estimate

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 estimate
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summary

### Estimate

  • description: "Estimates task effort by analyzing complexity, dependencies, historical velocity, and risk factors. Produces a structured estimate with confidence levels."
  • argument-hint: "[task-description]"
  • allowed-tools: Read, Glob, Grep
skill.md
name
estimate
description
"Estimates task effort by analyzing complexity, dependencies, historical velocity, and risk factors. Produces a structured estimate with confidence levels."
argument-hint
"[task-description]"
user-invocable
true
allowed-tools
Read, Glob, Grep

Phase 1: Understand the Task

Read the task description from the argument. If the description is too vague to estimate meaningfully, ask for clarification before proceeding.

Read CLAUDE.md for project context: tech stack, coding standards, architectural patterns, and any estimation guidelines.

Read relevant design documents from design/gdd/ if the task relates to a documented feature or system.


Phase 2: Scan Affected Code

Identify files and modules that would need to change:

  • Assess complexity (size, dependency count, cyclomatic complexity)
  • Identify integration points with other systems
  • Check for existing test coverage in the affected areas
  • Read past sprint data from production/sprints/ for similar completed tasks and historical velocity

Phase 3: Analyze Complexity Factors

Code Complexity:

  • Lines of code in affected files
  • Number of dependencies and coupling level
  • Whether this touches core/engine code vs leaf/feature code
  • Whether existing patterns can be followed or new patterns are needed

Scope:

  • Number of systems touched
  • New code vs modification of existing code
  • Amount of new test coverage required
  • Data migration or configuration changes needed

Risk:

  • New technology or unfamiliar libraries
  • Unclear or ambiguous requirements
  • Dependencies on unfinished work
  • Cross-system integration complexity
  • Performance sensitivity

Phase 4: Generate the Estimate

## Task Estimate: [Task Name]
Generated: [Date]

### Task Description
[Restate the task clearly in 1-2 sentences]

### Complexity Assessment

| Factor | Assessment | Notes |
|--------|-----------|-------|
| Systems affected | [List] | [Core, gameplay, UI, etc.] |
| Files likely modified | [Count] | [Key files listed below] |
| New code vs modification | [Ratio] | |
| Integration points | [Count] | [Which systems interact] |
| Test coverage needed | [Low / Medium / High] | |
| Existing patterns available | [Yes / Partial / No] | |

**Key files likely affected:**
- `[path/to/file1]` -- [what changes here]

### Effort Estimate

| Scenario | Days | Assumption |
|----------|------|------------|
| Optimistic | [X] | Everything goes right, no surprises |
| Expected | [Y] | Normal pace, minor issues, one round of review |
| Pessimistic | [Z] | Significant unknowns surface, blocked for a day |

**Recommended budget: [Y days]**

### Confidence: [High / Medium / Low]

[Explain which factors drive the confidence level for this specific task.]

### Risk Factors

| Risk | Likelihood | Impact | Mitigation |
|------|-----------|--------|------------|

### Dependencies

| Dependency | Status | Impact if Delayed |
|-----------|--------|-------------------|

### Suggested Breakdown

| # | Sub-task | Estimate | Notes |
|---|----------|----------|-------|
| 1 | [Research / spike] | [X days] | |
| 2 | [Core implementation] | [X days] | |
| 3 | [Testing and validation] | [X days] | |
| | **Total** | **[Y days]** | |

### Notes and Assumptions
- [Key assumption that affects the estimate]
- [Any caveats about scope boundaries]

Output the estimate with a brief summary: recommended budget, confidence level, and the single biggest risk factor.

This skill is read-only — no files are written. Verdict: COMPLETE — estimate generated.


Phase 5: Next Steps

  • If confidence is Low: recommend a time-boxed spike (/prototype) before committing.
  • If the task is > 10 days: recommend breaking it into smaller stories via /create-stories.
  • To schedule the task: run /sprint-plan update to add it to the next sprint.

Guidelines

  • Always give a range (optimistic / expected / pessimistic), never a single number
  • The recommended budget should be the expected estimate, not the optimistic one
  • Round to half-day increments — estimating in hours implies false precision for tasks longer than a day
  • Do not pad estimates silently — call out risk explicitly so the team can decide
how to use estimate

How to use estimate 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 estimate
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 estimate

The skills CLI fetches estimate 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/estimate

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

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)
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general reviews

Ratings

4.862 reviews
  • Isabella Ramirez· Dec 16, 2024

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

  • Kaira Srinivasan· Dec 12, 2024

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

  • Neel Torres· Dec 12, 2024

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

  • Liam Bhatia· Dec 8, 2024

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

  • Dhruvi Jain· Dec 4, 2024

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

  • Liam Torres· Nov 27, 2024

    estimate reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Oshnikdeep· Nov 23, 2024

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

  • Omar Smith· Nov 7, 2024

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

  • Kaira White· Nov 3, 2024

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

  • Arjun Shah· Nov 3, 2024

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

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