Completion Verification

Verify all phases are complete with weighted quality scoring before allowing session exit.

509 stars

Best use case

Completion Verification is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Verify all phases are complete with weighted quality scoring before allowing session exit.

Teams using Completion Verification should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/completion-verification/SKILL.md --create-dirs "https://raw.githubusercontent.com/a5c-ai/babysitter/main/library/methodologies/planning-with-files/skills/completion-verification/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/completion-verification/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How Completion Verification Compares

Feature / AgentCompletion VerificationStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Verify all phases are complete with weighted quality scoring before allowing session exit.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# Completion Verification

Verify all phases are complete with weighted quality scoring before allowing session exit.

## Agent
Completion Verifier - `pwf-completion-verifier`

## Workflow
1. Read all three planning files in parallel
2. Parse checkbox completion state from task_plan.md
3. Cross-reference plan, findings, and progress for consistency
4. Check error resolution status
5. Calculate weighted quality score (phases 40%, errors 25%, findings 20%, continuity 15%)
6. Generate recommendations if threshold not met
7. Write verification report to progress.md

## Inputs
- `projectPath` - Root path for planning files
- `taskDescription` - Original task description
- `qualityThreshold` - Minimum score to pass (default: 80)
- `strictMode` - Require 100% checkbox completion (default: false)

## Outputs
- Quality score with component breakdown
- Phase completion report
- Unresolved error list
- Prioritized improvement recommendations

## Process Files
- `planning-orchestrator.js` - Completion assessment and final verification
- `planning-verification.js` - Full verification pipeline

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