Add Skill: langgraph-csv-workflow

Extracted from: https://github.com/jwwelbor/AgentMap.git Score: 1.0
2026-08-06 14:41:00 +00:00
parent 271f79610d
commit 2f2c7cf5fb
5 changed files with 143 additions and 0 deletions
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+{
+  "name": "langgraph-csv-workflow",
+  "version": "1.0.0",
+  "goal": "Transform simple CSV files into powerful AI agent workflows using LangGraph orchestration",
+  "inputs": [
+    "CSV workflow files with columns: graph_name, node_name, agent_type, next_node, on_failure, prompt, input_fields, output_field",
+    "LLM provider configuration (OpenAI, Anthropic, Google) in agentmap_config.yaml",
+    "Storage configuration for CSV/JSON/Vector DBs in agentmap_config_storage.yaml"
+  ],
+  "steps": [
+    "Define workflow in CSV format specifying graph nodes, agent types, and data flow between them",
+    "Configure LLM providers and storage backends in the agentmap configuration files",
+    "Execute the workflow using the agentmap CLI or Python API"
+  ],
+  "outputs": [
+    "Executed workflow with agent decisions and state transitions",
+    "Traced execution path through the graph nodes",
+    "Logged agent interactions and output fields populated"
+  ],
+  "failure_modes": [
+    "Invalid CSV format causing parse errors during workflow loading",
+    "Missing or misconfigured LLM provider credentials leading to runtime failures",
+    "Incorrect agent configuration (e.g., missing input_fields) causing processing errors"
+  ],
+  "confidence": 0.95,
+  "explanation": "AgentMap provides a declarative pattern where workflows are defined in CSV files with specific columns describing graph nodes, agent types, and data flow. This pattern can be adapted to create multi-agent systems with LangGraph, supporting various LLM providers and storage backends. The workflow is reusable across different use cases by simply modifying the CSV definition.",
+  "source_repo": "https://github.com/jwwelbor/AgentMap.git",
+  "score": 1.0
+}