Add MCP prompt skills for workflow design, debugging, and extraction (#4739)
This commit is contained in:
Marc Kelechava
@@ -33,6 +33,7 @@ from .credential import (
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skyvern_credential_get,
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skyvern_credential_list,
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)
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from .prompts import build_workflow, debug_automation, extract_data
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from .session import (
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skyvern_session_close,
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skyvern_session_connect,
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@@ -213,7 +214,6 @@ Use `{{parameter_key}}` to reference workflow input parameters in any block fiel
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Common block types for workflow definitions:
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- **navigation** — take actions on a page: fill forms, click buttons, navigate multi-step flows (most common)
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- **extraction** — extract structured data from the current page
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- **task_v2** — complex tasks via natural language prompt (handles both actions and extraction)
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- **for_loop** — iterate over a list of items
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- **conditional** — branch based on conditions
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- **code** — run Python code for data transformation
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@@ -305,6 +305,11 @@ mcp.tool()(skyvern_workflow_run)
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mcp.tool()(skyvern_workflow_status)
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mcp.tool()(skyvern_workflow_cancel)
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# -- Prompts (methodology guides injected into LLM conversations) --
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mcp.prompt()(build_workflow)
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mcp.prompt()(debug_automation)
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mcp.prompt()(extract_data)
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__all__ = [
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"mcp",
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# Session
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@@ -346,4 +351,8 @@ __all__ = [
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"skyvern_workflow_run",
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"skyvern_workflow_status",
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"skyvern_workflow_cancel",
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# Prompts
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"build_workflow",
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"debug_automation",
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"extract_data",
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]
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@@ -85,7 +85,6 @@ BLOCK_TYPE_MAP: dict[str, type[BlockYAML]] = {
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BLOCK_SUMMARIES: dict[str, str] = {
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"navigation": "Take actions on a page: fill forms, click buttons, navigate multi-step flows (most common)",
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"extraction": "Extract structured data from the current page",
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"task_v2": "Complex tasks via natural language prompt — handles both actions and extraction",
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"for_loop": "Iterate over a list, executing nested blocks for each item",
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"conditional": "Branch based on Jinja2 expressions or AI prompts",
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"code": "Run Python code for data transformation",
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@@ -138,12 +137,6 @@ BLOCK_EXAMPLES: dict[str, dict[str, Any]] = {
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},
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},
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},
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"task_v2": {
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"block_type": "task_v2",
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"label": "book_flight",
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"url": "https://booking.example.com",
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"prompt": "Book a flight from {{ origin }} to {{ destination }} on {{ date }}",
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},
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"for_loop": {
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"block_type": "for_loop",
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"label": "process_each_url",
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@@ -297,7 +290,7 @@ async def skyvern_block_schema(
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block_type: Annotated[
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str | None,
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Field(
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description="Block type to get schema for (e.g., 'navigation', 'extraction', 'task_v2'). Omit to list all available types."
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description="Block type to get schema for (e.g., 'navigation', 'extraction', 'for_loop'). Omit to list all available types."
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),
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] = None,
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) -> dict[str, Any]:
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@@ -323,7 +316,7 @@ async def skyvern_block_schema(
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normalized = block_type.strip().lower()
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task_redirect = normalized == "task"
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task_redirect = normalized in ("task", "task_v2")
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if task_redirect:
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normalized = "navigation"
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@@ -344,7 +337,7 @@ async def skyvern_block_schema(
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warnings = (
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[
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"'task' is deprecated. Showing 'navigation' schema instead. Use 'navigation' for actions (requires navigation_goal) and 'extraction' for data extraction (requires data_extraction_goal + data_schema)."
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f"'{block_type}' is deprecated. Showing 'navigation' schema instead. Use 'navigation' for actions (requires navigation_goal) and 'extraction' for data extraction (requires data_extraction_goal + data_schema)."
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]
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if task_redirect
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else []
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@@ -426,9 +419,9 @@ async def skyvern_block_validate(
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try:
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block = adapter.validate_python(raw)
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warnings = []
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if block.block_type == "task":
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if block.block_type in ("task", "task_v2"):
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warnings.append(
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"'task' block type is deprecated. Use 'navigation' for actions and 'extraction' for data extraction."
