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Merge pull request #102 from INCATools/ai-integrations
i Adding AI integrations
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‎.claude/.mcp.json‎

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{
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"mcpServers": {
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"ols-mcp": {
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"type": "stdio",
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"command": "uvx",
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"args": [
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"ols-mcp"
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],
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"env": {}
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},
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"pubmed": {
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"type": "http",
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"url": "https://pubmed.mcp.claude.com/mcp"
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}
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}
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}

‎.claude/settings.json‎

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{
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"permissions": {
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"allow": [
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"Bash(*)",
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"Edit",
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"MultiEdit",
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"NotebookEdit",
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"FileEdit",
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"WebFetch",
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"WebSearch",
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"Write"
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]
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}
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}

‎.github/actions/claude-code-action/action.yml‎

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name: "Claude Code Action"
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description: "Run Claude Code in GitHub Actions workflows"
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inputs:
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github_token:
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description: "GitHub token with repo and issues permissions"
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required: true
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anthropic_api_key:
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description: "Anthropic API key"
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required: false
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cborg_api_key:
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description: "CBORG API key"
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required: false
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claude_code_oauth_token:
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description: "Claude Code OAuth token"
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required: false
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prompt:
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description: "The prompt to send to Claude Code"
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required: false
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default: ""
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prompt_file:
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description: "Path to a file containing the prompt to send to Claude Code"
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required: false
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default: ""
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allowed_tools:
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description: "Comma-separated list of allowed tools for Claude Code to use"
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required: false
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default: ""
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output_file:
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description: "File to save Claude Code output to (optional)"
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required: false
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default: ""
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timeout_minutes:
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description: "Timeout in minutes for Claude Code execution"
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required: false
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default: "10"
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install_github_mcp:
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description: "Whether to install the GitHub MCP server"
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required: false
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default: "false"
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install_artl_mcp:
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description: "Whether to install the ARTL MCP server"
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required: false
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default: "false"
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runs:
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using: "composite"
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steps:
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- name: Install uvx
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shell: bash
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run: |
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curl -LsSf https://astral.sh/uv/install.sh | sh
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source $HOME/.cargo/env
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which uvx || echo "uvx not found in PATH, installing via pip"
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pip install uv || true
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- name: Install Claude Code
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shell: bash
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run: npm install -g @anthropic-ai/claude-code
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- name: Install GitHub MCP Server
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if: inputs.install_github_mcp == 'true'
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shell: bash
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run: |
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claude mcp add-json github '{
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"command": "docker",
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"args": [
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"run",
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"-i",
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"--rm",
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"-e",
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"GITHUB_PERSONAL_ACCESS_TOKEN",
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"ghcr.io/github/github-mcp-server:sha-ff3036d"
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],
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"env": {
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"GITHUB_PERSONAL_ACCESS_TOKEN": "${{ inputs.GITHUB_TOKEN }}"
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}
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}'
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- name: Install ARTL MCP Server
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if: inputs.install_artl_mcp == 'true'
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shell: bash
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run: |
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claude mcp add-json artl '{
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"command": "uvx",
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"args": [
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"artl-mcp"
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]
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}'
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- name: Prepare Prompt File
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shell: bash
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id: prepare_prompt
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run: |
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# Check if either prompt or prompt_file is provided
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if [ -z "${{ inputs.prompt }}" ] && [ -z "${{ inputs.prompt_file }}" ]; then
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echo "::error::Neither 'prompt' nor 'prompt_file' was provided. At least one is required."
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exit 1
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fi
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# Determine which prompt source to use
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if [ ! -z "${{ inputs.prompt_file }}" ]; then
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# Check if the prompt file exists
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if [ ! -f "${{ inputs.prompt_file }}" ]; then
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echo "::error::Prompt file '${{ inputs.prompt_file }}' does not exist."
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exit 1
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fi
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# Use the provided prompt file
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PROMPT_PATH="${{ inputs.prompt_file }}"
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else
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mkdir -p /tmp/claude-action
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PROMPT_PATH="/tmp/claude-action/prompt.txt"
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echo "${{ inputs.prompt }}" > "$PROMPT_PATH"
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fi
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# Verify the prompt file is not empty
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if [ ! -s "$PROMPT_PATH" ]; then
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echo "::error::Prompt is empty. Please provide a non-empty prompt."
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exit 1
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fi
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# Save the prompt path for the next step
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echo "PROMPT_PATH=$PROMPT_PATH" >> $GITHUB_ENV
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- name: Run Claude Code
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shell: bash
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id: run_claude
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run: |
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if [ ! -z "${{ inputs.claude_code_oauth_token }}" ]; then
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echo CLAUDE AUTH TOKEN IS NOT SET
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else
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echo CLAUDE AUTH TOKEN IS SET
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export ANTHROPIC_API_KEY=
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fi
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ALLOWED_TOOLS_ARG=""
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if [ ! -z "${{ inputs.allowed_tools }}" ]; then
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ALLOWED_TOOLS_ARG="--allowedTools ${{ inputs.allowed_tools }}"
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fi
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# Set a timeout to ensure the command doesn't run indefinitely
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timeout_seconds=$((${{ inputs.timeout_minutes }} * 60))
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if [ -z "${{ inputs.output_file }}" ]; then
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# Run Claude Code and output to console
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claude \
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-p \
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--verbose \
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--output-format stream-json \
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"$(cat ${{ env.PROMPT_PATH }})" \
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${{ inputs.allowed_tools != '' && format('--allowedTools "{0}"', inputs.allowed_tools) || '' }}
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else
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# Run Claude Code and tee output to console and file
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claude \
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-p \
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--verbose \
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--output-format stream-json \
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"$(cat ${{ env.PROMPT_PATH }})" \
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${{ inputs.allowed_tools != '' && format('--allowedTools "{0}"', inputs.allowed_tools) || '' }} | tee output.txt
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# Process output.txt into JSON in a separate step
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jq -s '.' output.txt > output.json
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# Extract the result from the last item in the array (system message)
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jq -r '.[-1].result' output.json > "${{ inputs.output_file }}"
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echo "Complete output saved to output.json, final response saved to ${{ inputs.output_file }}"
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fi
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env:
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ANTHROPIC_API_KEY: ${{ inputs.anthropic_api_key }}
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# ANTHROPIC_AUTH_TOKEN: ${{ inputs.cborg_api_key }}
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CLAUDE_CODE_OAUTH_TOKEN: ${{ inputs.claude_code_oauth_token }}
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GITHUB_TOKEN: ${{ inputs.github_token }}
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# ANTHROPIC_BASE_URL: "https://api.cborg.lbl.gov"
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# DISABLE_NON_ESSENTIAL_MODEL_CALLS: "1"

