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---
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name: conditional-request-routing
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version: 1.0.0
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description: Classify an input request and route it to either an approval or rejection
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path, producing a corresponding result
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inputs:
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- 'request: the input request or content to be reviewed and routed'
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steps:
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- 'Collect input: Use an input agent to capture the user''s request into state field
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''request'''
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- 'Branch: Use a branching agent to evaluate ''request'' and route to ''Approve''
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node on success or ''Reject'' node on failure'
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- 'Approve path: Use a default agent to format and output an approval message with
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the request'
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- 'Reject path: Use a default agent to format and output a rejection message with
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the request'
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outputs:
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- 'result: the approval or rejection message containing the original request'
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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-routing
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Classify an input request and route it to either an approval or rejection path, producing a corresponding result
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## Steps
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1. Collect input: Use an input agent to capture the user's request into state field 'request'
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2. Branch: Use a branching agent to evaluate 'request' and route to 'Approve' node on success or 'Reject' node on failure
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3. Approve path: Use a default agent to format and output an approval message with the request
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4. Reject path: Use a default agent to format and output a rejection message with the request
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## Inputs
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- request: the input request or content to be reviewed and routed
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## Outputs
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- result: the approval or rejection message containing the original request
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## Failure Modes
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- Branching agent cannot evaluate request and neither path is taken
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- Missing or empty input request
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- Prompt misconfiguration causing incorrect routing
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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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# Commands: conditional-request-routing
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## Available Commands
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- `/skill conditional-request-routing` — Load this skill
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- `/run conditional-request-routing` — Execute workflow
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# Examples: conditional-request-routing
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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: the input request or content to be reviewed and routed
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# Process: Collect input: Use an input agent to capture the user's request into state field 'request' → Branch: Use a branching agent to evaluate 'request' and route to 'Approve' node on success or 'Reject' node on failure → Approve path: Use a default agent to format and output an approval message with the request
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# Outputs: result: the approval or rejection message containing the original request
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```
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{
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"name": "conditional-request-routing",
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"version": "1.0.0",
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"goal": "Classify an input request and route it to either an approval or rejection path, producing a corresponding result",
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"inputs": [
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"request: the input request or content to be reviewed and routed"
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],
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"steps": [
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"Collect input: Use an input agent to capture the user's request into state field 'request'",
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"Branch: Use a branching agent to evaluate 'request' and route to 'Approve' node on success or 'Reject' node on failure",
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"Approve path: Use a default agent to format and output an approval message with the request",
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"Reject path: Use a default agent to format and output a rejection message with the request"
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],
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"outputs": [
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"result: the approval or rejection message containing the original request"
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],
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"failure_modes": [
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"Branching agent cannot evaluate request and neither path is taken",
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"Missing or empty input request",
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"Prompt misconfiguration causing incorrect routing"
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],
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"confidence": 0.85,
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"explanation": "Extracted from AgentMap's README example 'ReviewFlow' CSV workflow. This is a declarative LangGraph pattern using AgentMap's CSV format that implements conditional branching - a universally reusable pattern for request triage, content moderation, approval gates, or any two-path decision flow. It can be adapted by changing agent types (e.g., using LLM agents instead of default) and prompts.",
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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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+1
-1
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# Tests: text-concatenation-pipeline
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# Tests: conditional-request-routing
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## Test Checklist
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## Test Checklist
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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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{
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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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Reference in New Issue
Block a user