TICKET MANAGEMENT

GitHub Duplicate Issue Triage Agent

When a new GitHub issue is opened, an agent searches the repository for similar existing issues, and if it finds a strong match it comments with the link.

CategoryTicket Management
Enginepaperclip
Difficultyadvanced
Triggerevent
Steps6
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerNew GitHub issue openedGitHubGitHub
  • ActionSearch repo for similar open issuesGitHubGitHub
  • ActionJudge best match and confidence with OpenAIOpenAI
  • LogicBranch: confident duplicate vs ambiguous
  • ActionComment, label duplicate, and close in GitHubGitHubGitHub
  • OutputPost reasoning note on the issueGitHubGitHub

What it does

Open-source and internal repos collect many issues reporting the same bug. This agent reviews each new issue, hunts the existing backlog for the same problem, and when it is confident, closes the newcomer as a duplicate pointing at the canonical issue, while flagging uncertain cases for a maintainer.

When to use it

Use it on busy repositories where maintainers spend real time spotting and closing duplicate issues by hand and want consistent, linked triage on every new report.

How it works

  1. 1A newly opened GitHub issue triggers the flow.
  2. 2The agent searches the repo for open issues with overlapping titles and bodies.
  3. 3OpenAI judges the candidates and returns the best match with a confidence score and rationale.
  4. 4A logic branch splits high-confidence duplicates from ambiguous ones.
  5. 5For confident matches, GitHub comments with the canonical link, labels the issue `duplicate`, and closes it; ambiguous ones get a `needs-triage` label instead.
  6. 6The agent posts a short reasoning note on the issue so the decision is auditable.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect GitHubRepos, issues, pull requests, actions.
  2. 2
    Connect OpenAIModels, embeddings, files.
  3. 3
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  4. 4
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  5. 5
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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