Add Skill: conditional-review-workflow

Extracted from: https://github.com/jwwelbor/AgentMap.git
Score: 1.0

skills/conditional-review-workflow/SKILL.md

@@ -0,0 +1,56 @@
+---
+name: conditional-review-workflow
+version: 1.0.0
+description: Process a user request through branching logic to approve or reject it,
+  producing a routed decision result
+inputs:
+- 'request: string - The user''s request or input collected at runtime via the input
+  agent'
+steps:
+- 'Start: Input agent collects the user request and stores it in the ''request'' state
+  field, then routes to Classify node'
+- 'Classify: Branching agent evaluates the ''request'' field and routes to Approve
+  node on success or Reject node on failure (on_failure)'
+- 'Approve: Default agent formats an approval message using the request and stores
+  it in the ''result'' output field'
+- 'Reject: Default agent formats a rejection message using the request and stores
+  it in the ''result'' output field'
+outputs:
+- 'result: string - Final message indicating whether the request was approved or rejected,
+  containing the original request'
+tags: []
+metadata:
+  source_repo: https://github.com/jwwelbor/AgentMap.git
+  extracted_at: ''
+  confidence: 0.85
+---
+
+# conditional-review-workflow
+
+Process a user request through branching logic to approve or reject it, producing a routed decision result
+
+## Steps
+
+1. Start: Input agent collects the user request and stores it in the 'request' state field, then routes to Classify node
+2. Classify: Branching agent evaluates the 'request' field and routes to Approve node on success or Reject node on failure (on_failure)
+3. Approve: Default agent formats an approval message using the request and stores it in the 'result' output field
+4. Reject: Default agent formats a rejection message using the request and stores it in the 'result' output field
+
+## Inputs
+
+- request: string - The user's request or input collected at runtime via the input agent
+
+## Outputs
+
+- result: string - Final message indicating whether the request was approved or rejected, containing the original request
+
+## Failure Modes
+
+- Input collection failure - user provides no or invalid input (no explicit on_failure defined for Start node in example)
+- Branching classification failure - if branching agent cannot evaluate, it routes to Reject via on_failure configuration
+- LLM provider unavailability - if branching or agents rely on LLM backends that are misconfigured or offline
+
+## Source
+
+Extracted from: [https://github.com/jwwelbor/AgentMap.git](https://github.com/jwwelbor/AgentMap.git)
+Confidence: 0.85

skills/conditional-review-workflow/commands.md

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+# Commands: conditional-review-workflow
+
+## Available Commands
+
+- `/skill conditional-review-workflow` — Load this skill
+- `/run conditional-review-workflow` — Execute workflow

skills/conditional-review-workflow/examples.md

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+# Examples: conditional-review-workflow
+
+## Usage Example
+
+```python
+# How to use this skill
+# Inputs: request: string - The user's request or input collected at runtime via the input agent
+# Process: Start: Input agent collects the user request and stores it in the 'request' state field, then routes to Classify node → Classify: Branching agent evaluates the 'request' field and routes to Approve node on success or Reject node on failure (on_failure) → Approve: Default agent formats an approval message using the request and stores it in the 'result' output field
+# Outputs: result: string - Final message indicating whether the request was approved or rejected, containing the original request
+```

skills/conditional-review-workflow/metadata.json

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+{
+  "name": "conditional-review-workflow",
+  "version": "1.0.0",
+  "goal": "Process a user request through branching logic to approve or reject it, producing a routed decision result",
+  "inputs": [
+    "request: string - The user's request or input collected at runtime via the input agent"
+  ],
+  "steps": [
+    "Start: Input agent collects the user request and stores it in the 'request' state field, then routes to Classify node",
+    "Classify: Branching agent evaluates the 'request' field and routes to Approve node on success or Reject node on failure (on_failure)",
+    "Approve: Default agent formats an approval message using the request and stores it in the 'result' output field",
+    "Reject: Default agent formats a rejection message using the request and stores it in the 'result' output field"
+  ],
+  "outputs": [
+    "result: string - Final message indicating whether the request was approved or rejected, containing the original request"
+  ],
+  "failure_modes": [
+    "Input collection failure - user provides no or invalid input (no explicit on_failure defined for Start node in example)",
+    "Branching classification failure - if branching agent cannot evaluate, it routes to Reject via on_failure configuration",
+    "LLM provider unavailability - if branching or agents rely on LLM backends that are misconfigured or offline"
+  ],
+  "confidence": 0.85,
+  "explanation": "Extracted from AgentMap's documented CSV workflow example (ReviewFlow). This is a reusable conditional routing pattern that can be adapted for any approval/rejection, triage, or binary-decision scenario by modifying the branching prompt and agent types. The CSV-based declarative format makes it portable across the AgentMap framework.",
+  "source_repo": "https://github.com/jwwelbor/AgentMap.git",
+  "score": 1.0
+}

skills/conditional-review-workflow/tests.md

@@ -1,4 +1,4 @@
-# Tests: text-concatenation
+# Tests: conditional-review-workflow
 