‎.github/actions/claude-issue-summarize-action/action.yml‎

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name: "Claude Issue summarize Action"
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description: "Automatically Summarize GitHub issues using Claude Code"
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inputs:
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timeout_minutes:
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description: "Timeout in minutes for execution"
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required: false
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default: "5"
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anthropic_api_key:
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description: "Anthropic API key"
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required: false
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cborg_api_key:
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description: "CBORG API key"
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required: false
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claude_code_oauth_token:
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description: "Claude Code OAuth token"
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required: false
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github_token:
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description: "GitHub token with repo and issues permissions"
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required: true
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runs:
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using: "composite"
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steps:
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- name: Checkout repository code
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uses: actions/checkout@v4
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with:
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ref: ${{ github.ref }}
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- name: Create prompt file
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shell: bash
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run: |
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mkdir -p /tmp/claude-prompts
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cat > /tmp/claude-prompts/claude-issue-summarize-prompt.txt << 'EOF'
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You're an Summarization assistant for GitHub issues. Your task is to analyze the issue, look up related issues, and summarize the issue.
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Remember that this repo is primarily a note-taking and memory device for Chris Mungall, so anything you can do to enhance and enrich that would be helpful.
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IMPORTANT: Don't make any PRs. You should ONLY post a response, IN THE SAME ISSUE.
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Issue Information:
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- REPO: ${{ github.repository }}
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- ISSUE_NUMBER: ${{ github.event.issue.number }}
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TASK OVERVIEW:
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1. First, use your judgement to determine the course of action.
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- If the issue is an epic or has links to other issues, read those issues, and summarize them. Summarize their status etc. Given an overall summary.
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- If the issue is an idea or a vague high level description, run with the idea, do deep research, give heloful suggestions with links to relevant papers etc.
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- If there are links in the issue to websites, database entities, etc, then look these up.
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- If there are links or references to papers, then looks these up and summarize (don't guess content - if you can't access the paper, then say "I can't access the paper")
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- Try using artl-mcp to get paper fulltext.
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- If you want a more powerful AI agent to take on this one and make a PR, use this magic phrase: `@dragon-ai-agent please <INSTRUCTIONS>`
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2. Next, use the GitHub tools to get context about the issue:
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- You have access to these github tools:
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- mcp__github__get_issue: Use this to retrieve the current issue's details including title, description, and existing labels
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- mcp__github__get_issue_comments: Use this to read any discussion or additional context provided in the comments
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- mcp__github__update_issue: Use this to apply labels to the issue (do not use this for commenting)
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- mcp__github__search_issues: Use this to find similar issues that might provide context for proper categorization and to identify potential duplicate issues
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- mcp__github__list_issues: Use this to understand patterns in how other issues are labeled
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- You can also use web searching and fetching.
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- It's okay to not add any information if the issue is not clear.
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EOF
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- name: Run Claude Code
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uses: ./.github/actions/claude-code-action
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with:
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prompt_file: /tmp/claude-prompts/claude-issue-summarize-prompt.txt
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allowed_tools: "Bash(gh label list),WebFetch,Fetch,LS,mcp__github__get_issue,mcp__github__get_issue_comments,mcp__github__update_issue,mcp__github__add_issue_comment,mcp__github__search_issues,mcp__github__list_issues"
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install_github_mcp: "true"
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install_artl_mcp: "true"
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timeout_minutes: ${{ inputs.timeout_minutes }}
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anthropic_api_key: ${{ inputs.anthropic_api_key }}
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claude_code_oauth_token: ${{ inputs.claude_code_oauth_token }}
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cborg_api_key: ${{ inputs.cborg_api_key }}
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github_token: ${{ inputs.github_token }}

