linkdapi
Work with LinkdAPI Python SDK for accessing LinkedIn professional profile and company data. Use when you need to fetch profile information, company data, job listings, or search for people/jobs on LinkedIn. The skill uses uv script pattern for ephemeral Python scripts with inline dependencies.
Best use case
linkdapi is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Work with LinkdAPI Python SDK for accessing LinkedIn professional profile and company data. Use when you need to fetch profile information, company data, job listings, or search for people/jobs on LinkedIn. The skill uses uv script pattern for ephemeral Python scripts with inline dependencies.
Teams using linkdapi should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/linkdapi/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How linkdapi Compares
| Feature / Agent | linkdapi | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Work with LinkdAPI Python SDK for accessing LinkedIn professional profile and company data. Use when you need to fetch profile information, company data, job listings, or search for people/jobs on LinkedIn. The skill uses uv script pattern for ephemeral Python scripts with inline dependencies.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# LinkdAPI Python SDK
Python SDK for LinkdAPI — professional profile and company data from LinkedIn with enterprise-grade reliability.
> **Get your API key:** https://linkdapi.com/signup?ref=K_CZJSWF
## Quick Start Pattern
Use the **uv script pattern** for ephemeral Python scripts with inline dependencies:
```python
# /// script
# dependencies = [
# "linkdapi",
# ]
# ///
from linkdapi import LinkdAPI
client = LinkdAPI("YOUR_API_KEY")
profile = client.get_profile_overview("ryanroslansky")
print(profile)
```
Run with:
```bash
uv run script.py
```
This installs dependencies automatically, runs the script, and cleans up — perfect for one-off tasks.
## Why This Pattern
- **No global installs**: Dependencies are managed per-script
- **Ephemeral by design**: Write, run, delete — no cleanup needed
- **Reproducible**: Everything needed is in one file
- **Fast**: uv handles dependency resolution and caching
## Writing Scripts
### Script Header Format
Always start with the uv script block:
```python
# /// script
# dependencies = [
# "linkdapi",
# # Add more if needed (e.g., "rich", "pandas")
# ]
# ///
```
### Common Tasks
**Get profile overview:**
```python
# /// script
# dependencies = ["linkdapi"]
# ///
from linkdapi import LinkdAPI
client = LinkdAPI("YOUR_API_KEY")
profile = client.get_profile_overview("ryanroslansky")
if profile.get('success'):
data = profile['data']
print(f"{data['fullName']} - {data.get('headline', '')}")
print(f"Location: {data.get('location')}")
```
**Get company info:**
```python
# /// script
# dependencies = ["linkdapi"]
# ///
from linkdapi import LinkdAPI
client = LinkdAPI("YOUR_API_KEY")
company = client.get_company_info(name="google")
if company.get('success'):
data = company['data']
print(f"{data['name']}")
print(f"Industry: {data.get('industry')}")
print(f"Employees: {data.get('employeeCount', 'N/A')}")
```
**Search jobs:**
```python
# /// script
# dependencies = ["linkdapi"]
# ///
from linkdapi import LinkdAPI
client = LinkdAPI("YOUR_API_KEY")
result = client.search_jobs(
keyword="Software Engineer",
location="San Francisco, CA",
time_posted="1week"
)
if result.get('success'):
for job in result['data']['jobs'][:5]:
print(f"{job['title']} at {job['company']}")
```
**Batch profile enrichment (async):**
```python
# /// script
# dependencies = ["linkdapi"]
# ///
import asyncio
from linkdapi import AsyncLinkdAPI
async def enrich():
async with AsyncLinkdAPI("YOUR_API_KEY") as api:
profiles = await asyncio.gather(
api.get_profile_overview("ryanroslansky"),
api.get_profile_overview("satyanadella"),
api.get_profile_overview("jeffweiner08")
)
for p in profiles:
if p.get('success'):
print(p['data']['fullName'])
asyncio.run(enrich())
```
## Agent Workflow
When a user requests LinkedIn data:
1. **Identify the task** (profile lookup, company data, job search, etc.)
2. **Write a temporary script** in workspace with the uv script header
3. **Add dependencies** (usually just `"linkdapi"`, add others if needed)
4. **Import and use** LinkdAPI classes
5. **Run with `uv run`**
6. **Capture output** and report to user
7. **Delete the script** after use (optional)
### Example Workflow
User: *"Get the profile for jeffweiner08"*
Agent:
```bash
cat > /tmp/linkdapi_query.py << 'EOF'
# /// script
# dependencies = ["linkdapi"]
# ///
from linkdapi import LinkdAPI
import os
client = LinkdAPI(os.getenv("LINKDAPI_API_KEY"))
profile = client.get_profile_overview("jeffweiner08")
if profile.get('success'):
data = profile['data']
print(f"Name: {data['fullname']}")
print(f"Headline: {data.get('headline', 'N/A')}")
print(f"Location: {data.get('location', 'N/A')}")
print(f"Company: {data.get('company', 'N/A')}")
else:
print(f"Error: {profile.get('message')}")
EOF
uv run /tmp/linkdapi_query.py
rm /tmp/linkdapi_query.py
```
## Getting an API Key
To use LinkdAPI, you'll need an API key. Sign up at:
🔗 **https://linkdapi.com/signup?ref=K_CZJSWF**
Once registered, you'll get an API key that you can use to authenticate your requests.
## Authentication
Set the API key as an environment variable:
```bash
export LINKDAPI_API_KEY="your_api_key_here"
```
Use it in scripts:
```python
import os
from linkdapi import LinkdAPI
client = LinkdAPI(os.getenv("LINKDAPI_API_KEY"))
```
## Key API Methods
### Profiles
- `get_profile_overview(username)` — Basic profile info
- `get_profile_details(urn)` — Detailed profile data
- `get_contact_info(username)` — Email, phone, websites
- `get_full_profile(username=None, urn=None)` — Complete profile
- `get_full_experience(urn)` — Work history
- `get_education(urn)` — Education history
- `get_skills(urn)` — Skills & endorsements
### Companies
- `get_company_info(company_id=None, name=None)` — Company details
- `company_name_lookup(query)` — Search by name
- `get_company_employees_data(company_id)` — Employee stats
- `get_company_jobs(company_ids)` — Job listings
### Jobs
- `search_jobs(keyword, location, ...)` — Search job postings
- `get_job_details(job_id)` — Detailed job info
### Search
- `search_people(keyword, title, company, ...)` — Find people
- `search_companies(keyword, industry, ...)` — Find companies
- `search_posts(keyword, ...)` — Find posts
## Performance Tips
- Use `AsyncLinkdAPI` for batch operations (40x faster)
- Add `return_exceptions=True` in `asyncio.gather()` for graceful error handling
- Use context managers (`async with`) for proper resource cleanup
## Error Handling
Check responses and handle errors:
```python
result = client.get_profile_overview("username")
if result.get('success'):
data = result['data']
# Process data
else:
print(f"API Error: {result.get('message')}")
```
## References
Full API documentation: https://linkdapi.com/docsRelated Skills
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