This skill should be used when users want guidance on Spec-Driven Development methodology using GitHub's Spec-Kit.

MITAuto-check passedDevelopment

Install Sdd

skills CLI
$ npx skills add SpillwaveSolutions/sdd-skill --skill sdd -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install SpillwaveSolutions/sdd-skill sdd --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
sdd
GitHub stars
106
Token cost
~5.7k tokens
SKILL.md length
1,898 words
Files
14 (incl. scripts, references)
Skills in repo
1
Repo updated
First seen
Licence
MIT

At a glance

This skill should be used when users want guidance on Spec-Driven Development methodology using GitHub's Spec-Kit.

  • Works in 5 steps: Detect Artifact Changes → Read and Summarize → Present Structured Summary (Use 10-Point… → …
  • Tasks that involve Spec-driven development
  • SKILL.md covers Core Philosophy, Quick Decision Tree, Installation Quick Start and Supported AI Agents, plus 4 more sections
  • Runs Python and Shell scripts from its folder; calls uv and uvx; reaches github.com

What it does

Sdd is an agent skill from SpillwaveSolutions/sdd-skill. This skill should be used when users want guidance on Spec-Driven Development methodology using GitHub's Spec-Kit. Guide users through executable specification workflows for both new projects (greenfield) and existing codebases (brownfield). After any SDD command generates artifacts, automatically provide structured 10-point summaries with feature status tracking, enabling natural language feature management and keeping users engaged throughout the process.

Its SKILL.md is about 5.7k tokens, which your agent loads only when the skill is triggered. The skill folder holds 15 other files, including scripts and reference files (for example `README.md`, `package-lock.json` and `package.json`).

It sits in Development, covering Spec-driven development. It works with GitHub. The repository describes itself as: A comprehensive Claude Code skill for guiding users through GitHub's Spec-Kit and the Spec-Driven Development methodology. The licence is MIT.

When your agent uses it

  • Tasks that involve Spec-driven development

Example prompts

  • “/sdd”

Requirements

  • Python 3
  • A Bash shell

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

  1. Detect Artifact Changes
  2. Read and Summarize
  3. Present Structured Summary (Use 10-Point Template Below)
  4. Include Feature Status (Hybrid Approach)
  5. Offer Feedback Options

What it can do on your machine

Read from SKILL.md and the folder at commit eba9606. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 4 files in scripts/ (Python and Shell), which the agent can run.

    Shell commands in SKILL.md call:

    • uv
    • uvx

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • github.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Sdd loads about 5.7k tokens when it runs, and up to ~26k if it reads all its reference files. Until then it costs about 116 tokens; SKILL.md has 1,898 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~116
When it runs · the whole SKILL.md, loaded when a task matches
~5.7k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~26k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from SpillwaveSolutions/sdd-skill at commit eba9606, republished under its MIT licence (© SpillwaveSolutions). 1,898 words, ~5,658 tokens.

Download SKILL.mdSave it as .claude/skills/sdd/SKILL.md (or your agent's skills folder). This skill also uses 13 other files; get the full folder from GitHub.
name
sdd
description
This skill should be used when users want guidance on Spec-Driven Development methodology using GitHub's Spec-Kit. Guide users through executable specification workflows for both new projects (greenfield) and existing codebases (brownfield). After any SDD command generates artifacts, automatically provide structured 10-point summaries with feature status tracking, enabling natural language feature management and keeping users engaged throughout the process.
version
2.1.0
triggers
spec-driven development, spec kit, speckit, sdd, specify cli, specification driven, github spec-kit, /speckit, constitution, specify init, executable…
author
Based on GitHub Spec-Kit by Den Delimarsky and John Lam
license
MIT
tags
development-methodology, ai-native-development, spec-driven, github, project-management, workflow, requirements, planning

Spec-Driven Development (SDD) Skill

Guide users through GitHub's Spec-Kit for Spec-Driven Development - a methodology that flips traditional software development by making specifications executable and directly generating working implementations.

Core Philosophy

Spec-Driven Development emphasizes:

  • Intent-driven development: Define the "what" before the "how"
  • Rich specification creation: Use guardrails and organizational principles
  • Multi-step refinement: Not one-shot code generation
  • AI-native: Heavy reliance on advanced AI capabilities

Remember: This is AI-native development. Specifications aren't just documentation - they're executable artifacts that directly drive implementation. The AI agent uses them to generate working code that matches the intent defined in the specs.

