Create clear, comprehensive technical documentation for specs, architecture, runbooks, and APIs.
Works with
Provides templates and step-by-step guidance for five document types: technical specifications, architecture documents, runbooks, API documentation, and changelogs
Includes audience-specific writing strategies for developers, operations teams, managers, and end users with tailored content focus
Offers visual aid support via Mermaid diagrams, flowcharts, tables, and code examples with synt
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versiontechnical-writingExecute the skills CLI command in your project's root directory to begin installation:
Fetches technical-writing from supercent-io/skills-template and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate technical-writing. Access via /technical-writing in your agent's command palette.
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 environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
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
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
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
0
total installs
0
this week
88
GitHub stars
0
upvotes
Run in your terminal
0
installs
0
this week
88
stars
Developer audience:
DevOps/Operations audience:
Manager/Stakeholder audience:
End user audience:
Technical Specification:
# [Feature Name] Technical Specification
## Overview
Brief description of what this spec covers
## Problem Statement
What problem are we solving?
## Goals and Non-Goals
### Goals
- Goal 1
- Goal 2
### Non-Goals
- What we're explicitly not doing
## Solution Design
### High-Level Architecture
### Data Models
### API Contracts
### User Interface
## Implementation Plan
### Phase 1
### Phase 2
## Testing Strategy
## Security Considerations
## Performance Considerations
## Monitoring and Alerting
## Rollout Plan
## Rollback Plan
## Open Questions
## References
Architecture Document:
# System Architecture
## Overview
High-level system description
## Architecture Diagram
[Insert diagram]
## Components
### Component 1
- Responsibility
- Technology stack
- Interfaces
### Component 2
...
## Data Flow
How data moves through the system
## Key Design Decisions
### Decision 1
- Context
- Options considered
- Decision made
- Rationale
## Technology Stack
- Frontend: React, TypeScript
- Backend: Python, FastAPI
- Database: PostgreSQL
- Infrastructure: AWS, Docker, Kubernetes
## Scalability
How the system scales
## Security
Authentication, authorization, data protection
## Monitoring and Observability
Metrics, logs, tracing
## Disaster Recovery
Backup and recovery procedures
## Future Considerations
Runbook:
# [Service Name] Runbook
## Service Overview
What this service does
## Dependencies
- Service A
- Service B
- Database X
## Deployment
### How to deploy
```bash
./deploy.sh production
./rollback.sh
Symptoms: Response time > 1s Diagnosis: Check database connection pool Resolution: Restart service or scale up
Symptoms: Memory usage growing over time Diagnosis: Check heap dump Resolution: Restart service, investigate in staging
kubectl logs -f deployment/service-name
curl https://api/metrics
**API Documentation**:
```markdown
# API Documentation
## Authentication
All requests require authentication:
```bash
curl -H "Authorization: Bearer YOUR_TOKEN" \
https://api.example.com/endpoint
GET /api/v1/users
Parameters:
| Name | Type | Required | Description |
|---|---|---|---|
| page | integer | No | Page number (default: 1) |
| limit | integer | No | Items per page (default: 20) |
Example Request:
curl -X GET "https://api.example.com/api/v1/users?page=1&limit=20" \
-H "Authorization: Bearer YOUR_TOKEN"
Example Response:
{
"data": [
{
"id": 1,
"name": "John Doe",
"email": "[email protected]"
}
],
"pagination": {
"page": 1,
"limit": 20,
"total": 100
}
}
Error Responses:
| Status | Description |
|---|---|
| 400 | Bad Request |
| 401 | Unauthorized |
| 500 | Server Error |
### Step 3: Writing guidelines
**Clarity**:
- Use simple, direct language
- One idea per sentence
- Short paragraphs (3-5 sentences)
- Define technical terms
- Avoid jargon when possible
**Structure**:
- Use hierarchical headings (H1, H2, H3)
- Break content into sections
- Use lists for multiple items
- Use tables for structured data
- Add table of contents for long docs
**Examples**:
- Include code examples
- Provide diagrams
- Show before/after comparisons
- Real-world scenarios
**Completeness**:
- Cover prerequisites
- Include error handling
- Document edge cases
- Explain why, not just how
- Link to related docs
**Consistency**:
- Consistent terminology
- Consistent formatting
- Consistent code style
- Consistent structure
### Step 4: Visual aids
**Architecture diagrams** (Mermaid):
```mermaid
graph TB
A[Client] -->|HTTP| B[Load Balancer]
B --> C[Web Server 1]
B --> D[Web Server 2]
C --> E[Database]
D --> E
Sequence diagrams:
sequenceDiagram
Client->>+Server: Request
Server->>+Database: Query
Database-->>-Server: Data
Server-->>-Client: Response
Flowcharts:
flowchart TD
A[Start] --> B{Is valid?}
B -->|Yes| C[Process]
B -->|No| D[Error]
C --> E[End]
D --> E
Code blocks with syntax highlighting:
def calculate_total(items: List[Item]) -> Decimal:
"""Calculate total price of items."""
return sum(item.price for item in items)
Screenshots:
Tables:
| Parameter | Type | Default | Description |
|---|---|---|---|
| timeout | int | 30 | Request timeout in seconds |
| retries | int | 3 | Number of retry attempts |
Self-review checklist:
Get feedback:
Maintain documentation:
# [Feature Name] Technical Spec
**Author**: [Your Name]
**Make data-driven prioritization decisions faster
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
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ 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.
supercent-io/skills-template
davila7/claude-code-templates
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
Registry listing for technical-writing matched our evaluation — installs cleanly and behaves as described in the markdown.
technical-writing fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
technical-writing reduced setup friction for our internal harness; good balance of opinion and flexibility.
technical-writing is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
We added technical-writing from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Solid pick for teams standardizing on skills: technical-writing is focused, and the summary matches what you get after install.
technical-writing reduced setup friction for our internal harness; good balance of opinion and flexibility.
technical-writing fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
I recommend technical-writing for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
We added technical-writing from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
showing 1-10 of 25