Add Publisher v2 + 5 extracted skills
Publisher fixes: - Checkout new branch before push (was pushing main ref) - Verify files staged before commit - Handle duplicate files gracefully - Clean error reporting per stage Skills merged to main: - mcp-server-setup (from pipeshub-ai) - research-pipeline (from Blacknode) - multi-agent-sequential-workflow (from Fast-LLM-Agent-MCP) - unifai-workflow-execution (from UnifAI) - code-review-agent-workflow (from AgentKit)
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{
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"name": "research-pipeline",
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"version": "1.0.0",
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"goal": "Fetch a Wikipedia page, summarise its content using an AI agent, and write the summary to a file.",
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"inputs": [
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"URL of the Wikipedia page"
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],
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"steps": [
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"Step 1: Import necessary modules from `_bootstrap` and `blacknode`: Run `from _bootstrap import NIM_MODEL, require_nim_api_key; import blacknode as bn`",
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"Step 2: Require NVIDIA NIM API key: Call `require_nim_api_key()` to ensure the API key is set.",
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"Step 3: Create a graph instance: Initialize `g = bn.Graph()`.",
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"Step 4: Add nodes for URL, HTTPGet, summarisation, and file writing: `url = g.node('Literal', value='URL of the Wikipedia page'); fetcher = g.node('HTTPGet'); summarise = g.node('LLMAgent', system='You are a technical writer. Summarise the text in 3 bullet points.', model=NIM_MODEL); writer = g.node('FileWrite', path='summary.txt')`",
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"Step 5: Connect nodes with edges: `url.out('value') >> fetcher.inp('url'); fetcher.out('text') >> summarise.inp('prompt'); summarise.out('text') >> writer.inp('text')`",
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"Step 6: Cook the graph to execute and get output: `result = g.cook(writer, 'path'); print(f'Summary written to: {result}')`"
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],
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"outputs": [
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"Path of the summary file"
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],
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"failure_modes": [
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"If the URL is invalid or unreachable, the HTTPGet node will fail; if the summarisation fails, the output text might be empty"
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],
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"confidence": 0.95,
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"explanation": "This workflow can be adapted to fetch and summarise any Wikipedia page or similar content source.",
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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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