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f"'{block.block_type}' block type is deprecated. Use 'navigation' for actions and 'extraction' for data extraction."
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)
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return make_result(
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action,
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430
skyvern/cli/mcp_tools/prompts.py
Normal file
430
skyvern/cli/mcp_tools/prompts.py
Normal file
@@ -0,0 +1,430 @@
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"""MCP prompt skills for Skyvern workflow design, debugging, and data extraction.
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These prompts are registered with @mcp.prompt() and injected into LLM conversations
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to guide Claude through Skyvern automation tasks. Each prompt teaches Claude to act
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as the USER — designing workflows and interpreting results — while Skyvern's AI
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handles the actual browser navigation.
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Milestone context:
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M3: Expose MCP functionality as Claude Skills (this module)
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M4: Expose Skyvern Workflow Copilot via MCP + Skills (these prompts power it)
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"""
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from typing import Annotated
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from pydantic import Field
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# ---------------------------------------------------------------------------
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# build_workflow
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# ---------------------------------------------------------------------------
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BUILD_WORKFLOW_CONTENT = """\
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# Build a Skyvern Workflow
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## How Skyvern Workflows Work
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You create a workflow definition (blocks + parameters). Skyvern executes it in a cloud browser.
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Each block runs in order, sharing the same browser session. The key differentiator is
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**navigation blocks**: you describe a goal in natural language and Skyvern's AI navigates the site
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autonomously — clicking, filling forms, handling popups, and retrying on failure. You do NOT
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need to specify selectors, XPaths, or step-by-step instructions.
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Workflows are versioned, parameterized, and reusable. Once a workflow works, you can re-run it
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with different inputs forever. Think of each workflow as a saved automation skill.
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Tools you will use: skyvern_workflow_create, skyvern_workflow_run, skyvern_workflow_status,
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skyvern_workflow_update, skyvern_block_schema, skyvern_block_validate.
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---
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## Design the Workflow
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### Default to navigation blocks
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navigation is the right choice for most steps. You give it a URL and a navigation_goal.
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Skyvern figures out the navigation at runtime.
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GOOD navigation_goal — describes the GOAL and what "done" looks like:
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"Search for '{{product_name}}' in the search bar, click the first result, and add it to cart.
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Done when the cart icon shows 1 item."
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BAD navigation_goal — describes HOW to do it (Skyvern already knows):
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"Find the input element with id='search', type the product name, press Enter, wait for
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results to load, find the first anchor tag in the results div, click it..."
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### Block type decision tree
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1. **navigation** (default) — AI-powered browser actions. Use when the step involves browsing,
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clicking, filling forms, or any multi-action sequence. Skyvern handles element finding,
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popup dismissal, scrolling, and retries.
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2. **extraction** — structured data extraction. Use when you need JSON output from a page
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(prices, tables, lists). Requires data_extraction_goal and data_schema.
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3. **for_loop** — iterate over a list. Use when you need to repeat blocks for each item
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in a parameter list (e.g., process each URL, each product).
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4. **goto_url** — simple navigation without any actions. Use to jump to a known URL.
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5. **login** — authenticate with stored credentials. Use for sites that require login.
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6. **code** — run Python for data transformation between blocks.
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7. **action** — single focused action on the current page (e.g., click one button).
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### One block per logical step
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Split workflows into small, focused blocks. Each block should do ONE thing.
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GOOD (3 blocks):
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Block 1 (navigation): "Go to the search page and search for '{{query}}'. Done when results load."
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Block 2 (navigation): "Click the first result and add it to cart. Done when cart shows 1 item."
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Block 3 (extraction): "Extract the product name, price, and availability from the cart page."
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BAD (1 block):
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Block 1 (navigation): "Search for the product, click the first result, add to cart, go to checkout,
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fill in shipping, enter payment, and submit the order."
