scope-check

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

MDX-style export adds YAML metadata + attribution linking explainx.ai and this canonical listing URL.

$npx skills add https://github.com/Donchitos/Claude-Code-Game-Studios --skill scope-check
0 commentsdiscussion
summary

### Scope Check

  • description: "Analyze a feature or sprint for scope creep by comparing current scope against the original plan. Flags additions, quantifies bloat, and recommends cuts. Use when user says 'any scope cr
  • argument-hint: "[feature-name or sprint-N]"
  • allowed-tools: Read, Glob, Grep, Bash
skill.md
name
scope-check
description
"Analyze a feature or sprint for scope creep by comparing current scope against the original plan. Flags additions, quantifies bloat, and recommends cuts. Use when user says 'any scope creep', 'scope review', 'are we staying in scope'."
argument-hint
"[feature-name or sprint-N]"
user-invocable
true
allowed-tools
Read, Glob, Grep, Bash
model
haiku

Scope Check

This skill is read-only — it reports findings but writes no files.

Compares original planned scope against current state to detect, quantify, and triage scope creep.

Argument: $ARGUMENTS[0] — feature name, sprint number, or milestone name.


Phase 1: Find the Original Plan

Locate the baseline scope document for the given argument:

  • Feature name → read design/gdd/[feature].md or matching file in design/
  • Sprint number (e.g., sprint-3) → read production/sprints/sprint-03.md or similar
  • Milestone → read production/milestones/[name].md

If the document is not found, report the missing file and stop. Do not proceed without a baseline to compare against.


Phase 2: Read the Current State

Check what has actually been implemented or is in progress:

  • Scan the codebase for files related to the feature/sprint
  • Read git log for commits related to this work (git log --oneline --since=[start-date])
  • Check for TODO/FIXME comments that indicate unfinished scope additions
  • Check active sprint plan if the feature is mid-sprint

Phase 3: Compare Original vs Current Scope

Produce the comparison report:

## Scope Check: [Feature/Sprint Name]
Generated: [Date]

### Original Scope
[List of items from the original plan]

### Current Scope
[List of items currently implemented or in progress]

### Scope Additions (not in original plan)
| Addition | Source | When | Justified? | Effort |
|----------|--------|------|------------|--------|
| [item] | [commit/person] | [date] | [Yes/No/Unclear] | [S/M/L] |

### Scope Removals (in original but dropped)
| Removed Item | Reason | Impact |
|-------------|--------|--------|
| [item] | [why removed] | [what's affected] |

### Bloat Score
- Original items: [N]
- Current items: [N]
- Items added: [N] (+[X]%)
- Items removed: [N]
- Net scope change: [+/-N] ([X]%)

### Risk Assessment
- **Schedule Risk**: [Low/Medium/High] — [explanation]
- **Quality Risk**: [Low/Medium/High] — [explanation]
- **Integration Risk**: [Low/Medium/High] — [explanation]

### Recommendations
1. **Cut**: [Items that should be removed to stay on schedule]
2. **Defer**: [Items that can move to a future sprint/version]
3. **Keep**: [Additions that are genuinely necessary]
4. **Flag**: [Items that need a decision from producer/creative-director]

Phase 4: Verdict

Assign a canonical verdict based on net scope change:

Net ChangeVerdictMeaning
≤10%PASSOn Track — within acceptable variance
10–25%CONCERNSMinor Creep — manageable with targeted cuts
25–50%FAILSignificant Creep — must cut or formally extend timeline
>50%FAILOut of Control — stop, re-plan, escalate to producer

Output the verdict prominently:

**Scope Verdict: [PASS / CONCERNS / FAIL]**
Net change: [+X%] — [On Track / Minor Creep / Significant Creep / Out of Control]

Phase 5: Next Steps

After presenting the report, offer concrete follow-up:

  • PASS → no action required. Suggest re-running before next milestone.
  • CONCERNS → offer to identify the 2–3 additions with best cut ratio. Reference /sprint-plan update to formally re-scope.
  • FAIL → recommend escalating to producer. Reference /sprint-plan update for re-planning or /estimate to re-baseline timeline.

Always end with:

"Run /scope-check [name] again after cuts are made to verify the verdict improves."


Rules

  • Scope creep is additions without corresponding cuts or timeline extensions
  • Not all additions are bad — some are discovered requirements. But they must be acknowledged and accounted for
  • When recommending cuts, prioritize preserving the core player experience over nice-to-haves
  • Always quantify scope changes — "it feels bigger" is not actionable, "+35% items" is
how to use scope-check

How to use scope-check 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 scope-check
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 scope-check

The skills CLI fetches scope-check 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/scope-check

Reload or restart Cursor to activate scope-check. Access the skill through slash commands (e.g., /scope-check) 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

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

Accelerate Code Development

Use skill to generate boilerplate code, refactor legacy code, and write tests faster

Example

Generate React component with TypeScript types, styled-components, and comprehensive test suite in minutes