Quick Decision Tree

Is this a new project (greenfield)?

→ See Greenfield Workflow for the complete 6-step process

Is this an existing codebase (brownfield)?

→ See Brownfield Workflow for reverse-engineering and integration guidance

Need installation help?

→ See Installation Guide for setup and troubleshooting

Installation Quick Start

Recommended (Persistent):

bash
uv tool install specify-cli --from git+https://github.com/github/spec-kit.git

One-time Usage:

bash
uvx --from git+https://github.com/github/spec-kit.git specify init <PROJECT_NAME>

Verify:

bash
specify check

For detailed installation options, troubleshooting, and environment variables, see Installation Guide.

Supported AI Agents

Works with:

  • ✅ Claude Code
  • ✅ GitHub Copilot
  • ✅ Gemini CLI
  • ✅ Cursor
  • ✅ Qwen Code
  • ✅ opencode
  • ✅ Windsurf
  • ✅ Kilo Code
  • ✅ Auggie CLI
  • ✅ CodeBuddy CLI
  • ✅ Roo Code
  • ✅ Codex CLI
  • ✅ Amp
  • ⚠️ Amazon Q Developer CLI (doesn't support custom arguments for slash commands)

Artifact Summarization and Feedback Loop

CRITICAL WORKFLOW: After any SDD command generates or modifies artifacts, automatically follow this feedback loop to keep the user engaged:

After Each Command Completes
  1. Detect Artifact Changes

    • Identify which artifacts were created or modified:
      • constitution.md (project principles)
      • spec.md (requirements specification)
      • plan.md (technical implementation plan)
      • tasks.md (actionable task breakdown)
      • Analysis reports from brownfield workflows
  2. Read and Summarize

    • Read the relevant artifact(s)
    • Extract key information:
      • For constitution.md: Core principles, coding standards, constraints
      • For spec.md: Main requirements, user stories, success criteria
      • For plan.md: Tech stack choices, architecture decisions, milestones
      • For tasks.md: Number of tasks, major task categories, dependencies
      • For analysis reports: Current patterns, tech debt, integration points
  3. Present Structured Summary (Use 10-Point Template Below)

    • Show what was generated and why
    • Highlight the most important decisions with rationale
    • Include quality indicators and watch-outs
    • Keep summary focused and actionable
    • Use clear headings for each section
  4. Include Feature Status (Hybrid Approach)

    • Brief status line in every summary
    • Detailed status on demand with /speckit.status
    • See "Feature Status Tracking" section below
  5. Offer Feedback Options

    • Option A: "Looks good, proceed to next step"
    • Option B: "I'd like to modify [specific section]"
    • Option C: "Regenerate with these changes: [user input]"
    • Option D: "Explain why [specific decision] was made"
10-Point Summary Template

Use this structured format after ANY SDD command completes:

## ✅ [Command Name] Completed - Here's What Just Happened

### 🎯 Key Decisions Made (Top 3)
1. [Decision] - **Rationale:** [Why this was chosen]
2. [Decision] - **Rationale:** [Why this was chosen]
3. [Decision] - **Rationale:** [Why this was chosen]

### 📋 What Was Generated
- [Artifact 1]: [Brief description of content]
- [Artifact 2]: [Brief description of content]

### 🔍 Important Items to Review (Top 3)
1. [Critical item to check and why it matters]
2. [Important detail to verify and potential impact]
3. [Edge case to consider and how it affects the design]

### ⚠️ Watch Out For (Top 2)
- [Potential issue or gotcha] - **How to avoid:** [Guidance]
- [Common mistake] - **How to avoid:** [Guidance]

### 🔄 What This Enables Next (2 Options)
- **Option 1:** [Next step] - Best if: [Condition]
- **Option 2:** [Alternative step] - Best if: [Condition]

📊 **Feature Status:** [Current Feature Name] ([Stage]) → Next: [Next Feature]
   Progress: [●●●○○] [X]% | Completed: [N] of [Total] features | Dependencies: [Status]

