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---
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name: conditional-request-review-workflow
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version: 1.0.0
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description: Classify an input request and route it to an approval or rejection path,
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producing a final result message.
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inputs:
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- request
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steps:
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- Start node (agent_type=input) collects the user request and stores it in state field
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'request'.
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- Classify node (agent_type=branching) reads 'request', makes a branching decision,
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and on success goes to Approve, on failure goes to Reject; stores decision in 'decision'.
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- Approve node (agent_type=default) formats an approval message using 'request' and
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writes to 'result'.
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- Reject node (agent_type=default) formats a rejection message using 'request' and
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writes to 'result' (also used if Classify fails).
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outputs:
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- result
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tags: []
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metadata:
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source_repo: https://github.com/jwwelbor/AgentMap.git
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extracted_at: ''
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confidence: 0.85
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---
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# conditional-request-review-workflow
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Classify an input request and route it to an approval or rejection path, producing a final result message.
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## Steps
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1. Start node (agent_type=input) collects the user request and stores it in state field 'request'.
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2. Classify node (agent_type=branching) reads 'request', makes a branching decision, and on success goes to Approve, on failure goes to Reject; stores decision in 'decision'.
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3. Approve node (agent_type=default) formats an approval message using 'request' and writes to 'result'.
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4. Reject node (agent_type=default) formats a rejection message using 'request' and writes to 'result' (also used if Classify fails).
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## Inputs
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- request
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## Outputs
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- result
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## Failure Modes
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- If branching classification fails, workflow defaults to Reject node via on_failure.
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- Input node has no defined on_failure, so workflow may terminate unexpectedly if input collection fails.
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## Source
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Extracted from: [https://github.com/jwwelbor/AgentMap.git](https://github.com/jwwelbor/AgentMap.git)
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Confidence: 0.85
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@@ -1,6 +0,0 @@
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# Commands: conditional-request-review-workflow
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## Available Commands
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- `/skill conditional-request-review-workflow` — Load this skill
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- `/run conditional-request-review-workflow` — Execute workflow
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# Examples: conditional-request-review-workflow
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## Usage Example
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```python
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# How to use this skill
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# Inputs: request
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# Process: Start node (agent_type=input) collects the user request and stores it in state field 'request'. → Classify node (agent_type=branching) reads 'request', makes a branching decision, and on success goes to Approve, on failure goes to Reject; stores decision in 'decision'. → Approve node (agent_type=default) formats an approval message using 'request' and writes to 'result'.
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# Outputs: result
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```
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@@ -1,25 +0,0 @@
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{
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"name": "conditional-request-review-workflow",
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"version": "1.0.0",
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"goal": "Classify an input request and route it to an approval or rejection path, producing a final result message.",
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"inputs": [
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"request"
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],
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"steps": [
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"Start node (agent_type=input) collects the user request and stores it in state field 'request'.",
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"Classify node (agent_type=branching) reads 'request', makes a branching decision, and on success goes to Approve, on failure goes to Reject; stores decision in 'decision'.",
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"Approve node (agent_type=default) formats an approval message using 'request' and writes to 'result'.",
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"Reject node (agent_type=default) formats a rejection message using 'request' and writes to 'result' (also used if Classify fails)."
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],
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"outputs": [
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"result"
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],
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"failure_modes": [
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"If branching classification fails, workflow defaults to Reject node via on_failure.",
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"Input node has no defined on_failure, so workflow may terminate unexpectedly if input collection fails."
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],
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"confidence": 0.85,
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"explanation": "This workflow is directly taken from the AgentMap README 'ReviewFlow' CSV example. It represents a reusable declarative pattern for conditional routing based on input content, adaptable to many binary decision tasks.",
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"source_repo": "https://github.com/jwwelbor/AgentMap.git",
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"score": 1.0
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}
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---
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name: text-concatenation-pipeline
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version: 1.0.0
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description: Combine two text inputs into a single output string using a Blacknode
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node graph.
