project-stage-detect

Donchitos/Claude-Code-Game-Studios · updated Apr 16, 2026

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$npx skills add https://github.com/Donchitos/Claude-Code-Game-Studios --skill project-stage-detect
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summary

### Project Stage Detect

  • name: project-stage-detect
  • description: "Automatically analyze project state, detect stage, identify gaps, and recommend next steps based on existing artifacts. Use when user asks 'where are we in development', 'what stage are
  • argument-hint: "[optional: role filter like 'programmer' or 'designer']"
skill.md
name
project-stage-detect
description
"Automatically analyze project state, detect stage, identify gaps, and recommend next steps based on existing artifacts. Use when user asks 'where are we in development', 'what stage are we in', 'full project audit'."
argument-hint
"[optional: role filter like 'programmer' or 'designer']"
user-invocable
true
allowed-tools
Read, Glob, Grep, Bash, Write
model
haiku # Read-only diagnostic skill — no specialist agent delegation needed

Project Stage Detection

This skill scans your project to determine its current development stage, completeness of artifacts, and gaps that need attention. It's especially useful when:

  • Starting with an existing project
  • Onboarding to a codebase
  • Checking what's missing before a milestone
  • Understanding "where are we?"

Workflow

1. Scan Key Directories

Analyze project structure and content:

Design Documentation (design/):

  • Count GDD files in design/gdd/*.md
  • Check for game-concept.md, game-pillars.md, systems-index.md
  • If systems-index.md exists, count total systems vs. designed systems
  • Analyze completeness (Overview, Detailed Design, Edge Cases, etc.)
  • Count narrative docs in design/narrative/
  • Count level designs in design/levels/

Source Code (src/):

  • Count source files (language-agnostic)
  • Identify major systems (directories with 5+ files)
  • Check for core/, gameplay/, ai/, networking/, ui/ directories
  • Estimate lines of code (rough scale)

Production Artifacts (production/):

  • Check for active sprint plans
  • Look for milestone definitions
  • Find roadmap documents

Prototypes (prototypes/):

  • Count prototype directories
  • Check for READMEs (documented vs undocumented)
  • Assess if prototypes are archived or active

Architecture Docs (docs/architecture/):

  • Count ADRs (Architecture Decision Records)
  • Check for overview/index documents

Tests (tests/):

  • Count test files
  • Estimate test coverage (rough heuristic)

2. Classify Project Stage

Based on scanned artifacts, determine stage. Check production/stage.txt first — if it exists, use its value (explicit override from /gate-check). Otherwise, auto-detect using these heuristics (check from most-advanced backward):

StageIndicators
ConceptNo game concept doc, brainstorming phase
Systems DesignGame concept exists, systems index missing or incomplete
Technical SetupSystems index exists, engine not configured
Pre-ProductionEngine configured, src/ has <10 source files
Productionsrc/ has 10+ source files, active development
PolishExplicit only (set by /gate-check Production → Polish gate)
ReleaseExplicit only (set by /gate-check Polish → Release gate)

3. Collaborative Gap Identification

DO NOT just list missing files. Instead, ask clarifying questions:

  • "I see combat code (src/gameplay/combat/) but no design/gdd/combat-system.md. Was this prototyped first, or should we reverse-document?"
  • "You have 15 ADRs but no architecture overview. Should I create one to help new contributors?"
  • "No sprint plans in production/. Are you tracking work elsewhere (Jira, Trello, etc.)?"
  • "I found a game concept but no systems index. Have you decomposed the concept into individual systems yet, or should we run /map-systems?"
  • "Prototypes directory has 3 projects with no READMEs. Were these experiments, or do they need documentation?"