**Your options:** [A] Proceed [B] Modify [C] Explain more [D] Show full status
Example: Enhanced Summarization After `/speckit.specify`

```

✅ Specify Completed - Here's What Just Happened

🎯 Key Decisions Made
  1. Authentication: JWT tokens - Rationale: Stateless architecture, horizontally scalable, industry standard
  2. Password requirements: 12+ characters with complexity - Rationale: Balances security (NIST guidelines) with usability
  3. Session timeout: 24 hours - Rationale: Standard for web apps, balances security vs user convenience
📋 What Was Generated
  • `.speckit/features/user-auth/specify.md`: Complete requirements with 5 user stories, 8 success criteria, 3 edge cases
🔍 Important Items to Review
  1. Password reset flow - Verify email requirements match your infrastructure (SMTP server, templates)
  2. Multi-factor authentication - Currently marked as "future enhancement"; may need to be in MVP
  3. Rate limiting - Set at 5 login attempts per 15 min; consider if this fits your security policy
⚠️ Watch Out For
  • Email service dependency not specified - How to avoid: Add email service to plan.md dependencies
  • GDPR compliance for user data - How to avoid: Review data retention and user deletion requirements
🔄 What This Enables Next
  • Option 1: Run `/speckit.plan` to design technical implementation - Best if: Requirements look good
  • Option 2: Modify specify.md - Best if: You need to adjust requirements or add features

📊 Feature Status: user-authentication (Specified) → Next: profile-management Progress: [●●○○○] 40% | Completed: 1 of 5 features | Dependencies: database-setup ✅

Your options: [A] Proceed to planning [B] Modify requirements [C] Explain JWT choice [D] Show full status ```

When to Skip Summarization

Only skip the summarization step when:

  • User explicitly requests "skip summaries" or "run all steps automatically"
  • Re-running a command without artifact changes
  • Command fails or produces errors (troubleshoot instead)
Benefits of This Workflow
  • Eliminates "black box" feeling: Clear explanations of what was generated and why
  • Enables early feedback: Catch misunderstandings before implementation
  • Maintains agility: Quick review with structured format, not lengthy approval processes
  • Builds trust: User sees the AI's reasoning and decisions with rationale
  • Provides context: Feature status keeps users oriented in the overall project

Feature Status Tracking

Hybrid Approach

After every SDD command, include a brief feature status line in the summary. Provide detailed status on demand with /speckit.status.

Brief Status Line Format

Include this at the end of every summary:

📊 **Feature Status:** [Current Feature Name] ([Stage]) → Next: [Next Feature Name]
   Progress: [●●●○○] [X]% | Completed: [N] of [Total] features | Dependencies: [Dep] ✅/⏸️

Stage values:

  • Specifying (20% complete)
  • Planning (40% complete)
  • Tasking (60% complete)
  • In Progress (80% complete)
  • Complete (100% complete)

Progress indicator:

  • Use filled circles (●) for completed stages
  • Use empty circles (○) for pending stages
  • Calculate percentage based on stage
Detailed Status Dashboard

When user requests full status (option D) or runs /speckit.status, show:

📊 Project Feature Status Dashboard

🎯 CURRENT FEATURE
├─ [feature-name] ([Stage] - [X]% complete)
│  ├─ ✅ Requirements specified
│  ├─ 🔄 Implementation plan in progress
│  ├─ ⏸️  Tasks not started
│  └─ ⏸️  Implementation not started
│  Blockers: [None | Description]
│  Dependencies: [feature-name] ✅

✅ COMPLETED FEATURES ([N])
├─ [feature-1] (100% complete)
└─ [feature-2] (100% complete)

📋 UPCOMING FEATURES ([N])
├─ [feature-3] (depends on: [current-feature])
└─ [feature-4] (depends on: [feature-3])

⚠️  BLOCKED FEATURES ([N])
[List any features that are blocked with reasons]
Natural Language Feature Management

Claude should automatically detect and handle natural language feature management requests:

User says: "Move feature XYZ before ABC" Claude does:

  1. Reads current feature list from .speckit/features/
  2. Shows current order with numbers
  3. Proposes new order
  4. Asks for confirmation
  5. Updates feature priority/order in constitution or plan
  6. Shows updated status dashboard

User says: "Add a new feature for email notifications" Claude does:

  1. Detects new feature request
  2. Asks clarifying questions (priority, dependencies, description)
  3. Generates feature spec outline
  4. Inserts into feature list at appropriate position
