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Vibe Iteration Review

skill-ash1794-vibe-engineering-iteration-review · by ash1794

Performs end-of-iteration review with quality grading, metrics, and trend analysis. Use at the end of each development iteration or sprint.

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Install

$ agentstack add skill-ash1794-vibe-engineering-iteration-review

✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

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About

vibe-iteration-review

What gets measured gets improved. Review every iteration.

When to Use This Skill

  • End of a development sprint or iteration
  • After completing a milestone
  • Before starting the next iteration (retrospective)
  • When the user asks "how did we do?"

When NOT to Use This Skill

  • Mid-iteration (too early, incomplete data)
  • After single small tasks
  • When there's no defined iteration boundary

Steps

  1. Gather data:
  • What was planned for this iteration?
  • What was actually delivered?
  • How many commits? Lines changed? Tests added?
  • Coverage delta? Quality metrics?
  • Known issues introduced?
  1. Grade quality (A-F):
  • A: All planned work delivered, tests pass, no known issues, clean code
  • B: Most work delivered, minor issues, good test coverage
  • C: Core work delivered, some gaps, acceptable quality
  • D: Significant gaps, quality issues, needs rework
  • F: Iteration failed, major rework needed
  1. Compare to previous iterations (if available):
  • Is quality trending up or down?
  • Is velocity improving?
  • Are known issues accumulating?
  1. Extract lessons:
  • What went well?
  • What went poorly?
  • What to change next iteration?

Output Format

Iteration Review: [Iteration Name/Number]

Quality Grade: A/B/C/D/F Planned vs Delivered: X/Y (Z%)

| Metric | This Iteration | Previous | Trend | |--------|---------------|----------|-------| | Commits | X | Y | ↑/↓/→ | | Tests added | X | Y | ↑/↓/→ | | Coverage | X% | Y% | ↑/↓/→ | | Known issues | X | Y | ↑/↓/→ |

Delivered

  • [x] [Task 1]
  • [x] [Task 2]
  • [ ] [Task 3] — deferred because [reason]

Lessons Learned

  1. [What to continue]
  2. [What to change]
  3. [What to stop]

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

Reviews

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Versions

  • v0.1.0 Imported from the upstream source.