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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-workflow
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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-workflow
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version: 1.0.0
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description: Concatenate two text strings and produce the combined output.
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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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- Create a Text node with value set to input text_a.
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- Create a second Text node with value set to input text_b.
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- Create a Concat node with inputs a and b.
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- Create an Output node.
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- Connect Text node a 'value' port to Concat node 'a' port.
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- Connect Text node b 'value' port to Concat node 'b' port.
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- Connect Concat node 'value' port to Output node 'value' port.
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- Execute/cook the graph from the Output node to obtain the 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-workflow
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Concatenate two text strings and produce the combined output.
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## Steps
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1. Create a Text node with value set to input text_a.
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2. Create a second Text node with value set to input text_b.
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3. Create a Concat node with inputs a and b.
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4. Create an Output node.
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5. Connect Text node a 'value' port to Concat node 'a' port.
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6. Connect Text node b 'value' port to Concat node 'b' port.
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7. Connect Concat node 'value' port to Output node 'value' port.
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8. Execute/cook the graph from the Output node to obtain the 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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- Missing or invalid text inputs.
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- Graph execution error if nodes are not properly connected.
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- Concat node may not handle non-string types.
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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-workflow
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## Available Commands
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- `/skill text-concatenation-workflow` — Load this skill
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- `/run text-concatenation-workflow` — Execute workflow
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# Examples: text-concatenation-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: text_a (string), text_b (string)
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# Process: Create a Text node with value set to input text_a. → Create a second Text node with value set to input text_b. → Create a Concat node with inputs a and b.
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# Outputs: concatenated_text (string)
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```
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{
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"name": "text-concatenation-workflow",
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"version": "1.0.0",
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"goal": "Concatenate two text strings and produce the combined output.",
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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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"Create a Text node with value set to input text_a.",
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"Create a second Text node with value set to input text_b.",
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"Create a Concat node with inputs a and b.",
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"Create an Output node.",
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"Connect Text node a 'value' port to Concat node 'a' port.",
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"Connect Text node b 'value' port to Concat node 'b' port.",
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"Connect Concat node 'value' port to Output node 'value' port.",
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"Execute/cook the graph from the Output node to obtain the 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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"Missing or invalid text inputs.",
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"Graph execution error if nodes are not properly connected.",
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"Concat node may not handle non-string types."
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],
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"confidence": 0.95,
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"explanation": "Extracted from examples/converted_text_pipeline.py which demonstrates a simple Blacknode graph workflow: two Text nodes feed a Concat node that outputs via an Output node. This pattern is reusable for any text combination task.",
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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