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---
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name: conditional-request-review
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version: 1.0.0
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description: Capture a user request, classify it via branching, and produce an approval
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or rejection result.
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inputs:
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- request
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steps:
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- 'Start: input agent prompts user for request and stores it in state field ''request'''
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- 'Classify: branching agent evaluates ''request'' and routes to Approve on success
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or Reject on failure, storing ''decision'''
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- 'Approve: default agent formats approval message using ''request'' and stores it
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in ''result'''
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- 'Reject: default agent formats rejection message using ''request'' and stores it
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in ''result'''
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outputs:
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- result (string message indicating approval or rejection)
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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
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Capture a user request, classify it via branching, and produce an approval or rejection result.
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## Steps
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1. Start: input agent prompts user for request and stores it in state field 'request'
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2. Classify: branching agent evaluates 'request' and routes to Approve on success or Reject on failure, storing 'decision'
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3. Approve: default agent formats approval message using 'request' and stores it in 'result'
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4. Reject: default agent formats rejection message using 'request' and stores it in 'result'
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## Inputs
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- request
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## Outputs
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- result (string message indicating approval or rejection)
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## Failure Modes
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- If branching classification fails, workflow routes to Reject (on_failure)
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- If input not provided, workflow may hang or error depending on runtime
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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-review
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## Available Commands
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- `/skill conditional-request-review` — Load this skill
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- `/run conditional-request-review` — Execute workflow
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# Examples: conditional-request-review
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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: input agent prompts user for request and stores it in state field 'request' → Classify: branching agent evaluates 'request' and routes to Approve on success or Reject on failure, storing 'decision' → Approve: default agent formats approval message using 'request' and stores it in 'result'
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# Outputs: result (string message indicating approval or rejection)
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```
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{
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"name": "conditional-request-review",
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"version": "1.0.0",
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"goal": "Capture a user request, classify it via branching, and produce an approval or rejection result.",
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"inputs": [
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"request"
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],
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"steps": [
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"Start: input agent prompts user for request and stores it in state field 'request'",
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"Classify: branching agent evaluates 'request' and routes to Approve on success or Reject on failure, storing 'decision'",
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"Approve: default agent formats approval message using 'request' and stores it in 'result'",
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"Reject: default agent formats rejection message using 'request' and stores it in 'result'"
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],
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"outputs": [
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"result (string message indicating approval or rejection)"
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],
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"failure_modes": [
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"If branching classification fails, workflow routes to Reject (on_failure)",
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"If input not provided, workflow may hang or error depending on runtime"
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],
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"confidence": 0.85,
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"explanation": "Workflow extracted from AgentMap README example 'ReviewFlow' CSV. It is a generic conditional routing pattern usable for any binary decision process.",
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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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@@ -0,0 +1,10 @@
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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
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# Tests: conditional-request-review
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# Tests: text-concatenation-pipeline
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## Test Checklist
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## Test Checklist
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Reference in New Issue
Block a user