task-breakdown

davidkiss/smart-ai-skills · updated Apr 8, 2026

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$npx skills add https://github.com/davidkiss/smart-ai-skills --skill task-breakdown
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summary

Write comprehensive task breakdowns assuming the expert who is going to implement the specs has zero context for our project and questionable taste. Document everything they need to know: which existing files to check, which files to touch for each task and what changes to make to them. Give them the whole plan as bite-sized tasks. DRY. YAGNI. TDD.

skill.md

Writing Task Breakdown

Overview

Write comprehensive task breakdowns assuming the expert who is going to implement the specs has zero context for our project and questionable taste. Document everything they need to know: which existing files to check, which files to touch for each task and what changes to make to them. Give them the whole plan as bite-sized tasks. DRY. YAGNI. TDD.

Assume they are a skilled worker, but know almost nothing about our toolset or problem domain. Assume they don't know how to verify they are doing the right thing.

Analyze available agent skills and use all relevant ones to create the task breakdown.

Announce at start: "I'm using the task-breakdown skill to create a plan."

Constraints:

  • Each task should have a last step that verifies the task was completed correctly
  • The very last task should verify that after completing all tasks, the changes and actions were applied correctly and as intended by the specs, if provided

Presenting the tasks:

  • Once you believe you have the full task breakdown, present the tasks one-by-one to the user
  • Present tasks based on their dependencies on each other - e.g. if task B depends on task A, task A must be presented before task B
  • Ask after each task whether it looks right so far
  • Be ready to go back and clarify if something doesn't make sense - consider updating previous tasks based on user feedback, if needed
  • When user confirms a task looks good, update docs/YYYY-MM-DD-<feature-name>-tasks.md with that task

Bite-Sized Task Granularity

Each step is one action (2-5 minutes):

  • "Write the failing test" - step
  • "Run it to make sure it fails" - step
  • "Implement the minimal code to make the test pass" - step
  • "Run the tests and make sure they pass" - step

Task Breakdown Document Header

Every task breakdown MUST start with this header:

# [Task Name] Task Breakdown

**Goal:** [One sentence describing what this achieves]

**Approach:** [2-3 sentences about approach]

**Skills:** [List of skills to use]

**Tech Details:** [Key tools, services, technologies/libraries to use]

---

Task Structure

### Task N: [Component Name]

**Files:**
- Create: `exact/path/to/file.py`
- Modify: `exact/path/to/existing.py:123-145`
- Test: `tests/exact/path/to/test.py`

**Step 1: Write the failing test**

```python
def test_specific_behavior():
    result = function(input)
    assert result == expected

Step 2: Run test to verify it fails

Run: pytest tests/path/test.py::test_name -v Expected: FAIL with "function not defined"

Step 3: Write minimal implementation

def function(input):
    return expected

Step 4: Cleanup code changes Use skill(s) if available to cleanup code changes

Step 5: Review code changes Use skill(s) if available to review code changes. Make sure code follows the project's coding standards and aligns with the specs and the task breakdown.

Step 6: Run test to verify it passes

Run: pytest tests/path/test.py::test_name -v Expected: PASS


## Remember
- Exact file paths always
- For coding tasks, complete code in task breakdown (not "add validation")
- Exact commands with expected output
- Reference relevant skills with @ syntax
- DRY, YAGNI, TDD

## Execution Handoff

After saving the task breakdown, offer task execution:

**"Task breakdown complete and saved to `docs/YYYY-MM-DD-<feature-name>-tasks.md`.**

**Subagent-based task execution (this session)** - I dispatch fresh subagent per task, review between tasks, fast iteration

- **REQUIRED SUB-SKILL:** Use subagent-task-execution
- Stay in this session
- Fresh subagent per task + code review
how to use task-breakdown

How to use task-breakdown 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 task-breakdown
2

Execute installation command

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

$npx skills add https://github.com/davidkiss/smart-ai-skills --skill task-breakdown

The skills CLI fetches task-breakdown from GitHub repository davidkiss/smart-ai-skills 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/task-breakdown

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

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

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

Ratings

4.474 reviews
  • Charlotte Harris· Dec 28, 2024

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

  • Pratham Ware· Dec 24, 2024

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

  • Dev Mehta· Dec 24, 2024

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

  • Emma Mehta· Dec 24, 2024

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

  • Chaitanya Patil· Dec 20, 2024

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

  • Anika Dixit· Dec 20, 2024

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

  • William Jain· Dec 8, 2024

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

  • Carlos Chen· Dec 8, 2024

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

  • Omar Malhotra· Nov 27, 2024

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

  • William Gill· Nov 27, 2024

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

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