Back to Skills

planning-doc-generator

matteocervelli
Updated Today
26 views
10
10
View on GitHub
Metaworddata

About

This skill generates structured project assessment markdown documents from JSON input data. It automatically creates WHY/WHO/WHAT sections and includes a GO/NO-GO decision matrix for project evaluation. Developers should use it when they need to quickly generate planning documentation from structured project data.

Documentation

Planning Document Generator Skill

Purpose

Generate structured assessment documents from JSON configuration. Converts project planning data into markdown assessment reports with purpose, stakeholder, and scope analysis plus a GO/NO-GO decision framework.

When to Use

  • Creating project assessment documents
  • Generating planning documentation from structured data
  • Building evaluation reports with decision matrices
  • Documenting project vision and scope
  • Creating stakeholder alignment assessments
  • Generating baseline project documentation

Input: JSON Format

The skill expects JSON input with the following structure:

{
  "project_name": "Project Name",
  "date": "2025-11-03",
  "why": {
    "exists": "Why does this project exist?",
    "problem": "What problem does it solve?",
    "vision": "What is the desired outcome?"
  },
  "who": {
    "stakeholders": "List of key stakeholders",
    "decision_makers": "Who decides",
    "executors": "Who does the work",
    "concerns": "Their priorities and concerns"
  },
  "what": {
    "building": "What are we building/changing?",
    "features": "Key features and components",
    "out_of_scope": "What is out of scope",
    "success_criteria": "Definition of success"
  },
  "go_no_go": {
    "purpose_clarity": "✓|⚠|✗",
    "stakeholder_alignment": "✓|⚠|✗",
    "scope_definition": "✓|⚠|✗",
    "resource_availability": "✓|⚠|✗",
    "timeline_feasibility": "✓|⚠|✗",
    "risk_assessment": "✓|⚠|✗",
    "success_metrics": "✓|⚠|✗"
  },
  "decision": "GO|CONDITIONAL|NO-GO",
  "rationale": "Explanation of decision"
}

Template Filling Process

  1. Load templates/assessment-template.md
  2. Replace all {PLACEHOLDER} values with JSON data
  3. Calculate coverage: Count non-empty answers ÷ 17 questions
  4. Insert status indicators (✓/⚠/✗) from GO/NO-GO section
  5. Generate markdown with formatted decision matrix
  6. Validate all sections populated with content (no {ANSWER} remaining)

Coverage Calculation

Total question count: 17

Breakdown:

  • WHY section: 3 questions
  • WHO section: 4 questions
  • WHAT section: 4 questions
  • GO/NO-GO section: 7 assessment items
  • Other: 1 additional (missing info summary)

Formula:

Coverage = (Number of answered/populated fields ÷ 17) × 100
Percentage = Round to nearest whole number

Output Location

Generated documents save to:

~/docs/planning/{project_slug}/assessment-{date}.md

Example:

~/docs/planning/project-name/assessment-2025-11-03.md

Workflow

JSON Input
    ↓
Load Template
    ↓
Replace Placeholders
    ↓
Calculate Coverage
    ↓
Format Decision Matrix
    ↓
Validate Completeness
    ↓
Write to ~/docs/planning/
    ↓
Markdown Output

Key Features

Status Indicators

  • Green: Ready to proceed
  • Yellow: Proceed with caution / clarification needed
  • Red: Blocker / do not proceed

Decision Framework

  • GO: All indicators green, proceed immediately
  • CONDITIONAL GO: Some yellow flags, proceed with mitigation
  • NO-GO: Red flags present, do not proceed without resolution

Coverage Tracking

Automatically calculates and displays:

  • Number of questions answered (X/17)
  • Percentage coverage
  • List of missing information

Best Practices

  1. Complete All Fields: Aim for 100% coverage (17/17)
  2. Be Specific: Use concrete details, not generic placeholders
  3. Stakeholder Buy-in: Ensure WHO section reflects actual decision-makers
  4. Realistic Assessment: Be honest in GO/NO-GO evaluation
  5. Document Decisions: Clear rationale essential for tracking

Example Usage

# Command-line usage
planning-doc-generator \
  --input project-plan.json \
  --output ~/docs/planning/myproject/

# Result
~/docs/planning/myproject/assessment-2025-11-03.md

Integration Points

Input Sources

  • Project planning worksheets (converted to JSON)
  • Kickoff meeting notes (structured into JSON)
  • Requirements documents (parsed to JSON format)
  • Stakeholder surveys (aggregated to JSON)

Output Consumers

  • Project stakeholders (for review/approval)
  • Project managers (for tracking)
  • Decision makers (for GO/NO-GO calls)
  • Documentation archives (for reference)

Validation Rules

Before writing output file:

  • All {PLACEHOLDER} values replaced
  • No {ANSWER} tokens remaining
  • Project name populated
  • Date populated (YYYY-MM-DD format)
  • Decision field contains valid value (GO, CONDITIONAL, NO-GO)
  • Coverage calculated and accurate

Version: 1.0.0 Created: 2025-11-03 Scope: Global utility skill

Quick Install

/plugin add https://github.com/matteocervelli/llms/tree/main/planning-doc-generator

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

GitHub 仓库

matteocervelli/llms
Path: .claude/skills/planning-doc-generator

Related Skills

business-rule-documentation

Meta

This skill provides standardized templates for systematically documenting business logic and domain knowledge following Domain-Driven Design principles. It helps developers capture business rules, process flows, decision trees, and terminology glossaries to maintain consistency between requirements and implementation. Use it when documenting domain models, creating business rule repositories, or bridging communication between business and technical teams.

View skill

go-test

Meta

The go-test skill provides expertise in Go's standard testing package and best practices. It helps developers implement table-driven tests, subtests, benchmarks, and coverage strategies while following Go conventions. Use it when writing test files, creating mocks, detecting race conditions, or organizing integration tests in Go projects.

View skill

csv-data-summarizer

Meta

This skill automatically analyzes CSV files to generate comprehensive statistical summaries and visualizations using Python's pandas and matplotlib/seaborn. It should be triggered whenever a user uploads or references CSV data without prompting for analysis preferences. The tool provides immediate insights into data structure, quality, and patterns through automated analysis and visualization.

View skill

Excel Analysis

Meta

This skill enables developers to analyze Excel files and perform data operations using pandas. It can read spreadsheets, create pivot tables, generate charts, and conduct data analysis on .xlsx files and tabular data. Use it when working with Excel files, spreadsheets, or any structured tabular data within Claude Code.

View skill