  5. Shows updated status dashboard

User says: "Let's do profile-management first" Claude does:

  1. Identifies current feature order
  2. Proposes moving profile-management to top priority
  3. Adjusts dependencies if needed
  4. Updates artifacts
  5. Shows updated status

Detection patterns:

  • "Move [feature] before/after [other]" → Reorder
  • "Add [feature]" → New feature
  • "Let's do [feature] first" → Move to top priority
  • "Skip [feature] for now" → Mark as deferred
  • "We finished [feature]" → Update status to complete
  • "What features depend on [feature]?" → Show dependency tree
  • "Show feature status" → Display full dashboard
Quick Feature Operations

Guide users through these operations when requested:

Add Feature:

User: "Add a feature for admin dashboard"
Claude:
1. What's the priority? (High/Medium/Low)
2. What features does this depend on? (user-auth, profile-management, etc.)
3. Brief description?
[Creates outline, shows updated status]

Reorder Features:

User: "Reorder features"
Claude:
Current order:
1. user-authentication
2. profile-management
3. admin-dashboard
4. email-notifications
5. reporting

How would you like to reorder? (provide new numbers or describe changes)
[Updates order, shows new status]

Remove Feature:

User: "Remove the reporting feature"
Claude:
⚠️  Warning: This will remove 'reporting' feature.
Dependencies affected: None
Are you sure? (yes/no)
[If yes: removes, updates status]
Progress Calculation

Automatically calculate progress based on SDD workflow completion:

StageProgressIndicators
Specified20%specify.md exists
Planned40%plan.md exists
Tasked60%tasks.md exists
In Progress80%Implementation started (code files modified)
Complete100%Implementation complete, tests pass
Dependency Tracking

Track and visualize dependencies:

Show dependencies:

user-authentication
├─ Depends on: database-setup ✅
└─ Blocks: profile-management ⏸️, admin-dashboard ⏸️

Check if ready:

📊 Can we start profile-management?
   Checking dependencies...
   ✅ user-authentication (complete)
   ✅ database-setup (complete)

   All dependencies satisfied! Ready to proceed.

Detect circular dependencies:

⚠️  Warning: Circular dependency detected
   feature-A depends on feature-B
   feature-B depends on feature-C
   feature-C depends on feature-A

   Please resolve this before proceeding.
Integration with Workflows

For Greenfield Projects:

  • After /speckit.specify, ask if there are multiple features
  • If yes, list them and track progress through each
  • Show status after each command

For Brownfield Projects:

  • After /speckit.reverse-engineer, create feature list from discovered functionality
  • Track new features separately from existing documented features
  • Show integration impact on status

For complete feature management guidance, see Feature Management Guide.

How to Use This Skill

When User Asks About SDD
  1. Explain core philosophy: Executable specifications, intent-driven, AI-native
  2. Verify prerequisites: `uv`, Python 3.11+, Git, AI agent
  3. Determine project type: New (greenfield) vs existing (brownfield)
  4. Guide to appropriate workflow:
Show full SKILL.md (739 more words)Show less
When User Wants to Start a New Project
  1. Guide installation → Installation Guide
  2. Initialize project: ```bash specify init my-project --ai claude ```
  3. Follow greenfield workflow → Greenfield Workflow
  4. After each step: Summarize artifacts and get user feedback
When User Has an Existing Codebase
  1. Check for `.speckit/` directory
  2. If missing → Guide through Brownfield Workflow:
    • Analyze existing code
    • Generate constitution from existing patterns
    • Choose artifact generation strategy
    • Add new features with SDD
  3. If present → Determine next step based on current progress
  4. After each step: Summarize artifacts and get user feedback
When User Wants to Add a Feature

To greenfield project:

  1. Navigate to Greenfield Workflow
  2. Follow steps 3-6 (specify → plan → tasks → implement)
  3. Summarize each artifact before proceeding

To brownfield/existing project:

  1. Navigate to Brownfield Workflow
  2. Follow steps 6-7 (specify → integration planning → tasks → implement)
  3. Summarize each artifact before proceeding
When User Encounters Issues
  1. Installation issues → Installation Guide troubleshooting section
  2. Workflow issues → Check appropriate workflow guide:
  3. Feature detection → Set `SPECIFY_FEATURE` environment variable (see Installation Guide)

Workflow Overview

Greenfield (New Projects)

