home / skills / athola / claude-night-market / feature-review

feature-review skill

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This skill helps you prioritize feature ideas using hybrid RICE and WSJF scoring and creates GitHub issues for accepted suggestions.

npx playbooks add skill athola/claude-night-market --skill feature-review

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SKILL.md

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---
name: feature-review
description: 'Feature review and prioritization with RICE/WSJF/Kano scoring. Creates
  GitHub issues for suggestions.


  feature review, prioritization, RICE, WSJF, roadmap, backlog

  Use when: reviewing features or suggesting new features

  DO NOT use when: evaluating single feature scope - use scope-guard.'
category: workflow-methodology
tags:
- feature-review
- prioritization
- RICE
- WSJF
- Kano
- roadmap
- backlog
dependencies:
- imbue:scope-guard
- imbue:review-core
tools:
- gh (GitHub CLI)
usage_patterns:
- feature-inventory
- prioritization-scoring
- suggestion-generation
- github-integration
complexity: intermediate
estimated_tokens: 3500
modules:
- modules/scoring-framework.md
- modules/classification-system.md
- modules/tradeoff-dimensions.md
- modules/configuration.md
---
## Table of Contents

- [Philosophy](#philosophy)
- [When to Use](#when-to-use)
- [When NOT to Use](#when-not-to-use)
- [Quick Start](#quick-start)
- [1. Inventory Current Features](#1-inventory-current-features)
- [2. Score and Classify](#2-score-and-classify)
- [3. Generate Suggestions](#3-generate-suggestions)

## Verification

Run `make test-feature-review` to verify scoring logic after changes.
- [4. Upload to GitHub](#4-upload-to-github)
- [Workflow](#workflow)
- [Phase 1: Feature Discovery (`feature-review:inventory-complete`)](#phase-1:-feature-discovery-(feature-review:inventory-complete))
- [Phase 2: Classification (`feature-review:classified`)](#phase-2:-classification-(feature-review:classified))
- [Phase 3: Scoring (`feature-review:scored`)](#phase-3:-scoring-(feature-review:scored))
- [Phase 4: Tradeoff Analysis (`feature-review:tradeoffs-analyzed`)](#phase-4:-tradeoff-analysis-(feature-review:tradeoffs-analyzed))
- [Phase 5: Gap Analysis & Suggestions (`feature-review:suggestions-generated`)](#phase-5:-gap-analysis-&-suggestions-(feature-review:suggestions-generated))
- [Phase 6: GitHub Integration (`feature-review:issues-created`)](#phase-6:-github-integration-(feature-review:issues-created))
- [Configuration](#configuration)
- [Configuration File](#configuration-file)
- [Guardrails](#guardrails)
- [Required TodoWrite Items](#required-todowrite-items)
- [Integration Points](#integration-points)
- [Output Format](#output-format)
- [Feature Inventory Table](#feature-inventory-table)
- [Suggestion Report](#suggestion-report)
- [Feature Suggestions](#feature-suggestions)
- [High Priority (Score > 2.5)](#high-priority-(score->-25))
- [Related Skills](#related-skills)
- [Reference](#reference)


# Feature Review

Review implemented features and suggest new ones using evidence-based prioritization. Create GitHub issues for accepted suggestions.

## Philosophy

Feature decisions rely on data. Every feature involves tradeoffs that require evaluation. This skill uses hybrid RICE+WSJF scoring with Kano classification to prioritize work and generates actionable GitHub issues for accepted suggestions.

## When To Use

- Roadmap reviews (sprint planning, quarterly reviews).
- Retrospective evaluations.
- Planning new development cycles.

## When NOT To Use

- Emergency bug fixes.
- Simple documentation updates.
- Active implementation (use `scope-guard`).

