Use the DeepSeek API via direct curl calls to access powerful AI language models for chat, reasoning, and code generation.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versiondeepseekExecute the skills CLI command in your project's root directory to begin installation:
Fetches deepseek from vm0-ai/vm0-skills 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 deepseek. Access via /deepseek 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.
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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
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Use the DeepSeek API via direct curl calls to access powerful AI language models for chat, reasoning, and code generation.
Official docs:
https://api-docs.deepseek.com/
Use this skill when you need to:
export DEEPSEEK_API_KEY="your-api-key"
| Type | Price |
|---|---|
| Input (cache hit) | $0.028 |
| Input (cache miss) | $0.28 |
| Output | $0.42 |
DeepSeek does not enforce strict rate limits. They will try to serve every request. During high traffic, connections are maintained with keep-alive signals.
All examples below assume you have DEEPSEEK_API_KEY set.
The base URL for the DeepSeek API is:
https://api.deepseek.com (recommended)https://api.deepseek.com/v1 (OpenAI-compatible)Send a simple chat message:
Write to /tmp/deepseek_request.json:
{
"model": "deepseek-chat",
"messages": [
{
"role": "system",
"content": "You are a helpful assistant."
},
{
"role": "user",
"content": "Hello, who are you?"
}
]
}
Then run:
curl -s "https://api.deepseek.com/chat/completions" -X POST -H "Content-Type: application/json" -H "Authorization: Bearer $DEEPSEEK_API_KEY" -d @/tmp/deepseek_request.json
Available models:
deepseek-chat: DeepSeek-V3.2 non-thinking mode (128K context, 8K max output)deepseek-reasoner: DeepSeek-V3.2 thinking mode (128K context, 64K max output)Adjust creativity/randomness with temperature:
Write to /tmp/deepseek_request.json:
{
"model": "deepseek-chat",
"messages": [
{
"role": "user",
"content": "Write a short poem about coding."
}
],
"temperature": 0.7,
"max_tokens": 200
}
Then run:
curl -s "https://api.deepseek.com/chat/completions" -X POST -H "Content-Type: application/json" -H "Authorization: Bearer $DEEPSEEK_API_KEY" -d @/tmp/deepseek_request.json | jq -r '.choices[0].message.content'
Parameters:
temperature (0-2, default 1): Higher = more creative, lower = more deterministictop_p (0-1, default 1): Nucleus sampling thresholdmax_tokens: Maximum tokens to generateGet real-time token-by-token output:
Write to /tmp/deepseek_request.json:
{
"model": "deepseek-chat",
"messages": [
{
"role": "user",
"content": "Explain quantum computing in simple terms."
}
],
"stream": true
}
Then run:
curl -s "https://api.deepseek.com/chat/completions" -X POST -H "Content-Type: application/json" -H "Authorization: Bearer $DEEPSEEK_API_KEY" -d @/tmp/deepseek_request.json
Streaming returns Server-Sent Events (SSE) with delta chunks, ending with data: [DONE].
Use the reasoner model for complex reasoning tasks:
Write to /tmp/deepseek_request.json:
{
"model": "deepseek-reasoner",
"messages": [
{
"role": "user",
"content": "What is 15 * 17? Show your work."
}
]
}
Then run:
curl -s "https://api.deepseek.com/chat/completions" -X POST -H "Content-Type: application/json" -H "Authorization: Bearer $DEEPSEEK_API_KEY" -d @/tmp/deepseek_request.json | jq -r '.choices[0].message.content'
The reasoner model excels at math, logic, and multi-step problems.
Force the model to return valid JSON:
Write to /tmp/deepseek_request.json:
{
"model": "deepseek-chat",
"messages": [
{
"role": "system",
"content": "You are a JSON generator. Always respond with valid JSON."
},
{
"role": "user",
"content": "List 3 programming languages with their main use cases."
}
],
"response_format": {
"type": "json_object"
}
}
Then run:
curl -s "https://api.deepseek.com/chat/completions" -X POST -H "Content-Type: application/json" -H "Authorization: Bearer $DEEPSEEK_API_KEY" -d @/tmp/deepseek_request.json | jq -r '.choices[0].message.content'
Continue a conversation with message history:
Write to /tmp/deepseek_request.json:
{
"model": "deepseek-chat",
"messages": [
{
"role": "user",
"content": "My name is Alice."
},
{
"role": "assistant",
"content": "Nice to meet you, Alice."
},
{
"role": "user",
"content": "What is my name?"
}
]
}
Then run:
curl -s "https://api.deepseek.com/chat/completions" -X POST -H "Content-Type: application/json" -H "Authorization: Bearer $DEEPSEEK_API_KEY" -d @/tmp/deepseek_request.json | jq -r '.choices[0].message.content'
Use Fill-in-the-Middle for code completion (beta endpoint):
Write to /tmp/deepseek_request.json:
{
"model": "deepseek-chat",
"prompt": "def add(a, b):\n ",
"max_tokens": 20
}
Then run:
curl -s "https://api.deepseek.com/beta/completions" -X POST -H "Content-Type: application/json" -H "Authorization: Bearer $DEEPSEEK_API_KEY" -d @/tmp/deepseek_request.json | jq -r '.choices[0].text'
FIM is useful for:
Define functions the model can call:
Write to /tmp/deepseek_request.json:
{
"model": "deepseek-chat",
"messages": [
{
"role": "user",
"content": "What is the weather in Tokyo?"
}
],
"tools": [
{
"type": "function",
"function": {
"name": "get_weather",
"description": "Get the current weather for a location",
"parameters": {
"type": "object",
"properties": ✓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
Steps
- 1Install product management skill
- 2Start with user story generation for known feature
- 3Progress to competitive analysis: research 2-3 competitors
- 4Use for roadmap prioritization: apply RICE/ICE scoring
- 5Draft stakeholder communications and refine based on feedback
- 6Build template library for recurring PM tasks
- 7Share 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
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
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4.6★★★★★65 reviews- MMia Robinson★★★★★Dec 24, 2024
Solid pick for teams standardizing on skills: deepseek is focused, and the summary matches what you get after install.
- MMia Jackson★★★★★Dec 20, 2024
We added deepseek from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- LLayla Tandon★★★★★Dec 20, 2024
deepseek is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- IIsabella Martinez★★★★★Dec 16, 2024
Useful defaults in deepseek — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- PPratham Ware★★★★★Dec 12, 2024
Useful defaults in deepseek — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- DDev Rahman★★★★★Dec 8, 2024
Registry listing for deepseek matched our evaluation — installs cleanly and behaves as described in the markdown.
- IIsabella Wang★★★★★Nov 15, 2024
deepseek reduced setup friction for our internal harness; good balance of opinion and flexibility.
- MMia Sethi★★★★★Nov 15, 2024
I recommend deepseek for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- HHenry Patel★★★★★Nov 11, 2024
Keeps context tight: deepseek is the kind of skill you can hand to a new teammate without a long onboarding doc.
- AArya Nasser★★★★★Nov 11, 2024
deepseek fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
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