``` specify init → /speckit.constitution → [SUMMARIZE] → /speckit.specify → [SUMMARIZE] → /speckit.plan → [SUMMARIZE] → /speckit.tasks → [SUMMARIZE] → /speckit.implement ```

Full details: Greenfield Workflow

Brownfield (Existing Projects)

``` specify init --here → /speckit.brownfield → [SUMMARIZE] → /speckit.analyze-codebase → [SUMMARIZE] → /speckit.reverse-engineer → [SUMMARIZE] → /speckit.specify → [SUMMARIZE] → /speckit.integration-plan → [SUMMARIZE] → /speckit.tasks → [SUMMARIZE] → /speckit.implement ```

Full details: Brownfield Workflow

Development Phases Supported

0-to-1 Development ("Greenfield")

Start with high-level requirements, generate specifications from scratch, plan implementation steps, build production-ready applications.

→ Greenfield Workflow

Iterative Enhancement ("Brownfield")

Add features iteratively to existing codebases, modernize legacy systems, adapt processes for evolving requirements, reverse-engineer existing code into SDD format.

→ Brownfield Workflow

Creative Exploration

Explore diverse solutions in parallel, support multiple technology stacks & architectures, experiment with UX patterns.

→ Greenfield Workflow - Multi-Stack Exploration section

Key Commands Reference

Installation & Setup

```bash specify init <project> # New project specify init --here --force # Existing project specify check # Verify installation ```

Greenfield Workflow

``` /speckit.constitution # Project principles → SUMMARIZE /speckit.specify # Define requirements → SUMMARIZE /speckit.plan # Technical planning → SUMMARIZE /speckit.tasks # Break down tasks → SUMMARIZE /speckit.implement # Execute ```

Brownfield Workflow

``` /speckit.brownfield # Analyze existing code → SUMMARIZE /speckit.analyze-codebase # Deep analysis & constitution → SUMMARIZE /speckit.reverse-engineer # Document existing features → SUMMARIZE /speckit.integration-plan # Plan new feature integration → SUMMARIZE ```

Optional Enhancement Commands

``` /speckit.clarify # Clarify ambiguous requirements /speckit.analyze # Cross-artifact consistency check /speckit.checklist # Generate quality checklists ```

Analysis Scripts

The SDD skill includes analysis scripts for deep quality validation and progress tracking:

`scripts/phase_summary.sh`

Generates a comprehensive progress report across all phases in a tasks.md file:

  • Shows completion percentage for each phase
  • Lists pending tasks per phase
  • Highlights simplified/modified tasks
  • Provides overall progress statistics
  • Supports any SDD feature's tasks.md file

Usage: ```bash ~/.claude/skills/sdd/scripts/phase_summary.sh specs/003-keyboard-shortcuts/tasks.md ```

Output: Markdown-formatted phase-by-phase progress report with:

  • Phase-by-phase completion percentages
  • Pending task lists (up to 5 per phase)
  • Simplified task warnings
  • Overall feature progress summary

When to Use:

  • Check progress on any SDD feature
  • Get quick overview of what's complete vs pending
  • Identify phases that need attention
  • Generate status reports for stakeholders
`scripts/analyze-requirements.py`

Analyzes requirement coverage across spec.md and tasks.md:

  • Maps functional requirements (FR-001, FR-002, etc.) to implementation tasks
  • Identifies uncovered requirements (gaps in task coverage)
  • Flags vague requirements lacking measurable criteria
  • Calculates coverage percentage

Usage: ```bash python3 ~/.claude/skills/sdd/scripts/analyze-requirements.py ```

Output: JSON with coverage metrics, uncovered requirements, vague requirements

`scripts/analyze-success-criteria.py`

Analyzes success criteria verification coverage:

  • Maps success criteria (SC-001, SC-002, etc.) to verification tasks
  • Validates measurability of each criterion
  • Identifies criteria without verification tasks
  • Groups by metric type (performance, accessibility, usability)

Usage: ```bash python3 ~/.claude/skills/sdd/scripts/analyze-success-criteria.py ```

Output: JSON with coverage summary, verification task mapping

`scripts/analyze-edge-cases.py`

Analyzes edge case coverage across specifications:

  • Maps edge cases to explicit task coverage
  • Identifies implicitly covered cases (handled by general logic)
  • Flags uncovered edge cases requiring attention
  • Categorizes coverage type (EXPLICIT, IMPLICIT, UNCOVERED)

Usage: ```bash python3 ~/.claude/skills/sdd/scripts/analyze-edge-cases.py ```

Output: JSON with coverage breakdown, uncovered edge case details

When to Use: These scripts are automatically invoked during `/speckit.analyze` to provide deep consistency validation. They help identify:

  • Requirements without task coverage
  • Success criteria without verification
  • Edge cases that need test coverage
  • Ambiguous requirements needing clarification
Validation Commands (Brownfield)

