feature-status

name	feature-status
description	Report feature maturity and status. Use when asking about project status, feature readiness, or which features are stable/experimental/development
allowed-tools	Bash(python3 .agents/skills/feature-status/report.py )

Feature Status Skill

This skill generates status reports for Project Amp features based on their maturity level. It reads the status field from feature documentation frontmatter and organizes features by maturity.

When to Use This Skill

Use this skill when:

• User asks "What's the project status?"
• User asks "What features are stable/experimental/development?"
• User wants to know "What features are ready for production?"
• User asks "Which features are mature vs experimental?"
• User requests "Show feature maturity levels"
• User asks "What features need documentation updates?" (features with unknown status)
• Auditing features to find missing status fields

How Feature Status Works

The skill:

1. Parses frontmatter: Extracts status field from all docs/features/*.md files
2. Groups by maturity: Organizes features by status level
3. Generates report: Creates formatted tables grouped by status with feature details

Available Commands

Status Report Command

python3 .agents/skills/feature-status/report.py

Generates a comprehensive status report with:

• Features grouped by maturity level (stable, experimental, unstable, development, unknown)
• Unicode tables showing name, type, and description for each feature
• Summary counts by status

Output Format:

Feature Status Report
================================================================================

stable (3)
┌─────────────┬──────────┬────────────────────────────┐
│ Name        │ Type     │ Description                │
├─────────────┼──────────┼────────────────────────────┤
│ feature-a   │ service  │ Stable production feature  │
│ feature-b   │ api      │ Ready for use              │
└─────────────┴──────────┴────────────────────────────┘

experimental (2)
┌─────────────┬──────────┬────────────────────────────┐
│ Name        │ Type     │ Description                │
├─────────────┼──────────┼────────────────────────────┤
│ feature-c   │ feature  │ Under active development   │
└─────────────┴──────────┴────────────────────────────┘

Summary: 3 stable, 2 experimental (5 total)

Use this when: You need an overview of feature maturity across the project.

Query Matching Guidelines

Status-Related Queries

The skill should be invoked for queries about:

• Project status: "What's the status of the project?", "Show me project health"
• Maturity levels: "What features are stable?", "Which features are experimental?"
• Production readiness: "What features are ready for production?", "What can I use in prod?"
• Development progress: "What features are still in development?", "What's being worked on?"
• Documentation audits: "What features are missing status?", "Which features need updates?"

Not Status Queries

Do NOT use this skill for:

• "How does feature X work?" → Use /feature-discovery
• "What features are available?" → Use /feature-discovery
• "Validate feature implementation" → Use /feature-validate
• "Check feature doc format" → Use /feature-fmt-check

Important Guidelines

Pre-approved Commands

These commands can run without user permission:

• python3 .agents/skills/feature-status/report.py - Safe, read-only, no side effects

Status Field Values

The status field in feature frontmatter should be one of:

• stable - Production-ready, well-tested, documented
• experimental - Usable but may change, feedback welcome
• unstable - API may change significantly, use with caution
• development - Under active development, not for production
• Missing/unknown - Flagged in report with ⚠ marker

When to Load Full Feature Docs

After running the status report, if user wants details about specific features:

1. Note which features the user is interested in
2. Use /feature-discovery to load full documentation for those features

Example Workflows

Example 1: User Asks About Project Status

Query: "What's the overall status of the project?"

1. Run python3 .agents/skills/feature-status/report.py
2. Review the generated report
3. Summarize findings: X stable features, Y experimental, Z in development
4. Highlight any features with unknown status that need attention

Example 2: User Asks About Production Readiness

Query: "Which features are ready for production?"

1. Run the status report
2. Extract and list features marked as stable
3. If user wants details, use /feature-discovery to load specific stable features

Example 3: User Audits Documentation

Query: "What features are missing status information?"

1. Run the status report
2. Look for features grouped under "⚠ unknown"
3. List features that need status field added to frontmatter
4. Suggest updating those feature docs

Example 4: User Filters by Maturity Level

Query: "Show me all experimental features"

1. Run the status report
2. Extract features from the "experimental" section
3. Present the list with descriptions
4. If user wants more details, use /feature-discovery to load specific docs

Common Mistakes to Avoid

Anti-patterns

Mistake	Why It's Wrong	Do This Instead
Manually list features by status	List becomes stale	Always run report.py
Guess status from feature name	Inaccurate	Read actual status field
Skip unknown status features	Missing metadata	Highlight for updates
Load all feature docs for status	Bloats context	Use report for overview only

Best Practices

• Run the report script to get current status
• Use report for overview, /feature-discovery for details
• Flag features with unknown status for documentation updates
• Present status grouped by maturity level for clarity

Next Steps

After generating a status report:

1. Present findings - Summarize status distribution to user
2. Identify actions - Note features needing status updates
3. Provide details - Use /feature-discovery if user wants specifics
4. Suggest improvements - Recommend adding status to unknown features