How to Summarise Salesforce with Claude Code

import os

import anthropic
import requests

BASE_URL = "https://api.enconvert.com/v2"
headers = {
    "X-API-Key": os.environ["ENCONVERT_API_KEY"],
    "Content-Type": "application/json",
}

article_urls = [
    "https://help.salesforce.com/s/articleView?id=sf.flow_concepts.htm&type=5",
    "https://help.salesforce.com/s/articleView?id=sf.custom_object_overview.htm&type=5",
    "https://help.salesforce.com/s/articleView?id=sf.users_permissions_overview.htm&type=5",
]

# One synchronous call: no job_id, no polling, no download step
response = requests.post(
    f"{BASE_URL}/distill",
    headers=headers,
    json={
        "urls": article_urls,
        "schema": {
            "title": "The article title",
            "body": "The full article body text, excluding navigation and sidebars",
            "article_type": "Whether this is a Help documentation article or a Knowledge article",
            "product_area": "The Salesforce product or feature area the article covers",
        },
    },
    timeout=120,  # increase for larger batches
)

# Distill is available on paid plans only, and the free tier returns 402
if response.status_code == 402:
    raise RuntimeError("Distill requires a paid plan")
response.raise_for_status()

# Failed pages come back as rows with a failed status, not as errors
articles = []
for result in response.json()["results"]:
    if result["status"] != "completed":
        print(f"Skipped {result['url']}: {result['status']}")
        continue

    if result.get("render_quality", 1.0) < 0.5:
        # a low score can mean a login wall or challenge page
        print(f"Low render quality for {result['url']}: {result['render_quality']}")
        continue

    data = result.get("data") or {}  # keys match schema exactly: title, body, article_type, product_area
    articles.append(
        f"Source: {result['url']}\n"
        f"Title: {data.get('title')}\n"
        f"Type: {data.get('article_type')}\n"
        f"Product area: {data.get('product_area')}\n\n"
        f"{data.get('body')}"
    )

if not articles:
    raise RuntimeError("No Salesforce articles passed extraction checks")

# Pass the extracted data into the Claude context window
client = anthropic.Anthropic(api_key=os.environ["ANTHROPIC_API_KEY"])
message = client.messages.create(
    model="claude-sonnet-5-5",
    max_tokens=4096,
    system=(
        "You answer questions about Salesforce features. Use only the articles provided, "
        "and cite the source URL for every statement you make."
    ),
    messages=[
        {
            "role": "user",
            "content": (
                "Articles:\n\n" + "\n\n---\n\n".join(articles) +
                "\n\nQuestion: Which Salesforce product areas do these articles cover, and what does each one explain?"
            ),
        }
    ],
)

for block in message.content:
    if block.type == "text":
        print(block.text)