Unique-AG

Diagnose and fix CI failures without leaving your editor.

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Delete local git branches whose remotes are gone, after verifying via gh CLI that each was actually merged.

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Guide branch creation, commit messages, and titles so the repo’s semantic workflow is enforced

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Handle pull requests and review comments using GitHub CLI (gh). Use when the user wants to check PR comments, address review feedback, reply with commit hashes, or work with pull requests.

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Manage Python dependencies, lock files, and project environments using Poetry.

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Check if a pull request is too large and guide splitting it into focused PRs.

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Apply Google-style docstrings and inline comments to Python .py files. Use when documenting new functions/classes/modules, incrementally documenting touched code, or flagging rename opportunities as TODOs.

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Triage and fix Dependabot alerts and CodeQL findings in the ai repository. Use when the user asks to address security vulnerabilities, fix Dependabot alerts, resolve CodeQL issues, or do security maintenance.

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Search the Unique AI Platform knowledge base using the unique-cli search command, with automatic per-turn citation tracking so cited facts render as clickable reference chips and `<sup>N</sup>` footnotes on the Unique platform. Use whenever the user asks to find, search, or query documents or content on Unique, including filtering by folder or metadata. Also covers `unique-cli read <cont_id>` for reading the full indexed text of a document when its content ID is already known. NOTE: This search uses combined vector + full-text indexing. Excel (.xlsx/.xls), CSV (.csv), and image files are NOT full-text indexed, so they will not appear in search results. To locate these file types, use the unique-cli-file-management skill instead (browse folders with `unique-cli ls` to find them by name).

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Invoke connected Unique spaces/subagents through the unique-cli subagent command. Use when the workspace exposes connected-space tools and you need to delegate a question or task to one of those configured assistants.

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Reproduce ai-repo PR checks locally with Poe and CI scripts, including per-package typecheck and coverage behavior. Use when validating changes before push or when user asks which local commands match CI.

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Add documentation pages to an existing MkDocs + Entangled site, explain how to serve locally, help adapt documentation

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Backport fixes from main onto release/YYYY.WW in the ai repo with cherry-pick and rebase merge so release-please changelogs stay correct. Use when hotfixing a release branch, cherry-picking to release/*, or preparing a release backport PR.

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Deploy a new LLM model via LiteLLM (GitOps) and/or Azure (Terraform + node backend), add it to the ai toolkit, create the required pull requests, and verify end-to-end. Use when rolling out a model to any environment, adding a model to the toolkit, troubleshooting "model not available" errors, or finding pricing/token limits/model ids for any provider.

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Proactively draft and create pull requests by inferring title, refs, and body from git context, then confirm and open via gh CLI.

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After pushing code or creating a PR, automatically wait for CI checks to complete, fix failures, address Bugbot findings, and re-push in a loop until the PR is green. Use when the user pushes to a PR, creates a PR, or asks to get a PR to green.

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Guide authors through a structured self-review before requesting peer review.

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Debug Python code using tracebacks, pdb, and structured logging.

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Write focused, deterministic, well-documented pytest tests for AI-authored code.

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Refactor Python code to improve quality while keeping functionality intact. Use when cleaning up complexity, removing duplication, or tightening structure.

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AI repo versioning and changelogs via release-please — never edit CHANGELOG.md or pyproject version by hand. Use when the user asks about releases, version bumps, changelogs, or preparing a release.

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Navigate execution flow from an entry point, mapping call chains, external dependencies, and side effects.

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Tabular and numerical data analysis with descriptive statistics and insights. Use when the user provides data, tables, CSVs, or numbers and wants analysis.

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Financial factsheet analysis with key metrics extraction and investment rationale

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