Find good first issues on GitHub

AI Summary: The user is seeking assistance with a "catch-all" configuration that now requires an "email worker." They are asking for guidance on how to proceed with this new requirement.

AI Summary: This issue proposes a "bloat audit" to reduce code complexity across the entire repository by removing duplicated boilerplate, dead configurations, and unnecessary dependencies. The goal is to improve maintainability and reduce potential bugs without altering user-visible behavior. The work is broken down into small, manageable PRs, with specific guidelines for implementation and verification.

AI Summary: The user is asking if the project is still being maintained because they haven't seen any recent updates. They are also open to any development suggestions or learning exchanges.

AI Summary: This issue is a beginner-friendly task to add a new wallpaper URL to a JSON file. It requires no coding and can be completed in under a minute by forking the repository, editing the JSON file, and submitting a pull request.

AI Summary: This issue highlights a critical gap in the project's roadmap: two production-evidence RFCs related to multi-spoke fleet coordination are unanchored, leaving external adopters without clarity on their future inclusion. This lack of roadmap visibility acts as an adoption blocker, particularly for organizations scaling beyond a single hub. The proposed next step is for maintainers to decide the track for these RFCs and record it in the roadmap, and for the adopter to be invited to the ADOPTERS.md file.

AI Summary: This security issue describes an authentication bypass vulnerability where anonymous callers can impersonate users and roles on public API endpoints. By forging `X-Hive-User` and `X-Hive-Role` headers, attackers can manipulate contribution queues, mint invites as trusted contributors, and overwrite profile data.

AI Summary: This issue aims to improve the reliability of documentation by adding automated checks for CLI commands and configuration examples. The goal is to ensure that documented commands and examples accurately reflect the shipped CLI and schema, preventing drift and providing clear failure messages when discrepancies are found. This will involve identifying checkable commands, validating them against the parser, and ensuring configuration examples conform to the current schema.

AI Summary: This issue proposes adding validation for Markdown links and anchors to the Continuous Integration (CI) pipeline. The goal is to prevent broken internal links and invalid heading references within the repository's documentation, ensuring navigation remains functional after file renames. The solution should be configurable to avoid unreliable external checks and exclude generated or vendored content.

AI Summary: This issue proposes a solution to accurately track the source code version associated with architectural claims in the documentation. The current method of embedding a commit hash is prone to staleness and self-referential problems, and the goal is to implement a verifiable provenance model that ensures the architecture map reflects the correct source revision.

AI Summary: This issue proposes to automate the verification of the guarantee-to-test map in the documentation. Currently, this map is maintained manually, leading to potential inconsistencies if tests are renamed or removed. The goal is to implement a CI check that ensures all documented guarantees point to valid and unique test files and functions, preventing outdated or broken links.

AI Summary: This issue proposes the implementation of a popup or notification system to inform users about newly added features. The goal is to improve user awareness and adoption of recent updates. This is tagged as a 'good first issue' and requires UI/UX and design input.

AI Summary: This issue is a beginner-friendly task to add a new common Japanese learner mistake to a JSON file. It requires no coding and can be completed in under a minute by forking the repository, editing the specified JSON file, and submitting a pull request.

AI Summary: This issue seeks a user with a live Snowflake account and programmatic access to test the recently implemented Snowflake support. The goal is to verify the integration works end-to-end, from data source registration and schema syncing to executing a query and observing the model's SQL and the returned data.

AI Summary: This issue is a call for help from Databricks users who have access to a running Databricks SQL warehouse. The goal is to test the Databricks support that was recently merged, which currently relies on mocked responses. Testers are asked to configure their workspace, perform specific actions, and report back on success, schema details, and query round-trip results.

AI Summary: This issue seeks community help to test Trino integration with real Trino or Starburst clusters. The goal is to verify data source registration, schema synchronization, and query execution against Iceberg, Delta, or Hive catalogs. Testers are asked to report success/failure of these steps, schema details, and a query round trip.

AI Summary: This issue is a beginner-friendly task to add a new Japanese example sentence to a JSON file. It requires no coding knowledge and can be completed directly in the browser by forking the repository, editing the specified JSON file, and submitting a pull request.

