retrospective

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 retrospective
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summary

### Retrospective

  • description: "Generates a sprint or milestone retrospective by analyzing completed work, velocity, blockers, and patterns. Produces actionable insights for the next iteration."
  • argument-hint: "[sprint-N|milestone-name]"
  • allowed-tools: Read, Glob, Grep, Write
skill.md
name
retrospective
description
"Generates a sprint or milestone retrospective by analyzing completed work, velocity, blockers, and patterns. Produces actionable insights for the next iteration."
argument-hint
"[sprint-N|milestone-name]"
user-invocable
true
allowed-tools
Read, Glob, Grep, Write
context
| !git log --oneline --since="2 weeks ago" 2>/dev/null

Phase 1: Parse Arguments

Determine whether this is a sprint retrospective (sprint-N) or a milestone retrospective (milestone-name).


Phase 1b: Check for Existing Retrospective

Before loading any data, glob for an existing retrospective file:

  • For sprint retrospectives: production/retrospectives/retro-[sprint-slug]-*.md (also check production/sprints/sprint-[N]-retrospective.md as an alternate location)
  • For milestone retrospectives: production/retrospectives/retro-[milestone-name]-*.md

If a matching file is found, present the user with:

An existing retrospective was found: [filename]

[A] Update existing retrospective — load it and add/revise sections
[B] Start fresh — generate a new retrospective, archiving the old one

Wait for user selection before continuing. If updating, read the existing file and carry its content forward into the generation phase, revising sections with new data.


Phase 2: Load Sprint or Milestone Data

Read the sprint or milestone plan from the appropriate location:

  • Sprint plans: production/sprints/
  • Milestone definitions: production/milestones/

If the file does not exist or is empty, output:

"No sprint data found for [sprint/milestone]. Run /sprint-status to generate sprint data first, or provide the sprint details manually."

Then use AskUserQuestion to present two options:

  • [A] Provide data manually — ask the user to paste or describe the sprint tasks, dates, and outcomes; use that as the source of truth for the retrospective.
  • [B] Stop — abort the skill. Verdict: BLOCKED — no sprint data available.

If the user chooses [A], collect the data and continue to Phase 3 using what they provide. If the user chooses [B], stop here.

Extract: planned tasks, estimated effort, owners, and goals.

Read the git log for the period covered by the sprint or milestone to understand what was actually committed and when.


Phase 3: Analyze Completion and Trends

Scan for completed and incomplete tasks by comparing the plan against actual deliverables. Check for:

  • Tasks completed as planned
  • Tasks completed but modified from the plan
  • Tasks carried over (not completed)
  • Tasks added mid-sprint (unplanned work)
  • Tasks removed or descoped

Scan the codebase for TODO/FIXME trends:

  • Count current TODO/FIXME/HACK comments
  • Compare to previous sprint counts if available (check previous retrospectives)
  • Note whether technical debt is growing or shrinking

Read previous retrospectives (if any) from production/sprints/ or production/milestones/ to check:

  • Were previous action items addressed?
  • Are the same problems recurring?
  • How has velocity trended?

Phase 4: Generate the Retrospective

## Retrospective: [Sprint N / Milestone Name]
Period: [Start Date] -- [End Date]
Generated: [Date]

### Metrics

| Metric | Planned | Actual | Delta |
|--------|---------|--------|-------|
| Tasks | [X] | [Y] | [+/- Z] |
| Completion Rate | -- | [Z%] | -- |
| Story Points / Effort Days | [X] | [Y] | [+/- Z] |
| Bugs Found | -- | [N] | -- |
| Bugs Fixed | -- | [N] | -- |
| Unplanned Tasks Added | -- | [N] | -- |
| Commits | -- | [N] | -- |

### Velocity Trend

| Sprint | Planned | Completed | Rate |
|--------|---------|-----------|------|
| [N-2] | [X] | [Y] | [Z%] |
| [N-1] | [X] | [Y] | [Z%] |
| [N] (current) | [X] | [Y] | [Z%] |

**Trend**: [Increasing / Stable / Decreasing]
[One sentence explaining the trend]

### What Went Well
- [Observation backed by specific data or examples]
- [Another positive observation]
- [Recognize specific contributions or decisions that paid off]

