Back to Skills

create-work-breakdown-structure

pjt222
Updated 2 days ago
6 views
17
2
17
View on GitHub
Metadata

About

This Claude Skill creates a detailed Work Breakdown Structure (WBS) and WBS Dictionary from approved project deliverables. It performs hierarchical decomposition, effort estimation, and identifies dependencies and critical path candidates. Use it during classic/waterfall project planning to break down initiatives into manageable work packages for estimation and resource allocation.

Quick Install

Claude Code

Recommended
Primary
npx skills add pjt222/agent-almanac -a claude-code
Plugin CommandAlternative
/plugin add https://github.com/pjt222/agent-almanac
Git CloneAlternative
git clone https://github.com/pjt222/agent-almanac.git ~/.claude/skills/create-work-breakdown-structure

Copy and paste this command in Claude Code to install this skill

Documentation

Create a Work Breakdown Structure

Break project scope into hierarchical set of work packages. Estimable, assignable, trackable. WBS gives foundation for effort estimation, resource planning, schedule development. Breaks complex deliverables into manageable components.

When Use

  • After project charter approved and scope defined
  • Planning classic/waterfall project with defined deliverables
  • Breaking big initiative into manageable work packages
  • Setting basis for effort estimation and resource planning
  • Making shared understanding of all required work

Inputs

  • Required: Approved project charter (especially scope and deliverables sections)
  • Required: Project methodology (classic/waterfall, or hybrid with WBS for planning)
  • Optional: Historical effort data from similar projects
  • Optional: Team composition and available skills
  • Optional: Organizational WBS templates or standards

Steps

Step 1: Extract Deliverables from Charter

Read project charter. List all deliverables and acceptance criteria. Group into 3-7 top-level categories (these become WBS Level 1 elements).

Got: List of Level 1 WBS elements matching charter deliverables.

If fail: Charter vague? Return to draft-project-charter to refine scope.

Step 2: Decompose into Work Packages

For each Level 1 element, break into sub-elements (Level 2, Level 3). Apply 100% rule: child elements must represent 100% of parent's scope. Stop decomposing when work packages are:

  • Estimable (can assign effort in person-days)
  • Assignable (one person or team owns it)
  • Measurable (clear done/not-done criteria)

Create WBS outline:

# Work Breakdown Structure: [Project Name]
## Document ID: WBS-[PROJECT]-[YYYY]-[NNN]

### WBS Hierarchy

1. [Level 1: Deliverable Category A]
   1.1 [Level 2: Sub-deliverable]
      1.1.1 [Level 3: Work Package]
      1.1.2 [Level 3: Work Package]
   1.2 [Level 2: Sub-deliverable]
2. [Level 1: Deliverable Category B]
   2.1 [Level 2: Sub-deliverable]
3. [Level 1: Project Management]
   3.1 Planning
   3.2 Monitoring & Control
   3.3 Closure

Apply WBS codes (1.1.1 format). Keep 3-5 levels deep max. Always include "Project Management" branch.

Got: Complete WBS with 15-50 work packages, each with unique WBS code.

If fail: Decomposition exceeds 5 levels? Scope too large — consider splitting into sub-projects.

Step 3: Write WBS Dictionary

For each work package (leaf node), write dictionary entry:

# WBS Dictionary: [Project Name]
## Document ID: WBS-DICT-[PROJECT]-[YYYY]-[NNN]

### WBS 1.1.1: [Work Package Name]
- **Description**: What this work package produces
- **Acceptance Criteria**: How to verify it's done
- **Responsible**: Person or role
- **Estimated Effort**: [T-shirt size or person-days]
- **Dependencies**: WBS codes this depends on
- **Assumptions**: Key assumptions for this work package

### WBS 1.1.2: [Work Package Name]
...

Got: Dictionary entry for every leaf-node work package.

If fail: Missing dictionary entries → incomplete decomposition. Revisit Step 2.

Step 4: Estimate Effort

For each work package, apply one estimation method:

  • T-shirt sizing (XS/S/M/L/XL) for early-stage planning
  • Person-days for detailed planning
  • Three-point estimate (optimistic/most likely/pessimistic) for high-uncertainty work

Create summary table:

## Effort Summary
| WBS Code | Work Package | Estimate | Method | Confidence |
|----------|-------------|----------|--------|------------|
| 1.1.1 | [Name] | 5 pd | person-days | High |
| 1.1.2 | [Name] | M | t-shirt | Medium |

Total effort = sum of all work packages.

