agents
/vibe-gap-analysis --dim N # Single dimension deep-dive (1-17)
/vibe-gap-analysis --dim 1,4,9 # Multiple specific dimensions
Modes
Quick Static (default)
Fast, single-agent structural audit. No subagents dispatched.
- Read architecture/design docs in
docs/or similar - Read implementation code in
src/,internal/,lib/etc. - Compare implementation against architecture doc section by section
- Cover dimensions 1-5 (structural):
- Dim 1: Spec Compliance — check specs against implementation
- Dim 2: Backend Code Quality — test coverage, error handling, lint issues
- Dim 3: Frontend Completeness — UI components, routes, test coverage
- Dim 4: Deployment & Ops — deploy scripts, CI/CD, Docker, TLS
- Dim 5: Architecture Integrity — design pattern compliance, component boundaries
- Produce structured gap report: component, expected status, actual status, % complete, action items
- Save to
docs/plans/gap-analysis-$(date +%Y%m%d).md - Commit with
docs: gap analysis $(date +%Y%m%d)
Deep (--deep)
Full 17-dimension audit using parallel subagents where the harness supports them (Claude Code, Codex, and Gemini CLI all can). Without subagents, run the dimensions sequentially. Exhaustive production readiness assessment.
Dispatch parallel agents in 3 rounds. Subagents inherit the session's model by default; if the harness lets you choose, a faster or cheaper tier is fine for the scanning rounds, but keep the most capable model for merging and scoring.
Round 1 — Structural (5 agents):
- Dim 1: Spec Compliance
- Dim 2: Backend Code Quality
- Dim 3: Frontend Completeness
- Dim 4: Deployment & Ops
- Dim 5: Architecture Integrity
Round 2 — Runtime Execution (7 agents):
- Dim 6: Database Concurrency & Integrity
- Dim 7: Failure Cascades & Recovery
- Dim 8: E2E Data Flow
- Dim 9: Security & Input Validation
- Dim 10: Observability & Alerting
- Dim 11: Data Durability & Backup
- Dim 12: Cost/Resource Explosion Safeguards
Round 3 — Business & Product Maturity (5 agents):
- Dim 13: Performance & Load Testing
- Dim 14: Multi-Tenancy / User Isolation
- Dim 15: Privacy & Compliance (GDPR/CCPA)
- Dim 16: Supply Chain Security
- Dim 17: Operational Readiness
Each agent gets this prompt template:
You are auditing [project] for production readiness.
**Your dimension:** [Dimension N — Name]
**Scope:** [Description]
**Previous gap analysis:** [path, if exists]
Instructions:
1. Read all relevant source files for your dimension
2. For each finding: severity (CRITICAL/HIGH/MEDIUM/LOW), location (file:line), issue, fix, effort
3. Score your dimension 0-100
4. Return findings as structured markdown
Be pedantic and skeptical, and calibrate severity to this project's actual stakes.
Report only findings you can point to with file:line evidence; mark anything inferred as "unverified".
After all rounds:
- Merge findings, deduplicate across dimensions
- Build production readiness scorecard (17 dimensions)
- Build findings-by-system-area cross-reference
- Build recommended action plan (phased)
- Save and commit
Single Dimension (--dim N)
Deep-dive into specific dimensions. One agent per requested dimension.
After completion, update only the audited dimensions in the existing gap analysis doc.
Dimension Reference
| # | Dimension | Type | What to Audit |
|---|---|---|---|
| 1 | Spec Compliance | Structural | Specs vs implementation |
| 2 | Backend Code Quality | Structural | Tests, errors, lint, races |
| 3 | Frontend Completeness | Structural | UI, routes, stores, tests |
| 4 | Deployment & Ops | Structural | Deploy, CI/CD, Docker, TLS |
| 5 | Architecture Integrity | Structural | Design patterns, boundaries |
| 6 | Database Concurrency | Runtime | Transactions, locks, backups |
| 7 | Failure Cascades | Runtime | Recovery, circuit breakers |
| 8 | E2E Data Flow | Runtime | API contracts, idempotency |
| 9 | Security | Runtime | Input validation, injection, secrets |
| 10 | Observability | Runtime | Logging, alerting, metrics |
| 11 | Data Durability | Runtime | RPO/RTO, backups, replication |
| 12 | Cost/Resource Control | Runtime | Budgets, limits, rate limiting |
| 13 | Performance & Load | Business | Timeouts, benchmarks, limits |
| 14 | Multi-Tenancy | Business | User isolation, data scoping |
| 15 | Privacy & Compliance | Business | GDPR, PII, consent, encryption |
| 16 | Supply Chain | Business | Dep pinning, vuln scanning, builds |
| 17 | Operational Readiness | Business | Runbooks, SLOs, incident response |
Output Format
All modes produce:
- Executive summary with total findings count
- Audit dimensions table with scores
- CRITICAL findings (full detail)
- HIGH findings (full detail)
- MEDIUM findings (one-line each)
- LOW findings (one-line each)
- Findings by system area (cross-reference)
- Recommended action plan (phased)
- Production readiness scorecard
Signals
- GitHub stars
- 85
- Forks
- 20
- Last commit
- Oct 2026
Advanced
- Item type
- skill
- Key
vibe-gap-analysis- Source
- github.com/ash1794/vibe-engineering
github.com/ash1794/vibe-engineering
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