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### Common workflow shapes
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**Search + Extract**: goto_url -> navigation (search) -> extraction (results)
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**Multi-page form**: navigation (page 1) -> navigation (page 2) -> navigation (page 3) -> extraction (confirmation)
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**Login + Action**: login (authenticate) -> navigation (do work) -> extraction (results)
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**Batch processing**: for_loop over URLs -> navigation (process each) -> extraction (gather data)
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---
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## Parameterize for Reuse
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Every workflow should accept parameters so it can be re-run with different inputs.
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### Declaring parameters
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Parameters are declared in the workflow_definition.parameters array:
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{"parameter_type": "workflow", "key": "company_name", "workflow_parameter_type": "string"}
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Supported types: string, integer, float, boolean, json, file_url.
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### Referencing parameters
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Use {{parameter_key}} in any block field — prompts, URLs, data schemas, goal descriptions.
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Skyvern substitutes values at runtime.
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### What to parameterize
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- Input data: names, addresses, search queries, product IDs
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- URLs: if the target URL varies between runs
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- Credentials: use the login block + credential_id parameter
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### What NOT to parameterize
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- Navigation instructions: these are the block prompts themselves
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- Block structure: if you need different flows, create separate workflows
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- Static site URLs: if the URL is always the same, hardcode it
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---
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## Test via Skyvern's Feedback Loop
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Do NOT try to get the workflow perfect on the first attempt. Use this iteration loop:
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### Step 1: Create and run
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Call skyvern_workflow_create with your definition, then skyvern_workflow_run with test parameters.
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### Step 2: Check status
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Poll with skyvern_workflow_status using the run_id. The response tells you:
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- Which block succeeded or failed
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- The failure_reason with what Skyvern saw on the page
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- Step count and timing
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### Step 3: Fix and re-run
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Based on the error feedback:
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- **"Prompt too vague"** — add specificity about what "done" looks like. Example: change
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"Fill in the form" to "Fill in the form with company name '{{name}}'. Done when the
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confirmation page shows 'Application Submitted'."
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- **"Element not found"** — add a navigation hint. Example: "Look for the search bar in the
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top navigation area" or "The form is inside an iframe."
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- **"Wrong page"** — add a URL check or split into smaller blocks so each one starts on the
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right page.
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- **"Timeout"** — the page may be slow. Increase max_retries on the block or add a wait block.
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Call skyvern_workflow_update with the fixed definition, then skyvern_workflow_run again.
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### Step 4: Verify output
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When the run succeeds, check the output field in skyvern_workflow_status. For extraction blocks,
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verify the JSON matches your data_schema.
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---
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## Quick Feasibility Check (Optional)
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If you are unsure whether Skyvern can handle a particular site, use skyvern_run_task as a probe
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BEFORE building a full workflow.
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skyvern_run_task is a one-shot autonomous agent. Give it a URL and a prompt — it navigates
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the site, takes actions, and reports results. No workflow definition needed.
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If it succeeds: turn the approach into a multi-block workflow for reuse.
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If it struggles: read the failure_reason, refine the prompt, and try again. Two or three
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iterations usually reveal whether the site is automatable and what prompt phrasing works.
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Do NOT open a manual browser session (skyvern_session_create) to explore the site before
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building a workflow. That approach bypasses Skyvern's AI and wastes time. skyvern_run_task
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gives you the same insight faster because Skyvern navigates the site for you.
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---
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## Prompt Refinement Tips
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When a navigation block fails, refine the navigation_goal:
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1. Use skyvern_run_task first to identify what Skyvern sees on the page.
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2. Add specificity: reference exact labels visible on the page.
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3. Describe what "done" looks like so Skyvern knows when to stop.
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Example workflow with clear goals:
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Block 1 (login): Authenticate with stored credentials.
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Block 2 (navigation): "Navigate to the settings page and open 'Notification Preferences'.
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Uncheck 'Marketing Emails' and check 'Security Alerts'. Click 'Save Changes'.
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Done when a success banner appears."
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Block 3 (extraction): "Extract the confirmation message."
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---
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## Pre-Flight Checklist
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Before calling skyvern_workflow_create, verify:
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1. Each block has a clear, single-responsibility goal (not a multi-page mega-prompt).