 ## Test Checklist
 

skills/text-concatenation/SKILL.md

@@ -1,61 +0,0 @@
----
-name: text-concatenation
-version: 1.0.0
-description: Concatenate two text inputs using Blacknode node graph
-inputs:
-- text_a
-- text_b
-steps:
-- Create a Blacknode Graph instance
-- Add a Text node with param value set to text_a
-- Add a second Text node with param value set to text_b
-- Add a Concat node that accepts inputs 'a' and 'b' and outputs 'value'
-- Add an Output node with input port 'value'
-- Connect first Text node 'value' port to Concat 'a' port
-- Connect second Text node 'value' port to Concat 'b' port
-- Connect Concat 'value' port to Output 'value' port
-- Invoke graph cook on Output 'value' to evaluate and return result
-outputs:
-- concatenated_text
-tags: []
-metadata:
-  source_repo: https://github.com/temiroff/Blacknode.git
-  extracted_at: ''
-  confidence: 0.9
----
-
-# text-concatenation
-
-Concatenate two text inputs using Blacknode node graph
-
-## Steps
-
-1. Create a Blacknode Graph instance
-2. Add a Text node with param value set to text_a
-3. Add a second Text node with param value set to text_b
-4. Add a Concat node that accepts inputs 'a' and 'b' and outputs 'value'
-5. Add an Output node with input port 'value'
-6. Connect first Text node 'value' port to Concat 'a' port
-7. Connect second Text node 'value' port to Concat 'b' port
-8. Connect Concat 'value' port to Output 'value' port
-9. Invoke graph cook on Output 'value' to evaluate and return result
-
-## Inputs
-
-- text_a
-- text_b
-
-## Outputs
-
-- concatenated_text
-
-## Failure Modes
-
-- Port name mismatch causes connection error
-- Missing runtime or graph not initialized
-- Cook on nonexistent node returns error
-
-## Source
-
-Extracted from: [https://github.com/temiroff/Blacknode.git](https://github.com/temiroff/Blacknode.git)
-Confidence: 0.9

skills/text-concatenation/commands.md

@@ -1,6 +0,0 @@
-# Commands: text-concatenation
-
-## Available Commands
-
-- `/skill text-concatenation` — Load this skill
-- `/run text-concatenation` — Execute workflow

skills/text-concatenation/examples.md

@@ -1,10 +0,0 @@
-# Examples: text-concatenation
-
-## Usage Example
-
-```python
-# How to use this skill
-# Inputs: text_a, text_b
-# Process: Create a Blacknode Graph instance → Add a Text node with param value set to text_a → Add a second Text node with param value set to text_b
-# Outputs: concatenated_text
-```

skills/text-concatenation/metadata.json

@@ -1,32 +0,0 @@
-{
-  "name": "text-concatenation",
-  "version": "1.0.0",
-  "goal": "Concatenate two text inputs using Blacknode node graph",
-  "inputs": [
-    "text_a",
-    "text_b"
-  ],
-  "steps": [
-    "Create a Blacknode Graph instance",
-    "Add a Text node with param value set to text_a",
-    "Add a second Text node with param value set to text_b",
-    "Add a Concat node that accepts inputs 'a' and 'b' and outputs 'value'",
-    "Add an Output node with input port 'value'",
-    "Connect first Text node 'value' port to Concat 'a' port",
-    "Connect second Text node 'value' port to Concat 'b' port",
-    "Connect Concat 'value' port to Output 'value' port",
-    "Invoke graph cook on Output 'value' to evaluate and return result"
-  ],
-  "outputs": [
-    "concatenated_text"
-  ],
-  "failure_modes": [
-    "Port name mismatch causes connection error",
-    "Missing runtime or graph not initialized",
-    "Cook on nonexistent node returns error"
-  ],
-  "confidence": 0.9,
-  "explanation": "The repo contains example converted workflows; converted_text_pipeline.py demonstrates a simple reusable pattern of two source nodes feeding a concatenation node into an output, applicable to any string joining task in Blacknode.",
-  "source_repo": "https://github.com/temiroff/Blacknode.git",
-  "score": 1.0
-}