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Metis: automatic GitHub issue triage powered by TypeSafe AI Jev. A reusable GitHub Action.
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CommunityJev Tools & CLIs
Metis
GitHub issue triage that classifies a new issue as bug, feature, documentation, question or other, applies the matching label when thresholds pass, and asks for only the details it judged missing.
- Stars
- 2
- Language
- Python
- License
- MIT
- Published by
- Community
- Author
- Ayush0054
- Last verified
- Oct 2026
About this project
metis-workflow is a small Python framework for workflows powered by TypeSafe AI's Jev model. Define a workflow class, use integrations where needed, and compose named steps. Python 3.10+, no runtime dependencies. The framework imports as metisworkflow. Both issue triage and PR screening are examples built entirely with this framework. They do not import the legacy package. The current framework version is 0.1.0. After publication, the distribution can be installed with pip install metis-workflow.
Quoted from the project's README. Read the full README.
Works forJev for Classification
Used inJev for Software & DevTools
- Languages
- Python
Highlights
- Jev returns typed decisions, not prose; the follow-up comment is a fixed template listing just the details judged missing.
- Default thresholds are 0.8 Choice confidence, 0.85 category probability and 0.9 per missing detail, called policy rather than accuracy.
- Skips uncertain classifications, bot-authored and closed issues, oversized reports, and any write if the title or body changed mid-run.
- The library entry point makes no GitHub requests and never posts; only the Action and the github subcommand write.
Watch out
The README states plainly that the package has not been built, installed or tested yet and that no release has been triggered, so the PyPI name metis-triage is not there yet and installing means pip install . from a checkout. The documented workflow pins main, which the README itself calls an initial development version and tells you to replace with a commit SHA. Out of the box the Action expects the bug, enhancement, documentation and question labels to already exist on the repository, since it applies an existing label rather than creating one. It needs issues: write, which organization policy can block, and issue titles and bodies are sent to TypeSafe for classification. An HTTP error during a write can leave a label applied without the accompanying reply, so rerunning the failed job is part of normal operation, and edits to an issue body do not retrigger triage. There is no accuracy evaluation behind the defaults. Copy reviewed against the repository README on 2026-10-04, not from running it.
Questions about this entry
Short answers drawn from the linked project or page.
The write path is guarded at several points. A label is applied only when both confidence thresholds pass, uncertain classifications are skipped, unrelated labels are left intact, and conflicting category labels make it defer rather than overwrite. It skips bot-authored issues, closed issues and oversized reports, and if the title or body changed while classification was running the write is abandoned. The comment is a fixed template listing only the details judged missing, since Jev returns typed decisions and never generates the reply text.
Not as an accuracy claim, and the README does not pretend otherwise: it calls them initial policy settings and explicitly not evaluated accuracy guarantees, with the instruction to tune them on your own issues when you are ready to test. They are configurable, since you copy the default configuration into your repository to change label names, disable missing-detail comments or adjust thresholds.
Yes, and that is the safer starting point. classify_issue takes a title, body and repository and returns the category, suggested label, needs_review flag and missing details without making a single GitHub request, so the caller decides whether a label exists and whether to apply it. Only the GitHub Action and the metis-triage github subcommand actually write.
Four things worth checking before you enable it. The labels must already exist on the repository, because Metis applies an existing label and never creates one. The workflow needs issues: write, which some organization policies refuse, plus a checkout step and contents: read if you supply a custom config, and that config file must be complete rather than partial. The key goes in GitHub Secrets as TYPESAFE_API_KEY, since the workflow does not load local .env or .envrc files.
From the checkout run python -m pip install .; after publication it is pip install metis-workflow. It needs Python 3.10 or newer and has no runtime dependencies, and the current framework version is 0.1.0.
Define a Workflow subclass with build_steps(), export it as workflow, and run it with metis-workflow run --workflow-file ... --event ... A manifest such as .github/metis-workflows.json registers several workflows by name.
Copy the examples, companion JSON, and manifest into your repository, add the workflow on the default branch, and set TYPESAFE_API_KEY as a repository secret. Only trusted base code should run in pull_request_target, and PR head code must never be checked out.
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