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2. Navigation block goals describe WHAT to achieve, not HOW to click.
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3. Every variable input uses {{parameter_key}} and is declared in parameters.
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4. Extraction blocks include a data_schema with the expected JSON structure.
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5. The block order matches the actual site flow (blocks share one browser session).
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6. Login is handled by a login block (not embedded in a navigation goal).
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7. You have test parameter values ready for the first skyvern_workflow_run call.
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8. Validate blocks with skyvern_block_validate before submitting the full definition.
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"""
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# ---------------------------------------------------------------------------
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# debug_automation
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# ---------------------------------------------------------------------------
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DEBUG_AUTOMATION_CONTENT = """\
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# Debugging Skyvern Automations
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When a workflow run or task fails, follow this structured process: read the error, diagnose the pattern,
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fix and re-run. Do NOT open a manual browser session to explore — Skyvern already tells you what went wrong.
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## Step 1: Read the Error
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Call skyvern_workflow_status with the workflow_run_id to get structured failure info.
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Key fields to examine:
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- **status**: "failed", "terminated", or "timed_out"
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- **failure_reason**: which block failed and why
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- **screenshot**: what the page looked like when the failure occurred
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- **extracted_information**: any partial data the AI did extract before failing
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If this was an interactive session failure (not a workflow), call skyvern_screenshot to see the current page state,
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then check the last tool response for error details.
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Record three things before proceeding:
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1. Which block (by label) failed
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2. The error type (timeout, element not found, wrong page, extraction empty, auth required)
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3. What the AI reported seeing on the page
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## Step 2: Diagnose the Pattern
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Skyvern failures fall into predictable categories. Match the error to a pattern and apply the standard fix.
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### Timeout (block exceeded max_steps or wall time)
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- Cause: prompt is too vague, so the AI explores without converging.
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- Fix: add specificity about what "done" looks like. Instead of "fill out the form", write "fill out the form and
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click the blue Submit button. Done when you see a confirmation message containing a reference number."
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- Also check: is max_steps too low? Default is reasonable, but complex forms may need more.
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### Element Not Found (AI could not locate the target element)
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- Cause: label mismatch (the button says "Continue" but the prompt says "Next"), or element loads asynchronously.
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- Fix: update the prompt to use the exact label visible on the page. If the element loads after a delay, add
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"wait for the page to fully load before acting" to the prompt.
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- If you know the exact label: switch that block to a navigation block with precise element references.
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### Wrong Page (block started on an unexpected page)
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- Cause: the previous block did not complete its page transition. The current block assumed it would land on page B
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but it is still on page A.
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- Fix: update the previous block's prompt to explicitly include the page transition. Add "click Continue and wait
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until the next page loads" instead of just "click Continue". Alternatively, add a goto_url block between them.
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### Extraction Empty (extraction returned null or empty object)
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- Cause: data loads dynamically (AJAX, infinite scroll) and was not present when the AI read the page. Or the
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extraction prompt does not match the page structure.
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- Fix: add "wait for the data table to fully load" to the prompt. If data requires scrolling, add a navigation
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block that scrolls first. If the prompt is wrong, update it to describe the data using labels visible on the page.
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### Auth Failure (redirected to login page)
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- Cause: workflow does not handle authentication, or session cookies expired.
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- Fix: add a login block at the start of the workflow, or use a browser_profile that has saved credentials.
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### Stuck / Hanging (run stays "running" indefinitely)
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- Action: call skyvern_workflow_cancel to stop the run. Then investigate: is the page showing a CAPTCHA, a
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modal dialog, or an unexpected redirect? Check the last screenshot from skyvern_workflow_status.
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### Rate Limited or Blocked (403, CAPTCHA, "unusual traffic" message)
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- Cause: the target site detected automation.
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- Fix: add a proxy (residential or ISP) to the workflow's proxy_location parameter. Reduce request frequency
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by adding wait blocks between actions. If CAPTCHA persists, report to the user — this may require manual
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intervention or a CAPTCHA-solving integration.
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## Step 3: Fix and Re-run
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Use skyvern_workflow_update to modify the failing block. Do NOT delete the workflow and recreate it.