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inputs:
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- text_a (string)
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- text_b (string)
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steps:
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- Instantiate a Text node with parameter value set to text_a
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- Instantiate a Text node with parameter value set to text_b
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- Instantiate a Concat node with no parameters
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- Instantiate an Output node
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- Connect output port 'value' of first Text node to input port 'a' of Concat node
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- Connect output port 'value' of second Text node to input port 'b' of Concat node
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- Connect output port 'value' of Concat node to input port 'value' of Output node
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- Execute graph by cooking the Output node's 'value' port to obtain result
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outputs:
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- concatenated_text (string)
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tags: []
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metadata:
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source_repo: https://github.com/temiroff/Blacknode.git
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extracted_at: ''
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confidence: 0.95
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---
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# text-concatenation-pipeline
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Combine two text inputs into a single output string using a Blacknode node graph.
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## Steps
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1. Instantiate a Text node with parameter value set to text_a
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2. Instantiate a Text node with parameter value set to text_b
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3. Instantiate a Concat node with no parameters
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4. Instantiate an Output node
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5. Connect output port 'value' of first Text node to input port 'a' of Concat node
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6. Connect output port 'value' of second Text node to input port 'b' of Concat node
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7. Connect output port 'value' of Concat node to input port 'value' of Output node
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8. Execute graph by cooking the Output node's 'value' port to obtain result
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## Inputs
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- text_a (string)
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- text_b (string)
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## Outputs
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- concatenated_text (string)
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## Failure Modes
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- One or both text inputs missing or non-string
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- Invalid node connections (port mismatch)
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- Runtime error during graph execution
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## Source
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Extracted from: [https://github.com/temiroff/Blacknode.git](https://github.com/temiroff/Blacknode.git)
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Confidence: 0.95
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# Commands: text-concatenation-pipeline
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## Available Commands
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- `/skill text-concatenation-pipeline` — Load this skill
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- `/run text-concatenation-pipeline` — Execute workflow
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# Examples: text-concatenation-pipeline
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## Usage Example
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```python
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# How to use this skill
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# Inputs: text_a (string), text_b (string)
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# Process: Instantiate a Text node with parameter value set to text_a → Instantiate a Text node with parameter value set to text_b → Instantiate a Concat node with no parameters
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# Outputs: concatenated_text (string)
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```
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@@ -0,0 +1,31 @@
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{
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"name": "text-concatenation-pipeline",
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"version": "1.0.0",
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"goal": "Combine two text inputs into a single output string using a Blacknode node graph.",
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"inputs": [
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"text_a (string)",
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"text_b (string)"
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],
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"steps": [
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"Instantiate a Text node with parameter value set to text_a",
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"Instantiate a Text node with parameter value set to text_b",
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"Instantiate a Concat node with no parameters",
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"Instantiate an Output node",
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"Connect output port 'value' of first Text node to input port 'a' of Concat node",
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"Connect output port 'value' of second Text node to input port 'b' of Concat node",
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"Connect output port 'value' of Concat node to input port 'value' of Output node",
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"Execute graph by cooking the Output node's 'value' port to obtain result"
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],
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"outputs": [
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"concatenated_text (string)"
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],
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"failure_modes": [
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"One or both text inputs missing or non-string",
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"Invalid node connections (port mismatch)",
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"Runtime error during graph execution"
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],
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"confidence": 0.95,
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"explanation": "Extracted from examples/converted_text_pipeline.py and referenced templates/text-pipeline.json in the Blacknode repository. The workflow is a basic reusable pattern for string concatenation using the visual node editor's graph model.",
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"source_repo": "https://github.com/temiroff/Blacknode.git",
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"score": 1.0
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}
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+1
-1
@@ -1,4 +1,4 @@
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# Tests: conditional-request-review-workflow
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# Tests: text-concatenation-pipeline
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## Test Checklist
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Block a user