Got: Every work package has effort estimate with stated confidence.

If fail: Confidence Low on >30% of packages? Schedule refinement session with SMEs.

Step 5: Identify Dependencies and Critical Path Candidates

Map dependencies between work packages:

## Dependencies
| WBS Code | Depends On | Type | Notes |
|----------|-----------|------|-------|
| 1.2.1 | 1.1.1 | Finish-to-Start | Output of 1.1.1 is input to 1.2.1 |
| 2.1.1 | 1.1.2 | Finish-to-Start | |

Find longest chain of dependent work packages — this is critical path candidate.

Got: Dependency table with at least finish-to-start relationships identified.

If fail: Dependencies form cycles? Decomposition has errors. Revisit Step 2.

Step 6: Review and Baseline

Combine WBS and dictionary into final documents. Verify 100% rule at every level. Get stakeholder sign-off.

Got: WBS.md and WBS-DICTIONARY.md files created and reviewed.

If fail: Stakeholders identify missing scope? Add work packages and re-estimate.

Checks

  • WBS file created with document ID and WBS codes
  • 100% rule satisfied: children fully represent parent scope at every level
  • Every leaf node has WBS dictionary entry
  • All work packages have effort estimates
  • Dependencies identified with no circular references
  • Project Management branch included
  • Critical path candidates identified
  • WBS depth does not exceed 5 levels

Pitfalls

  • Confusing deliverables with activities: WBS elements should be nouns (deliverables), not verbs (activities). "User Authentication Module" not "Implement Authentication".
  • Violating the 100% rule: Children don't add up to 100% of parent scope → work will be missed.
  • Too shallow or too deep: 2 levels too vague for planning; 6+ levels is micromanagement. Target 3-5 levels.
  • Skipping Project Management branch: PM work (planning, meetings, reporting) is real work consuming effort.
  • Estimating before decomposing: Estimate work packages, not categories. Level 1 estimate unreliable.
  • No dictionary: WBS without dictionary is tree of labels. Dictionary gives definition of done.

See Also

  • draft-project-charter — gives scope and deliverables feeding WBS decomposition
  • manage-backlog — translate WBS work packages into backlog items for tracking
  • generate-status-report — report progress against WBS % complete
  • plan-sprint — if using hybrid approach, sprint-plan from WBS work packages
  • conduct-retrospective — review estimation accuracy and decomposition quality

GitHub Repository

pjt222/agent-almanac
Path: i18n/caveman/skills/create-work-breakdown-structure
0
agentsagentskillsai-assisted-developmentclaude-codeskillsteams

Related Skills

content-collections

Meta

This skill provides a production-tested setup for Content Collections, a TypeScript-first tool that transforms Markdown/MDX files into type-safe data collections with Zod validation. Use it when building blogs, documentation sites, or content-heavy Vite + React applications to ensure type safety and automatic content validation. It covers everything from Vite plugin configuration and MDX compilation to deployment optimization and schema validation.

View skill

polymarket

Meta

This skill enables developers to build applications with the Polymarket prediction markets platform, including API integration for trading and market data. It also provides real-time data streaming via WebSocket to monitor live trades and market activity. Use it for implementing trading strategies or creating tools that process live market updates.

View skill

creating-opencode-plugins

Meta

This skill helps developers create OpenCode plugins that hook into 25+ event types like commands, files, and LSP operations. It provides the plugin structure, event API specifications, and implementation patterns for JavaScript/TypeScript modules. Use it when you need to intercept, monitor, or extend the OpenCode AI assistant's lifecycle with custom event-driven logic.

View skill

sglang

Meta

SGLang is a high-performance LLM serving framework that specializes in fast, structured generation for JSON, regex, and agentic workflows using its RadixAttention prefix caching. It delivers significantly faster inference, especially for tasks with repeated prefixes, making it ideal for complex, structured outputs and multi-turn conversations. Choose SGLang over alternatives like vLLM when you need constrained decoding or are building applications with extensive prefix sharing.

View skill