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Fixing playbook:
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1. Update the failing block's prompt to address the diagnosed issue. Be specific: add exact labels, describe
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what "done" looks like, mention elements to wait for.
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2. If the navigation_goal is too vague for a complex form, make it more explicit — reference exact field labels,
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describe the form layout, and specify what "done" looks like.
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3. Re-run with skyvern_workflow_run using the same parameters as the failed run.
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4. Poll skyvern_workflow_status until the run completes. Check whether the previously failing block now passes.
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5. If it still fails with the same error: refine the prompt further. If it fails with a NEW error, restart
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diagnosis from Step 1.
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## Step 4: Escalation
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Not every failure can be fixed by prompt refinement. Know when to escalate.
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**Use action blocks for single-step precision** when:
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- A navigation block does too much — you only need one specific click or input
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- The page has multiple similar-looking elements and the AI picks the wrong one
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- The step involves a single focused action (e.g., click one button, toggle one checkbox)
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**Open a manual session (last resort)** when:
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- You cannot determine from error output what the page looks like
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- The site has unusual UI patterns not described in any error message
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- Use: skyvern_session_create, skyvern_navigate to the failing URL, skyvern_screenshot to see the page
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**Report to the user** when:
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- CAPTCHA blocks persist even with proxy rotation
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- The site requires 2FA or hardware authentication
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- Rate limiting cannot be avoided with proxies and delays
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- The site's terms of service explicitly prohibit automation
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"""
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# ---------------------------------------------------------------------------
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# extract_data
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# ---------------------------------------------------------------------------
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EXTRACT_DATA_CONTENT = """\
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# Data Extraction with Skyvern
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You design the data schema and describe what to extract. Skyvern's AI finds the elements, \
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||||
parses the page, and returns structured JSON. You never write selectors or scraping code.
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## Schema Design
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||||
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Always provide a `data_extraction_schema` (JSON Schema) so Skyvern returns typed, validated output.
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- Use `"type": "object"` for a single record (profile, summary, confirmation).
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- Use `"type": "array"` with `"items": { "type": "object", ... }` for lists (search results, table rows).
|
||||
- Mark critical fields as `"required"` so missing data surfaces as an error rather than null.
|
||||
- Choose descriptive property names that reflect the data, not the page layout \
|
||||
(`order_date` not `col_3`, `company_name` not `first_bold_text`).
|
||||
- Nest objects when the data is naturally hierarchical:
|
||||
`{ "seller": { "name": "...", "rating": 4.5 }, "price": { "amount": 29.99, "currency": "USD" } }`
|
||||
|
||||
## Writing Extraction Prompts
|
||||
|
||||
Describe WHAT to extract, not WHERE it is on the page. Skyvern's AI locates the data.
|
||||
|
||||
Good: "Extract all product names, prices, and star ratings from the search results"
|
||||
Bad: "Get the text from each div.product-card > span.price"
|
||||
|
||||
When the page has multiple similar sections, specify which one:
|
||||
"Extract order details from the table under 'Recent Orders', not 'Recommended Products'"
|
||||
|
||||
For simple extractions on a page you already navigated to, use `skyvern_extract` with a schema. \
|
||||
For extraction combined with navigation (log in, then go to dashboard, then extract), use \
|
||||
`skyvern_run_task` with a `data_extraction_schema` -- it handles the full flow in one call.
|
||||
|
||||
## Multi-Page Extraction
|
||||
|
||||
For paginated results, build a workflow with a `for_loop` block that iterates over page numbers \
|
||||
or "next" clicks. Each iteration uses an extraction block to pull that page's data.
|
||||
|
||||
For infinite-scroll pages, use `skyvern_run_task` with a prompt like \
|
||||
"scroll to load all results, then extract every item" -- Skyvern handles the scrolling.
|
||||
|
||||
For detail-page drilling (list page -> click each item -> extract details), build a workflow: \
|
||||
extraction block to get the list of links, then a `for_loop` block that visits each link and \
|
||||
extracts the detail fields.