AI Summary: This issue proposes to improve the security and reproducibility of GitHub Actions by pinning all third-party Actions to immutable commit SHAs instead of mutable tags. This change will ensure that workflows always use a specific, verified version of an Action, preventing unexpected behavior due to tag updates and enhancing dependency management.

AI Summary: This issue requests the configuration of Dependabot to automate dependency updates for Python packages and GitHub Actions within the repository. The goal is to prevent dependencies from becoming stale by establishing a clear update path with a low-noise schedule and sensible pull request limits, while respecting existing CI processes.

AI Summary: This issue proposes adding a Software Bill of Materials (SBOM) to Python releases for the Mycelium project. The goal is to automatically generate and publish an SBOM in a standard format (like CycloneDX or SPDX) as a GitHub Release artifact, linking it to the specific package version and source commit. This will improve transparency and allow for easier consumption by standard SBOM tooling.

AI Summary: This issue proposes integrating dependency vulnerability scanning into the CI pipeline. The goal is to identify and fail builds if project dependencies have known security vulnerabilities, with a defined process for handling exceptions.

AI Summary: This issue proposes integrating a static Python security scanner, like Bandit, into the CI pipeline. The goal is to automatically detect common Python security vulnerabilities in the 'mycelium' package during pull requests, with clear documentation for any necessary exclusions and a local command for contributors.

AI Summary: This issue proposes adding a minimum Python code coverage requirement to the CI pipeline. The goal is to prevent regressions by ensuring a certain percentage of the code is tested, failing the build if it drops below a defined threshold. This will involve integrating `pytest-cov`, setting an initial coverage target, and documenting the process.

AI Summary: The CI pipeline for Podman on arm64 and rootless environments is failing on the v5 branch due to a change in the Podman info schema. The `.Host.RootlessNetworkCmd` field has been removed, causing a Go template in the CI configuration to fail. A fix exists for v4 and needs to be ported to v5, likely by using JSON output and `jq` for more robust field extraction.

AI Summary: This issue proposes refactoring the Rust code by moving a conditionally compiled module named `spec_traits` from `lib.rs` into a new file called `specialization.rs`. The goal is to improve code organization by modularizing the specialization traits into their own dedicated file, which will also be conditionally linked.

AI Summary: This issue proposes adding a check to the Continuous Integration (CI) pipeline to ensure that generated files have not been unintentionally modified. The change involves incorporating a `make gen` command into the CI workflow, which requires setting up Node.js. This will help maintain the integrity of generated code by detecting any deviations.

AI Summary: The `UPGRADE.md` file, which contains crucial information for operator upgrades, is not linked from the main `README.md` or the `src/docs/README.md` index. This prevents users from discovering the guide, especially before major version upgrades. The recommendation is to add links to `UPGRADE.md` in both of these locations.

AI Summary: This issue highlights a documentation discrepancy where a README file incorrectly states that certain wrapkey primitives have been implemented. These primitives were actually removed as dead code in a previous PR, making the documentation outdated and misleading. The recommendation is to update the README to reflect the current state of the code and link to the relevant PRs for historical context.

AI Summary: The production Dockerfile is using an outdated Node.js version (22) and Corepack, which is deprecated and will be removed in future Node.js versions. This issue proposes updating the Dockerfile to the current LTS (Node 24), replacing Corepack with a direct pnpm installation, and centralizing the Node.js version definition in `package.json` to ensure consistency between development, CI, and production environments.

AI Summary: On Windows, using Ctrl+V within Lithe's built-in terminal or command prompt results in the literal characters "^V" being typed instead of pasting the clipboard content. This bug is consistently reproducible on Windows 11 and prevents normal paste functionality in the terminal.

AI Summary: This feature request aims to improve media handling in OMH by ensuring that media-related tasks are routed only to providers and models that explicitly support the required input modalities. Currently, OMH can send media to executors without verifying their input capabilities, leading to potential failures or unhandled scenarios. The proposal involves adding input-modality capabilities to executor profiles and enforcing these checks before dispatching tasks.