## Quick Start

### 1. Inventory Current Features

Discover and categorize existing features:
```bash
/feature-review --inventory
```

### 2. Score and Classify

Evaluate features against the prioritization framework:
```bash
/feature-review
```

### 3. Generate Suggestions

Review gaps and suggest new features:
```bash
/feature-review --suggest
```

### 4. Upload to GitHub

Create issues for accepted suggestions:
```bash
/feature-review --suggest --create-issues
```

## Workflow

### Phase 1: Feature Discovery (`feature-review:inventory-complete`)

Identify features by analyzing:

1. **Code artifacts**: Entry points, public APIs, and configuration surfaces.
2. **Documentation**: README lists, CHANGELOG entries, and user docs.
3. **Git history**: Recent feature commits and branches.

**Output:** Feature inventory table.

### Phase 2: Classification (`feature-review:classified`)

Classify each feature along two axes:

**Axis 1: Proactive vs Reactive**

| Type | Definition | Examples |
|------|------------|----------|
| **Proactive** | Anticipates user needs. | Suggestions, prefetching. |
| **Reactive** | Responds to explicit input. | Form handling, click actions. |

**Axis 2: Static vs Dynamic**

| Type | Update Pattern | Storage Model |
|------|---------------|---------------|
| **Static** | Incremental, versioned. | File-based, cached. |
| **Dynamic** | Continuous, streaming. | Database, real-time. |

See [classification-system.md](modules/classification-system.md) for details.

### Phase 3: Scoring (`feature-review:scored`)

Apply hybrid RICE+WSJF scoring:

```
Feature Score = Value Score / Cost Score

Value Score = (Reach + Impact + Business Value + Time Criticality) / 4
Cost Score = (Effort + Risk + Complexity) / 3

Adjusted Score = Feature Score * Confidence
```

**Scoring Scale:** Fibonacci (1, 2, 3, 5, 8, 13).

**Thresholds:**
- **> 2.5**: High priority.
- **1.5 - 2.5**: Medium priority.
- **< 1.5**: Low priority.

See [scoring-framework.md](modules/scoring-framework.md) for the framework.

### Phase 4: Tradeoff Analysis (`feature-review:tradeoffs-analyzed`)

Evaluate each feature across quality dimensions:

| Dimension | Question | Scale |
|-----------|----------|-------|
| **Quality** | Does it deliver correct results? | 1-5 |
| **Latency** | Does it meet timing requirements? | 1-5 |
| **Token Usage** | Is it context-efficient? | 1-5 |
| **Resource Usage** | Is CPU/memory reasonable? | 1-5 |
| **Redundancy** | Does it handle failures gracefully? | 1-5 |
| **Readability** | Can others understand it? | 1-5 |
| **Scalability** | Will it handle 10x load? | 1-5 |
| **Integration** | Does it play well with others? | 1-5 |
| **API Surface** | Is it backward compatible? | 1-5 |

See [tradeoff-dimensions.md](modules/tradeoff-dimensions.md) for criteria.

### Phase 5: Gap Analysis & Suggestions (`feature-review:suggestions-generated`)

1. **Identify gaps**: Missing Kano basics.
2. **Surface opportunities**: High-value, low-effort features.
3. **Flag technical debt**: Features with declining scores.
4. **Recommend actions**: Build, improve, deprecate, or maintain.

### Phase 6: GitHub Integration (`feature-review:issues-created`)

1. Generate issue title and body from suggestions.
2. Apply labels (feature, enhancement, priority/*).
3. Link to related issues.
4. Confirm with user before creation.

## Configuration

Feature-review uses opinionated defaults but allows customization.

### Configuration File

Create `.feature-review.yaml` in project root:

```yaml
# .feature-review.yaml
version: 1

# Scoring weights (must sum to 1.0)
weights:
  value:
    reach: 0.25
    impact: 0.30
    business_value: 0.25
    time_criticality: 0.20
  cost:
    effort: 0.40
    risk: 0.30
    complexity: 0.30

# Score thresholds
thresholds:
  high_priority: 2.5
  medium_priority: 1.5

# Tradeoff dimension weights (0.0 to disable)
tradeoffs:
  quality: 1.0
  latency: 1.0
  token_usage: 1.0
  resource_usage: 0.8
  redundancy: 0.5
  readability: 1.0
  scalability: 0.8
  integration: 1.0
  api_surface: 1.0
```

See [configuration.md](modules/configuration.md) for options.