### What Went Poorly
- [Specific issue with measurable impact -- e.g., "Feature X took 5 days
  instead of estimated 2, blocking tasks Y and Z"]
- [Another issue with impact]
- [Do not assign blame -- focus on systemic causes]

### Blockers Encountered

| Blocker | Duration | Resolution | Prevention |
|---------|----------|------------|------------|
| [What blocked progress] | [How long] | [How it was resolved] | [How to prevent recurrence] |

### Estimation Accuracy

| Task | Estimated | Actual | Variance | Likely Cause |
|------|-----------|--------|----------|--------------|
| [Most overestimated task] | [X] | [Y] | [+Z] | [Why] |
| [Most underestimated task] | [X] | [Y] | [-Z] | [Why] |

**Overall estimation accuracy**: [X%] of tasks within +/- 20% of estimate

[Analysis: Are we consistently over- or under-estimating? For which types of
tasks? What adjustment should we apply?]

### Carryover Analysis

| Task | Original Sprint | Times Carried | Reason | Action |
|------|----------------|---------------|--------|--------|
| [Task that was not completed] | [Sprint N-X] | [N] | [Why] | [Complete / Descope / Redesign] |

### Technical Debt Status
- Current TODO count: [N] (previous: [N])
- Current FIXME count: [N] (previous: [N])
- Current HACK count: [N] (previous: [N])
- Trend: [Growing / Stable / Shrinking]
- [Note any areas of concern]

### Previous Action Items Follow-Up

| Action Item (from Sprint N-1) | Status | Notes |
|-------------------------------|--------|-------|
| [Previous action] | [Done / In Progress / Not Started] | [Context] |

### Action Items for Next Iteration

| # | Action | Owner | Priority | Deadline |
|---|--------|-------|----------|----------|
| 1 | [Specific, measurable action] | [Who] | [High/Med/Low] | [When] |
| 2 | [Another action] | [Who] | [Priority] | [When] |

### Process Improvements
- [Specific change to how we work, with expected benefit]
- [Another improvement -- keep it to 2-3 actionable items, not a wish list]

### Summary
[2-3 sentence overall assessment: Was this a good sprint/milestone? What is
the single most important thing to change going forward?]

Phase 5: Save Retrospective

Present the retrospective and top findings to the user (completion rate, velocity trend, top blocker, most important action item).

Ask: "May I write this to production/sprints/sprint-[N]-retrospective.md?" (or the milestone path if applicable)

If yes, write the file, creating the directory if needed. Verdict: COMPLETE — retrospective saved.

If no, stop here. Verdict: BLOCKED — user declined write.


Phase 6: Next Steps

  • Run /sprint-plan to incorporate the action items and velocity data into the next sprint.
  • If this was a milestone retrospective, run /gate-check to formally assess readiness for the next phase.

Guidelines

  • Be honest and specific. Vague retrospectives ("communication could be better") produce vague improvements. Use data and examples.
  • Focus on systemic issues, not individual blame.
  • Limit action items to 3-5. More than that dilutes focus.
  • Every action item must have an owner and a deadline.
  • Check whether previous action items were completed. Recurring unaddressed items are a process smell.
  • If this is a milestone retrospective, also evaluate whether the milestone goals were achieved and what that means for the overall project timeline.
how to use retrospective

How to use retrospective 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 retrospective
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 retrospective

The skills CLI fetches retrospective 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/retrospective

Reload or restart Cursor to activate retrospective. Access the skill through slash commands (e.g., /retrospective) 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)
  • No comments yet — start the thread.
general reviews

Ratings

4.555 reviews
  • Shikha Mishra· Dec 28, 2024

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

  • Noor Li· Dec 24, 2024

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

  • Tariq Khanna· Dec 24, 2024

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

  • Kaira Rao· Dec 8, 2024

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

  • William Reddy· Nov 27, 2024

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

  • Kaira Mehta· Nov 15, 2024

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

  • Zara Patel· Nov 15, 2024

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

  • Camila Tandon· Nov 3, 2024

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

  • Benjamin Patel· Oct 22, 2024

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

  • William Smith· Oct 18, 2024

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

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