‎.github/actions/claude-issue-triage-action/action.yml‎

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name: "Claude Issue Triage Action"
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description: "Automatically triage GitHub issues using Claude Code"
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inputs:
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timeout_minutes:
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description: "Timeout in minutes for execution"
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required: false
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default: "5"
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anthropic_api_key:
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description: "Anthropic API key"
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required: false
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claude_code_oauth_token:
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description: "Claude Code OAuth token"
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required: false
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cborg_api_key:
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description: "CBORG API key"
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required: true
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github_token:
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description: "GitHub token with repo and issues permissions"
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required: true
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runs:
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using: "composite"
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steps:
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- name: Checkout repository code
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uses: actions/checkout@v4
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with:
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ref: ${{ github.ref }}
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- name: Create prompt file
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shell: bash
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run: |
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mkdir -p /tmp/claude-prompts
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cat > /tmp/claude-prompts/claude-issue-triage-prompt.txt << 'EOF'
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You're an issue triage assistant for GitHub issues. Your task is to analyze the issue and select appropriate labels from the provided list.
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IMPORTANT: Don't post any comments or messages to the issue. Your only action should be to apply labels.
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Issue Information:
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- REPO: ${{ github.repository }}
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- ISSUE_NUMBER: ${{ github.event.issue.number }}
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TASK OVERVIEW:
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1. First, fetch the list of labels available in this repository by running: `gh label list`. Run exactly this command with nothing else.
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2. Next, use the GitHub tools to get context about the issue:
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- You have access to these tools:
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- mcp__github__get_issue: Use this to retrieve the current issue's details including title, description, and existing labels
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- mcp__github__get_issue_comments: Use this to read any discussion or additional context provided in the comments
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- mcp__github__update_issue: Use this to apply labels to the issue (do not use this for commenting)
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- mcp__github__search_issues: Use this to find similar issues that might provide context for proper categorization and to identify potential duplicate issues
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- mcp__github__list_issues: Use this to understand patterns in how other issues are labeled
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- Start by using mcp__github__get_issue to get the issue details
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3. Analyze the issue content, considering:
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- The issue title and description
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- The type of issue (bug report, feature request, question, etc.)
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- Technical areas mentioned
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- Severity or priority indicators
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- User impact
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- Components affected
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4. Select appropriate labels from the available labels list provided above:
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- Choose labels that accurately reflect the issue's nature
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- Be specific but comprehensive
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- Select priority labels if you can determine urgency (high-priority, med-priority, or low-priority)
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- Consider platform labels (android, ios) if applicable
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- If you find similar issues using mcp__github__search_issues, consider using a "duplicate" label if appropriate. Only do so if the issue is a duplicate of another OPEN issue.
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5. Apply the selected labels:
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- Use mcp__github__update_issue to apply your selected labels
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- DO NOT post any comments explaining your decision
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- DO NOT communicate directly with users
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- If no labels are clearly applicable, do not apply any labels
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IMPORTANT GUIDELINES:
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- Be thorough in your analysis
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- Only select labels from the provided list above
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- DO NOT post any comments to the issue
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- Your ONLY action should be to apply labels using mcp__github__update_issue
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- It's okay to not add any labels if none are clearly applicable
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EOF
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- name: Run Claude Code
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uses: ./.github/actions/claude-code-action
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with:
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prompt_file: /tmp/claude-prompts/claude-issue-triage-prompt.txt
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allowed_tools: "Bash(gh label list),mcp__github__get_issue,mcp__github__get_issue_comments,mcp__github__update_issue,mcp__github__search_issues,mcp__github__list_issues"
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install_github_mcp: "true"
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timeout_minutes: ${{ inputs.timeout_minutes }}
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anthropic_api_key: ${{ inputs.anthropic_api_key }}
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claude_code_oauth_token: ${{ inputs.claude_code_oauth_token }}
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cborg_api_key: ${{ inputs.cborg_api_key }}
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github_token: ${{ inputs.github_token }}

‎.github/ai-controllers.json‎

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["cmungall"]

‎.github/copilot-instructions.md‎

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../AGENTS.md

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