[Docs][fix examples and docs] [GraphWorkflow][add_nodes]

Author: kyegomez

docs/examples/marketplace_publishing_quickstart.md

@@ -74,9 +74,6 @@ my_agent = Agent(
         }
     ],
 
-    # Required: Tags and capabilities
-    tags=["finance", "crypto", "stocks", "analysis"],
-    capabilities=["market-analysis", "risk-assessment", "portfolio-optimization"]
 )
 ```
 
@@ -170,8 +167,6 @@ print(result)
 |-------|------|-------------|
 | `publish_to_marketplace` | `bool` | Set to `True` to enable publishing |
 | `use_cases` | `List[Dict]` | List of use case dictionaries with `title` and `description` |
-| `tags` | `List[str]` | Keywords for discovery |
-| `capabilities` | `List[str]` | Agent capabilities for matching |
 
 ### Use Case Format
 
@@ -243,31 +238,15 @@ print(response)
 
 ---
 
-## Monetization
-
-To create a paid agent:
-
-```python
-from swarms.utils.swarms_marketplace_utils import add_prompt_to_marketplace
-
-response = add_prompt_to_marketplace(
-    name="Premium Analysis Agent",
-    prompt="Your premium agent prompt...",
-    description="Advanced analysis capabilities",
-    use_cases=[...],
-    tags="premium, advanced",
-    category="finance",
-    is_free=False,         # Paid agent
-    price_usd=9.99         # Price per use
-)
-```
 
 ---
 
 ## Next Steps
 
-- Visit [Swarms Marketplace](https://swarms.world) to browse published agents
-- Learn about [Marketplace Documentation](../swarms_platform/share_and_discover.md)
-- Explore [Monetization Options](../swarms_platform/monetize.md)
-- See [API Key Management](../swarms_platform/apikeys.md)
+| Next Step | Description |
+|-----------|-------------|
+| [Swarms Marketplace](https://swarms.world) | Browse published agents |
+| [Marketplace Documentation](../swarms_platform/share_and_discover.md) | Learn how to publish and discover agents |
+| [Monetization Options](../swarms_platform/monetize.md) | Explore ways to monetize your agent |
+| [API Key Management](../swarms_platform/apikeys.md) | Manage your API keys for publishing and access |
 

examples/multi_agent/graphworkflow_examples/graph_workflow_basic.py

@@ -1,23 +1,22 @@
-
 from swarms.structs.graph_workflow import GraphWorkflow
 from swarms.structs.agent import Agent
 
 agent_one = Agent(
-    agent_name="research_agent", 
-    model_name="gpt-4o-mini", 
+    agent_name="research_agent",
+    model_name="gpt-4o-mini",
     name="Research Agent",
-    agent_description="Agent responsible for gathering and summarizing research information."
+    agent_description="Agent responsible for gathering and summarizing research information.",
 )
 agent_two = Agent(
-    agent_name="research_agent_two", 
+    agent_name="research_agent_two",
     model_name="gpt-4o-mini",
     name="Analysis Agent",
-    agent_description="Agent that analyzes the research data provided and processes insights."
+    agent_description="Agent that analyzes the research data provided and processes insights.",
 )
 agent_three = Agent(
-    agent_name="research_agent_three", 
+    agent_name="research_agent_three",
     model_name="gpt-4o-mini",
-    agent_description="Agent tasked with structuring analysis into a final report or output."
+    agent_description="Agent tasked with structuring analysis into a final report or output.",
 )
 
 # Create workflow with backend selection
@@ -41,4 +40,4 @@
 task = "Complete a simple task"
 results = workflow.run(task)
 
-print(results)
+print(results)

examples/single_agent/README.md

@@ -7,7 +7,6 @@ This directory contains examples demonstrating single agent patterns, configurat
 - [persistent_legal_agent.py](demos/persistent_legal_agent.py) - Legal document processing agent
 
 ## External Agents
-- [custom_agent_example.py](external_agents/custom_agent_example.py) - Custom agent implementation
 - [openai_assistant_wrapper.py](external_agents/openai_assistant_wrapper.py) - OpenAI Assistant integration
 
 ## LLM Integrations

examples/single_agent/external_agents/README.md

@@ -4,7 +4,6 @@ This directory contains examples demonstrating integration with external agent s
 
 ## Examples
 
-- [custom_agent_example.py](custom_agent_example.py) - Custom agent implementation
 - [openai_assistant_wrapper.py](openai_assistant_wrapper.py) - OpenAI Assistant integration wrapper
 
 ## Overview

examples/single_agent/external_agents/custom_agent_example.py

@@ -1,7 +1,9 @@
 import json
 from swarms import Agent
 
-blood_analysis_system_prompt = """You are a clinical laboratory data analyst assistant focused on hematology and basic metabolic panels.
+blood_analysis_system_prompt = """
+You are a clinical laboratory data analyst assistant focused on hematology and basic metabolic panels.
+
 Your goals:
 1) Interpret common blood test panels (CBC, CMP/BMP, lipid panel, HbA1c, thyroid panels) based on provided values, reference ranges, flags, and units.
 2) Provide structured findings: out-of-range markers, degree of deviation, likely clinical significance, and differential considerations.

examples/single_agent/utils/medical_agent_add_to_marketplace.py

@@ -1,27 +1,26 @@
-
 from swarms.structs.graph_workflow import GraphWorkflow
 from swarms.structs.agent import Agent
 
 agent_one = Agent(
-    agent_name="research_agent", 
-    model_name="claude-haiku-4-5", 
+    agent_name="research_agent",
+    model_name="claude-haiku-4-5",
     top_p=None,
     temperature=None,
-    agent_description="Agent responsible for gathering and summarizing research information."
+    agent_description="Agent responsible for gathering and summarizing research information.",
 )
 agent_two = Agent(
-    agent_name="research_agent_two", 
+    agent_name="research_agent_two",
     model_name="claude-haiku-4-5",
     top_p=None,
     temperature=None,
-    agent_description="Agent that analyzes the research data provided and processes insights."
+    agent_description="Agent that analyzes the research data provided and processes insights.",
 )
 agent_three = Agent(
-    agent_name="research_agent_three", 
+    agent_name="research_agent_three",
     model_name="claude-haiku-4-5",
     top_p=None,
     temperature=None,
-    agent_description="Agent tasked with structuring analysis into a final report or output."
+    agent_description="Agent tasked with structuring analysis into a final report or output.",
 )
 
 # Create workflow with backend selection
@@ -45,4 +44,4 @@
 task = "Analyze the best mining companies in the US"
 results = workflow.run(task)
 
-print(results)
+print(results)