### Guardrails

These rules apply to all configurations:

1. **Minimum dimensions**: Evaluate at least 5 tradeoff dimensions.
2. **Confidence requirement**: Review scores below 50% confidence.
3. **Breaking change warning**: Require acknowledgment for API surface changes.
4. **Backlog limit**: Limit suggestion queue to 25 items.

## Required TodoWrite Items

1. `feature-review:inventory-complete`
2. `feature-review:classified`
3. `feature-review:scored`
4. `feature-review:tradeoffs-analyzed`
5. `feature-review:suggestions-generated`
6. `feature-review:issues-created` (if requested)

## Integration Points

- **`imbue:scope-guard`**: Provides Worthiness Scores for suggestions.
- **`sanctum:do-issue`**: Prioritizes issues with high scores.
- **`superpowers:brainstorming`**: Evaluates new ideas against existing features.

## Output Format

### Feature Inventory Table

```markdown
| Feature | Type | Data | Score | Priority | Status |
|---------|------|------|-------|----------|--------|
| Auth middleware | Reactive | Dynamic | 2.8 | High | Stable |
| Skill loader | Reactive | Static | 2.3 | Medium | Needs improvement |
```

### Suggestion Report

```markdown
## Feature Suggestions

### High Priority (Score > 2.5)

1. **[Feature Name]** (Score: 2.7)
   - Classification: Proactive/Dynamic
   - Value: High reach
   - Cost: Moderate effort
   - Recommendation: Build in next sprint
```

## Related Skills

- `imbue:scope-guard`: Prevent overengineering.
- `imbue:review-core`: Structured review methodology.
- `sanctum:pr-review`: Code-level feature review.

## Reference

- **[scoring-framework.md](modules/scoring-framework.md)**: RICE+WSJF hybrid.
- **[classification-system.md](modules/classification-system.md)**: Axes definition.
- **[tradeoff-dimensions.md](modules/tradeoff-dimensions.md)**: Quality attributes.
- **[configuration.md](modules/configuration.md)**: Customization options.
## Troubleshooting

### Common Issues

**Command not found**
Ensure all dependencies are installed and in PATH

**Permission errors**
Check file permissions and run with appropriate privileges

**Unexpected behavior**
Enable verbose logging with `--verbose` flag

Overview

This skill performs evidence-based feature review and prioritization using a hybrid RICE+WSJF scoring model with Kano classification. It inventories current features, scores and classifies them, surfaces gaps and high-impact suggestions, and can create GitHub issues for approved items. The output is actionable: inventory tables, prioritized suggestion reports, and issue drafts ready for review.

How this skill works

The skill inspects code artifacts, documentation, and git history to build a feature inventory. It classifies features on proactive/reactive and static/dynamic axes, then applies a hybrid scoring formula (Value/Cost adjusted by Confidence) using Fibonacci scales. It runs tradeoff analysis across quality dimensions, generates feature suggestions from gap analysis, and formats issue titles and bodies for GitHub creation on confirmation.

When to use it

Roadmap planning and sprint prioritization
Quarterly or product-level feature reviews
Post-release retrospectives to reassess feature value
When evaluating a backlog for high-impact, low-effort opportunities
Before creating long-term roadmap tickets

Best practices

Run an inventory pass first to ensure complete coverage of features
Use the provided configuration file to tune weights and thresholds for your product
Score with a small cross-functional group to increase confidence estimates
Evaluate at least five tradeoff dimensions to avoid blind spots
Confirm suggested issues before automated GitHub creation to prevent noise

Example use cases

Reviewing an existing plugin suite to identify high-value enhancements
Prioritizing features for the next sprint using hybrid RICE+WSJF scores
Generating issue drafts for product manager approval and GitHub upload
Running gap analysis to highlight missing Kano basic features
Comparing technical debt items against new feature suggestions during planning

FAQ

Can I customize scoring weights?

Yes. Put a .feature-review.yaml file in the project root to adjust value/cost weights, tradeoff weights, and priority thresholds.

Will it create issues automatically?

It can, but issue creation is confirmable. The skill generates titles, bodies, labels, and related links and asks for confirmation before pushing to GitHub.