pediatric_drug_safety

Pediatric Drug Safety Review - Evaluate pediatric drug safety: pediatric use info, child safety, dosage forms, and overdosage info from FDA. Use this skill for pediatric pharmacology tasks involving get pediatric use info by drug name get child safety info by drug name get dosage forms and strengths by drug name get overdosage info by drug name. Combines 4 tools from 1 SCP server(s).

Best use case

pediatric_drug_safety is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Pediatric Drug Safety Review - Evaluate pediatric drug safety: pediatric use info, child safety, dosage forms, and overdosage info from FDA. Use this skill for pediatric pharmacology tasks involving get pediatric use info by drug name get child safety info by drug name get dosage forms and strengths by drug name get overdosage info by drug name. Combines 4 tools from 1 SCP server(s).

Teams using pediatric_drug_safety 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

$curl -o ~/.claude/skills/pediatric_drug_safety/SKILL.md --create-dirs "https://raw.githubusercontent.com/SpectrAI-Initiative/InnoClaw/main/.claude/skills/pediatric_drug_safety/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/pediatric_drug_safety/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How pediatric_drug_safety Compares

Feature / Agentpediatric_drug_safetyStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Pediatric Drug Safety Review - Evaluate pediatric drug safety: pediatric use info, child safety, dosage forms, and overdosage info from FDA. Use this skill for pediatric pharmacology tasks involving get pediatric use info by drug name get child safety info by drug name get dosage forms and strengths by drug name get overdosage info by drug name. Combines 4 tools from 1 SCP server(s).

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

# Pediatric Drug Safety Review

**Discipline**: Pediatric Pharmacology | **Tools Used**: 4 | **Servers**: 1

## Description

Evaluate pediatric drug safety: pediatric use info, child safety, dosage forms, and overdosage info from FDA.

## Tools Used

- **`get_pediatric_use_info_by_drug_name`** from `fda-drug-server` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/14/Origene-FDADrug`
- **`get_child_safety_info_by_drug_name`** from `fda-drug-server` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/14/Origene-FDADrug`
- **`get_dosage_forms_and_strengths_by_drug_name`** from `fda-drug-server` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/14/Origene-FDADrug`
- **`get_overdosage_info_by_drug_name`** from `fda-drug-server` (streamable-http) - `https://scp.intern-ai.org.cn/api/v1/mcp/14/Origene-FDADrug`

## Workflow

1. Get pediatric use info
2. Get child safety info
3. Get dosage forms
4. Get overdosage info

## Test Case

### Input
```json
{
    "drug_name": "amoxicillin"
}
```

### Expected Steps
1. Get pediatric use info
2. Get child safety info
3. Get dosage forms
4. Get overdosage info

## Usage Example

> **Note:** Replace `sk-b04409a1-b32b-4511-9aeb-22980abdc05c` with your own SCP Hub API Key. You can obtain one from the [SCP Platform](https://scphub.intern-ai.org.cn).

```python
import asyncio
import json
from contextlib import AsyncExitStack
from mcp import ClientSession
from mcp.client.streamable_http import streamablehttp_client
from mcp.client.sse import sse_client

SERVERS = {
    "fda-drug-server": "https://scp.intern-ai.org.cn/api/v1/mcp/14/Origene-FDADrug"
}

async def connect(url, stack):
    transport = streamablehttp_client(url=url, headers={"SCP-HUB-API-KEY": "sk-b04409a1-b32b-4511-9aeb-22980abdc05c"})
    read, write, _ = await stack.enter_async_context(transport)
    ctx = ClientSession(read, write)
    session = await stack.enter_async_context(ctx)
    await session.initialize()
    return session

def parse(result):
    try:
        if hasattr(result, 'content') and result.content:
            c = result.content[0]
            if hasattr(c, 'text'):
                try: return json.loads(c.text)
                except: return c.text
        return str(result)
    except: return str(result)

async def main():
    async with AsyncExitStack() as stack:
        # Connect to required servers
        sessions = {}
        sessions["fda-drug-server"] = await connect("https://scp.intern-ai.org.cn/api/v1/mcp/14/Origene-FDADrug", stack)

        # Execute workflow steps
        # Step 1: Get pediatric use info
        result_1 = await sessions["fda-drug-server"].call_tool("get_pediatric_use_info_by_drug_name", arguments={})
        data_1 = parse(result_1)
        print(f"Step 1 result: {json.dumps(data_1, indent=2, ensure_ascii=False)[:500]}")

        # Step 2: Get child safety info
        result_2 = await sessions["fda-drug-server"].call_tool("get_child_safety_info_by_drug_name", arguments={})
        data_2 = parse(result_2)
        print(f"Step 2 result: {json.dumps(data_2, indent=2, ensure_ascii=False)[:500]}")

        # Step 3: Get dosage forms
        result_3 = await sessions["fda-drug-server"].call_tool("get_dosage_forms_and_strengths_by_drug_name", arguments={})
        data_3 = parse(result_3)
        print(f"Step 3 result: {json.dumps(data_3, indent=2, ensure_ascii=False)[:500]}")

        # Step 4: Get overdosage info
        result_4 = await sessions["fda-drug-server"].call_tool("get_overdosage_info_by_drug_name", arguments={})
        data_4 = parse(result_4)
        print(f"Step 4 result: {json.dumps(data_4, indent=2, ensure_ascii=False)[:500]}")

        # Cleanup
        print("Workflow complete!")

if __name__ == "__main__":
    asyncio.run(main())
```

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