Reduce development time by 40-60% for repetitive coding tasks

Code Review Automation

Systematically review code for bugs, security issues, and style violations

Example

Analyze pull requests for common anti-patterns, suggest performance improvements, flag security vulnerabilities

Catch 70%+ of code issues before human review, improve code quality

Debug Complex Issues

Trace errors through stack traces and identify root causes faster

Example

Analyze error logs, suggest probable causes, recommend fixes with code examples

Cut debugging time by 30-50%, especially for unfamiliar codebases

Learn New Technologies

Get explanations, examples, and best practices for unfamiliar frameworks

Example

Understand Next.js app router, learn Rust ownership, grasp Kubernetes concepts with practical examples

Accelerate learning curve by 2-3x, reduce onboarding time for new tech stacks

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client with skill installation support
  • Basic understanding of programming concepts and version control (Git)
  • Code editor or IDE for testing generated code (VS Code, JetBrains, etc.)
  • Test environment separate from production for validating skill outputs

Time Estimate

15-30 minutes to install and see first useful output

Installation Steps

  1. 1.Install the skill using provided installation command
  2. 2.Verify skill is loaded in Claude Desktop (check ~/.claude/skills directory)
  3. 3.Test skill with simple prompt: 'Help me review this code snippet'
  4. 4.Gradually increase complexity: code generation → refactoring → architecture advice
  5. 5.Review all generated code before committing to repository
  6. 6.Iterate on prompts to improve output quality and relevance
  7. 7.Share effective prompts with team for consistency

Common Pitfalls

  • Blindly trusting generated code without testing—always run tests and manual review
  • Not providing enough context about your project structure and coding standards
  • Expecting perfection on first generation—iteration and refinement are normal
  • Sharing proprietary code or API keys in prompts—maintain confidentiality
  • Over-relying on skill for critical security or business logic code
  • Skipping documentation of why AI-generated code was chosen over alternatives

Best Practices

✓ Do

  • +Always review and test AI-generated code before merging
  • +Provide clear context: language, framework, coding standards, constraints
  • +Use for boilerplate, tests, docs—areas where mistakes are easily caught
  • +Iterate on prompts: start broad, refine with specific requirements
  • +Combine AI suggestions with human judgment and domain expertise
  • +Document successful prompt patterns for team reuse
  • +Keep version control so you can rollback if needed
  • +Use skill for learning and exploration, not production-critical features initially

✗ Don't

  • Don't commit AI code without thorough testing and review
  • Don't expose sensitive code, credentials, or proprietary algorithms
  • Don't use for security-critical code (auth, crypto, payments) without expert review
  • Don't skip peer review process just because AI generated it
  • Don't assume code follows your team's conventions—verify
  • Don't let junior developers skip learning fundamentals by relying solely on AI
  • Don't ignore compiler warnings or test failures in generated code

💡 Pro Tips

  • Describe desired patterns explicitly: 'Use async/await, avoid callbacks'
  • Ask for alternatives: 'Show 3 approaches to solve this, with tradeoffs'
  • Request explanations: 'Explain why this approach is better than X'
  • Use skill for 70% generation + 30% manual refinement for best results
  • Build a prompt library for common patterns (API endpoints, components, tests)
  • Pair program with AI: describe problem → review solution → iterate → refine

When to Use This

✓ Use When

Use coding skills for boilerplate generation, code reviews, refactoring legacy code, writing tests, learning new frameworks, and debugging non-critical issues. Best for repetitive tasks where errors are easy to catch.

✗ Avoid When

Avoid for production security features (auth, encryption, payment processing), complex business logic requiring deep domain knowledge, performance-critical algorithms, or when learning fundamentals is more valuable than speed.

Learning Path

  1. 1Start with simple tasks: generate functions, write tests, explain code
  2. 2Progress to code review: analyze PRs, suggest improvements
  3. 3Advanced: architectural decisions, refactoring strategies, performance optimization
  4. 4Expert: use for exploring new paradigms, researching best practices, mentoring juniors

Integration

  • VS Code
  • JetBrains IDEs
  • Cursor
  • GitHub Copilot
  • Git workflows

Discussion

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

Ratings

4.543 reviews
  • Hassan Diallo· Dec 28, 2024

    scope-check fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Shikha Mishra· Dec 16, 2024

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

  • Min Gupta· Dec 16, 2024

    We added scope-check from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Ganesh Mohane· Dec 8, 2024

    scope-check fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Camila Haddad· Dec 8, 2024

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

  • Ren Huang· Dec 8, 2024

    Registry listing for scope-check matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Sakshi Patil· Nov 27, 2024

    Registry listing for scope-check matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Dev Liu· Nov 27, 2024

    scope-check fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Camila Yang· Nov 19, 2024

    Registry listing for scope-check matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Xiao Nasser· Nov 7, 2024

    scope-check reduced setup friction for our internal harness; good balance of opinion and flexibility.

showing 1-10 of 43

1 / 5