4. Generate Stage Report

Use template: .claude/docs/templates/project-stage-report.md

Report structure:

# Project Stage Analysis

**Date**: [date]
**Stage**: [Concept/Systems Design/Technical Setup/Pre-Production/Production/Polish/Release]
**Stage Confidence**: [PASS — clearly detected / CONCERNS — ambiguous signals / FAIL — critical gaps block progress]

## Completeness Overview
- Design: [X%] ([N] docs, [gaps])
- Code: [X%] ([N] files, [systems])
- Architecture: [X%] ([N] ADRs, [gaps])
- Production: [X%] ([status])
- Tests: [X%] ([coverage estimate])

## Gaps Identified
1. [Gap description + clarifying question]
2. [Gap description + clarifying question]

## Recommended Next Steps
[Priority-ordered list based on stage and role]

5. Role-Filtered Recommendations (Optional)

If user provided a role argument (e.g., /project-stage-detect programmer):

Programmer:

  • Focus on architecture docs, test coverage, missing ADRs
  • Code-to-docs gaps

Designer:

  • Focus on GDD completeness, missing design sections
  • Prototype documentation

Producer:

  • Focus on sprint plans, milestone tracking, roadmap
  • Cross-team coordination docs

General (no role):

  • Holistic view of all gaps
  • Highest-priority items across domains

6. Request Approval Before Writing

Collaborative protocol:

I've analyzed your project. Here's what I found:

[Show summary]

Gaps identified:
1. [Gap 1 + question]
2. [Gap 2 + question]

Recommended next steps:
- [Priority 1]
- [Priority 2]
- [Priority 3]

May I write the full stage analysis to production/project-stage-report.md?

Wait for user approval before creating the file.


Example Usage

# General project analysis
/project-stage-detect

# Programmer-focused analysis
/project-stage-detect programmer

# Designer-focused analysis
/project-stage-detect designer

Follow-Up Actions

After generating the report, suggest relevant next steps:

  • Concept exists but no systems index?/map-systems to decompose into systems
  • Missing design docs?/reverse-document design src/[system]
  • Missing architecture docs?/architecture-decision or /reverse-document architecture
  • Prototypes need documentation?/reverse-document concept prototypes/[name]
  • No sprint plan?/sprint-plan
  • Approaching milestone?/milestone-review

Collaborative Protocol

This skill follows the collaborative design principle:

  1. Question First: Ask about gaps, don't assume
  2. Present Options: "Should I create X, or is it tracked elsewhere?"
  3. User Decides: Wait for direction
  4. Show Draft: Display report summary
  5. Get Approval: "May I write to production/project-stage-report.md?"

Never silently write files. Always show findings and ask before creating artifacts.

how to use project-stage-detect

How to use project-stage-detect on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add project-stage-detect
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/Donchitos/Claude-Code-Game-Studios --skill project-stage-detect

The skills CLI fetches project-stage-detect from GitHub repository Donchitos/Claude-Code-Game-Studios and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/project-stage-detect

Reload or restart Cursor to activate project-stage-detect. Access the skill through slash commands (e.g., /project-stage-detect) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

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Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

Improve work quality by 30-40% with less effort

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client with skill support
  • Clear understanding of task or problem to solve
  • Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Installation Steps

  1. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 5.Integrate into regular workflow if valuable

Common Pitfalls

  • Expecting perfect results without iteration
  • Not providing enough context in prompts
  • Using skill for tasks outside its intended scope
  • Accepting outputs without review and validation

Best Practices

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • Don't use without understanding skill limitations
  • Don't skip validation of outputs
  • Don't share sensitive information in prompts
  • Don't expect skill to replace human judgment

💡 Pro Tips

  • Be specific about desired format and style
  • Ask for multiple options to choose from
  • Request explanations to understand reasoning
  • Combine AI efficiency with human expertise

When to Use This

✓ Use When

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ Avoid When

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.731 reviews
  • Shikha Mishra· Dec 20, 2024

    Solid pick for teams standardizing on skills: project-stage-detect is focused, and the summary matches what you get after install.

  • Kaira Okafor· Dec 16, 2024

    project-stage-detect has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Ganesh Mohane· Dec 12, 2024

    Useful defaults in project-stage-detect — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Ishan Gonzalez· Nov 11, 2024

    project-stage-detect fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Sakshi Patil· Nov 3, 2024

    project-stage-detect is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Chaitanya Patil· Oct 22, 2024

    Keeps context tight: project-stage-detect is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Ishan Abebe· Sep 21, 2024

    Useful defaults in project-stage-detect — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Rahul Santra· Sep 13, 2024

    We added project-stage-detect from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Lucas Smith· Sep 13, 2024

    project-stage-detect has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Yuki Gonzalez· Sep 5, 2024

    I recommend project-stage-detect for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

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