Add Skill: blacknode-text-concatenation-workflow

Extracted from: https://github.com/temiroff/Blacknode.git
Score: 1.0

skills/blacknode-text-concatenation-workflow/SKILL.md

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+---
+name: blacknode-text-concatenation-workflow
+version: 1.0.0
+description: Concatenate two text strings using a Blacknode graph of Text, Concat,
+  and Output nodes.
+inputs:
+- 'text_a: string'
+- 'text_b: string'
+steps:
+- Initialize a Blacknode Graph object.
+- Add a Text node with parameter value set to text_a.
+- Add a second Text node with parameter value set to text_b.
+- Add a Concat node (no parameters required).
+- Add an Output node (no parameters required).
+- Connect the 'value' output port of the first Text node to the 'a' input port of
+  the Concat node.
+- Connect the 'value' output port of the second Text node to the 'b' input port of
+  the Concat node.
+- Connect the 'value' output port of the Concat node to the 'value' input port of
+  the Output node.
+- Evaluate the graph by cooking the Output node's 'value' port to obtain the concatenated
+  result.
+outputs:
+- 'concatenated_text: string'
+tags: []
+metadata:
+  source_repo: https://github.com/temiroff/Blacknode.git
+  extracted_at: ''
+  confidence: 0.95
+---
+
+# blacknode-text-concatenation-workflow
+
+Concatenate two text strings using a Blacknode graph of Text, Concat, and Output nodes.
+
+## Steps
+
+1. Initialize a Blacknode Graph object.
+2. Add a Text node with parameter value set to text_a.
+3. Add a second Text node with parameter value set to text_b.
+4. Add a Concat node (no parameters required).
+5. Add an Output node (no parameters required).
+6. Connect the 'value' output port of the first Text node to the 'a' input port of the Concat node.
+7. Connect the 'value' output port of the second Text node to the 'b' input port of the Concat node.
+8. Connect the 'value' output port of the Concat node to the 'value' input port of the Output node.
+9. Evaluate the graph by cooking the Output node's 'value' port to obtain the concatenated result.
+
+## Inputs
+
+- text_a: string
+- text_b: string
+
+## Outputs
+
+- concatenated_text: string
+
+## Failure Modes
+
+- Node types 'Text', 'Concat', or 'Output' not registered in Blacknode runtime
+- Port name mismatches during edge creation
+- Missing input values causing empty concatenation
+- Graph evaluation error if cycles or disconnected required ports
+
+## Source
+
+Extracted from: [https://github.com/temiroff/Blacknode.git](https://github.com/temiroff/Blacknode.git)
+Confidence: 0.95

skills/blacknode-text-concatenation-workflow/commands.md

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+# Commands: blacknode-text-concatenation-workflow
+
+## Available Commands
+
+- `/skill blacknode-text-concatenation-workflow` — Load this skill
+- `/run blacknode-text-concatenation-workflow` — Execute workflow

skills/blacknode-text-concatenation-workflow/examples.md

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+# Examples: blacknode-text-concatenation-workflow
+
+## Usage Example
+
+```python
+# How to use this skill
+# Inputs: text_a: string, text_b: string
+# Process: Initialize a Blacknode Graph object. → Add a Text node with parameter value set to text_a. → Add a second Text node with parameter value set to text_b.
+# Outputs: concatenated_text: string
+```

skills/blacknode-text-concatenation-workflow/metadata.json

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+{
+  "name": "blacknode-text-concatenation-workflow",
+  "version": "1.0.0",
+  "goal": "Concatenate two text strings using a Blacknode graph of Text, Concat, and Output nodes.",
+  "inputs": [
+    "text_a: string",
+    "text_b: string"
+  ],
+  "steps": [
+    "Initialize a Blacknode Graph object.",
+    "Add a Text node with parameter value set to text_a.",
+    "Add a second Text node with parameter value set to text_b.",
+    "Add a Concat node (no parameters required).",
+    "Add an Output node (no parameters required).",
+    "Connect the 'value' output port of the first Text node to the 'a' input port of the Concat node.",
+    "Connect the 'value' output port of the second Text node to the 'b' input port of the Concat node.",
+    "Connect the 'value' output port of the Concat node to the 'value' input port of the Output node.",
+    "Evaluate the graph by cooking the Output node's 'value' port to obtain the concatenated result."
+  ],
+  "outputs": [
+    "concatenated_text: string"
+  ],
+  "failure_modes": [
+    "Node types 'Text', 'Concat', or 'Output' not registered in Blacknode runtime",
+    "Port name mismatches during edge creation",
+    "Missing input values causing empty concatenation",
+    "Graph evaluation error if cycles or disconnected required ports"
+  ],
+  "confidence": 0.95,
+  "explanation": "Extracted from examples/converted_text_pipeline.py and referenced templates/text-pipeline.json in the Blacknode repo. This workflow is a foundational, dependency-free pattern for building directed graphs of typed nodes and is applicable to any simple data combination task.",
+  "source_repo": "https://github.com/temiroff/Blacknode.git",
+  "score": 1.0
+}

skills/blacknode-text-concatenation-workflow/tests.md

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

skills/conditional-review-workflow/SKILL.md

@@ -1,56 +0,0 @@
----
-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

@@ -1,6 +0,0 @@
-# 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

@@ -1,10 +0,0 @@
-# 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

@@ -1,26 +0,0 @@
-{
-  "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
-}