``` /speckit.validate-reverse-engineering # Verify spec accuracy /speckit.coverage-check # Check documentation coverage /speckit.validate-constitution # Verify constitution consistency /speckit.trace [feature] # Map specs to code ```

Detailed Documentation

Integration with Other Skills

This skill works well with:

  • project-memory: Document SDD decisions and patterns
  • design-doc-mermaid: Visualize architecture from plan.md
  • github-workflows: Automate SDD artifact validation
  • code-quality-reviewer: Review generated implementation

Resources

Maintainers

  • Den Delimarsky (@localden)
  • John Lam (@jflam)

© SpillwaveSolutions, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 13 other files (scripts, references) in the repository root of SpillwaveSolutions/sdd-skill.

  • SKILL.md
  • .gitignore
  • README.md
  • package-lock.json
  • package.json
  • references/brownfield.md
  • references/feature_management.md
  • references/greenfield.md
  • references/sdd_install.md
  • scripts/analyze-edge-cases.py
  • scripts/analyze-requirements.py
  • scripts/analyze-success-criteria.py
  • scripts/phase_summary.sh
  • skill.json

Open the folder on GitHubat commit eba9606

Compare with similar skills

Sdd next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Sdd compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Sdd this skillSpillwaveSolutions/sdd-skill106—~5.7kAutomated safety check: PassMIT
Speckit Taskstoissueskunstmusik/blue15419 repos~2kAutomated safety check: PassGPL-3.0
Review Spdzhu1090093659/spec_driven_develop984—~1.5kAutomated safety check: PassMIT
React Router RFC Implementerremix-run/react-router57k—~2.3kAutomated safety check: PassMIT
Spec Driven Developzhu1090093659/spec_driven_develop984—~5.1kAutomated safety check: PassMIT
Oft Spec Driven Developmentitsallcode/openfasttrace198—~2kAutomated safety check: PassGPL-3.0

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Works with

Categories

Questions about Sdd

What does Sdd do?

This skill should be used when users want guidance on Spec-Driven Development methodology using GitHub's Spec-Kit. Sdd is an agent skill from SpillwaveSolutions/sdd-skill. This skill should be used when users want guidance on Spec-Driven Development methodology using GitHub's Spec-Kit.

When should I use Sdd?

Sdd fits situations like: tasks that involve Spec-driven development.

How do I install Sdd in Claude Code?

Run `npx skills add SpillwaveSolutions/sdd-skill --skill sdd -a claude-code`. Or copy the skill folder (the SpillwaveSolutions/sdd-skill repository) into .claude/skills/sdd in your project. Claude Code loads it when a task matches its description.

How do I install Sdd in Codex?

Run `npx skills add SpillwaveSolutions/sdd-skill --skill sdd -a codex`. Or copy the skill folder (the SpillwaveSolutions/sdd-skill repository) into .agents/skills/sdd in your project. Codex loads it when a task matches its description.

Can I use Sdd in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add SpillwaveSolutions/sdd-skill --skill sdd -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/sdd, .gemini/skills/sdd, .github/skills/sdd and .opencode/skills/sdd in your project.

What does Sdd need to run?

Going by SKILL.md and its folder, Sdd needs Python and a shell for the scripts in its folder and the command-line tools its instructions call (uv and uvx). Our summary lists: Python 3; A Bash shell.

Does Sdd access the network?

SKILL.md names 1 domain. In commands or code: github.com; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.

Is Sdd safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Sdd use?

Sdd is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Sdd use?

About 5.7k tokens (SKILL.md is roughly 23k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 20k tokens, read only when the agent opens those files.

What are the alternatives to Sdd?

Skills that share tags, products or a category with Sdd: Speckit Taskstoissues (kunstmusik/blue, 154 stars), Review Spd (zhu1090093659/spec_driven_develop, 984 stars), React Router RFC Implementer (remix-run/react-router, 57k stars) and Spec Driven Develop (zhu1090093659/spec_driven_develop, 984 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Sdd?

SpillwaveSolutions (a GitHub organization) maintains it in SpillwaveSolutions/sdd-skill, which has 106 GitHub stars. The repository was last updated on November 17, 2025.

Source: SpillwaveSolutions/sdd-skill on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.