copperhead

name: Issue summary

# Posts a short tl;dr comment on new issues so maintainers can triage from
# the notification list without opening every issue. Uses GitHub Models via
# actions/ai-inference; the token only needs models: read for that.
on:
  issues:
    types: [opened]

permissions:
  contents: read
  issues: write
  models: read

jobs:
  summary:
    runs-on: ubuntu-latest
    steps:
      - name: Summarize the issue
        id: inference
        uses: actions/ai-inference@v1
        with:
          system-prompt: >
            You write one-line triage notes for a maintainer of copperhead,
            a CLI tool that edits KiCad circuit board projects. Write like a
            person leaving a quick note, not like a report. Plain sentences
            only: no headings, no bullet points, no bold text, no em dashes,
            and never phrases like "the user reports" or "this issue
            describes". Just say what is going on and what part of the tool
            it touches, in two or three short sentences at most. If the
            issue is too thin to summarize, say what is missing instead.
          prompt: |
            Issue title: ${{ github.event.issue.title }}

            Issue body:
            ${{ github.event.issue.body }}

      - name: Post the summary
        env:
          GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
          ISSUE_URL: ${{ github.event.issue.html_url }}
          # Passed via env, never interpolated into the script, so model
          # output cannot inject shell.
          RESPONSE: ${{ steps.inference.outputs.response }}
        run: |
          gh issue comment "$ISSUE_URL" --body "tl;dr: $RESPONSE"