fda-drug-risk-assessment
Assess drug risks and adverse effects using FDA drug database to retrieve safety information and risk profiles.
Best use case
fda-drug-risk-assessment is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Assess drug risks and adverse effects using FDA drug database to retrieve safety information and risk profiles.
Teams using fda-drug-risk-assessment 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/fda-drug-risk-assessment/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How fda-drug-risk-assessment Compares
| Feature / Agent | fda-drug-risk-assessment | 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?
Assess drug risks and adverse effects using FDA drug database to retrieve safety information and risk profiles.
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
# FDA Drug Risk Assessment
## Usage
### 1. MCP Server Definition
```python
import asyncio
import json
from mcp.client.streamable_http import streamablehttp_client
from mcp import ClientSession
class OrigeneClient:
"""Origene-FDADrug MCP Client"""
def __init__(self, server_url: str, api_key: str):
self.server_url = server_url
self.api_key = api_key
self.session = None
async def connect(self):
try:
self.transport = streamablehttp_client(
url=self.server_url,
headers={"SCP-HUB-API-KEY": self.api_key}
)
self.read, self.write, self.get_session_id = await self.transport.__aenter__()
self.session_ctx = ClientSession(self.read, self.write)
self.session = await self.session_ctx.__aenter__()
await self.session.initialize()
return True
except Exception as e:
print(f"✗ connect failure: {e}")
return False
async def disconnect(self):
try:
if self.session:
await self.session_ctx.__aexit__(None, None, None)
if hasattr(self, 'transport'):
await self.transport.__aexit__(None, None, None)
except Exception as e:
print(f"✗ disconnect error: {e}")
def parse_result(self, result):
if isinstance(result, dict):
content_list = result.get("content") or []
else:
content_list = getattr(result, "content", []) or []
texts = []
for item in content_list:
if isinstance(item, dict):
if item.get("type") == "text":
texts.append(item.get("text") or "")
else:
if getattr(item, "type", None) == "text":
texts.append(getattr(item, "text", "") or "")
return "".join(texts)
```
### 2. Drug Risk Assessment Workflow
**Implementation:**
```python
## Initialize client
client = OrigeneClient(
"https://scp.intern-ai.org.cn/api/v1/mcp/14/Origene-FDADrug",
"<your-api-key>"
)
if not await client.connect():
print("connection failed")
exit()
## Get drug risk information
result = await client.session.call_tool(
"get_risk_info_by_drug_name",
arguments={
"drug_name": "Valsartan"
}
)
result_data = client.parse_result(result)
print(result_data)
await client.disconnect()
```
### Tool Descriptions
**Origene-FDADrug Server:**
- `get_risk_info_by_drug_name`: Retrieve FDA drug risk information
- Args:
- `drug_name` (str): FDA approved drug name
- Returns: Risk profile, adverse events, and safety data
### Use Cases
- Drug safety assessment
- Adverse effect analysis
- Pharmacovigilance
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