|
||||
|
||||
## Validate Results
|
||||
|
||||
After extraction, check the returned data before using it:
|
||||
- Verify record count matches expectations (e.g., "I expected ~50 results but got 3").
|
||||
- Check for null or empty fields that should have values.
|
||||
- If the data looks wrong, refine the extraction prompt (be more specific about which section \
|
||||
or what the data looks like), not the schema.
|
||||
- Use `skyvern_validate` for page-level assertions before extracting \
|
||||
("Is this the search results page?" / "Are there at least 10 results visible?").
|
||||
"""
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Prompt functions
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
|
||||
def build_workflow(
|
||||
task_description: Annotated[
|
||||
str,
|
||||
Field(description="What the workflow should automate, e.g. 'Fill out a tax form on irs.gov'"),
|
||||
] = "",
|
||||
) -> str:
|
||||
"""Guide for building a Skyvern workflow. Invoke this prompt when a user asks to create,
|
||||
design, or build a browser automation workflow. The guide covers block selection, prompt
|
||||
writing, parameterization, testing, and iteration."""
|
||||
if task_description:
|
||||
return f"{BUILD_WORKFLOW_CONTENT}\n---\n\nUser's automation goal:\n```\n{task_description}\n```\n"
|
||||
return BUILD_WORKFLOW_CONTENT
|
||||
|
||||
|
||||
def debug_automation(
|
||||
error_or_symptom: Annotated[
|
||||
str,
|
||||
Field(description="The error message or symptom to diagnose, e.g. 'Timeout after 30s on login page'"),
|
||||
] = "",
|
||||
) -> str:
|
||||
"""Diagnose and fix a failing Skyvern workflow or task.
|
||||
|
||||
Guides you through reading Skyvern's structured error output, matching the failure to a known pattern,
|
||||
and fixing the workflow by updating block prompts — without manually exploring in a browser.
|
||||
"""
|
||||
parts = [DEBUG_AUTOMATION_CONTENT]
|
||||
if error_or_symptom:
|
||||
parts.append(
|
||||
f"\n---\n\nThe user reports this error or symptom:\n```\n{error_or_symptom}\n```\n\n"
|
||||
"Start at Step 1: call skyvern_workflow_status (or check the last tool response) to get the full error "
|
||||
"details. Then match it to a pattern in Step 2 and apply the fix from Step 3."
|
||||
)
|
||||
return "\n".join(parts)
|
||||
|
||||
|
||||
def extract_data(
|
||||
target_description: Annotated[
|
||||
str,
|
||||
Field(description="What data to extract, e.g. 'Product prices and ratings from Amazon search results'"),
|
||||
] = "",
|
||||
) -> str:
|
||||
"""Guide for extracting structured data from websites using Skyvern.
|
||||
|
||||
Covers schema design, writing extraction prompts, multi-page extraction patterns, and result
|
||||
validation. Call this prompt before building an extraction workflow or writing extraction calls.
|
||||
"""
|
||||
suffix = ""
|
||||
if target_description:
|
||||
suffix = (
|
||||
f"\n\nApply the above methodology to extract:\n```\n{target_description}\n```\n"
|
||||
"Design a JSON Schema for the output, choose the right tool "
|
||||
"(skyvern_extract for current page, skyvern_run_task for navigate-then-extract), "
|
||||
"and validate the results."
|
||||
)
|
||||
return EXTRACT_DATA_CONTENT + suffix
|
||||
@@ -349,7 +349,7 @@ async def skyvern_workflow_create(
|
||||
Best practice: use one block per logical step with a short focused prompt (2-3 sentences).
|
||||
Use "navigation" blocks for actions (filling forms, clicking) and "extraction" blocks for pulling data.
|
||||
Do NOT use the deprecated "task" block type.
|
||||
Common block types: navigation, extraction, task_v2, for_loop, conditional, code, text_prompt, action, wait, login.
|
||||
Common block types: navigation, extraction, for_loop, conditional, code, text_prompt, action, wait, login.
|
||||
Call skyvern_block_schema() for the full list with schemas and examples.
|
||||
|
||||
Example JSON definition (multi-block EIN application):
|
||||
|
||||
Reference in New Issue
Block a user