openzerocode

Use when you have a written implementation plan to execute

Spreadsheet toolkit. Reach for it whenever the artifact on either side of the conversation is a workbook file — .xlsx, .xlsm, .xltx, .csv, .tsv — and the user wants that artifact produced, changed, cleaned, or read. Typical triggers: 'build me a model', 'update this sheet', 'add a column', 'compute the totals as formulas', 'sanity-check this xlsx', 'export sheet 2 to CSV', 'render the workbook as PDF', 'the spreadsheet in ~/Downloads is a mess, fix it'. Applies equally to financial models, ops reports, data cleanups, and template fills. Skip it when the workbook is only source material and the real output is a Word doc, an HTML page, a Python script that runs standalone, a Google Sheets integration, or an ingestion pipeline into a database — in those cases the spreadsheet is a means, not the deliverable.

Perform a focused, evidence-based code review. Use when the user asks to review code, a diff, pull request, branch, commit, or implementation before merging.

Smart git commit message generator following Conventional Commits. Use when the user says 'commit', 'commit this', 'write a commit message', 'smart commit', or asks to create a git commit.

Use when the user asks what OpenZeroCode can do, how a feature works (memory, checkpoints, agents, subagents, tasks, compose, learn), how to configure it, where config/data lives, which config key controls a behavior, what CLI or slash commands exist, or how to enable/disable/tune something — the self-documenting reference for OpenZeroCode itself.

Use when executing implementation plans with independent tasks in the current session

Use this skill whenever a Microsoft Word (.docx) file is being produced, opened, transformed, or read. That includes: drafting reports, letters, contracts, RFPs, technical documents, or any long-form written deliverable; extracting text or structure from an existing Word file; filling a Word template with values; converting Word to PDF or plain text; splitting or merging documents; inspecting styles, headings, sections, tables, images, comments, or tracked changes. Trigger on mentions of 'Word doc', 'DOCX', 'Office document', a filename ending in .docx, or requests like 'turn this into a Word report'.

Guidance for distinctive, intentional visual design when building new UI or reshaping an existing one. Use whenever the task produces or modifies anything a user will see rendered — websites, landing pages, web apps, dashboards, React/HTML/Vue components, artifacts with visual output, style overhauls, or "make this look better" requests — even if the user never says the word "design". Covers aesthetic direction, typography, environment constraints (fonts, Tailwind, assets), and when to converge on convention instead of chasing distinctiveness.

Modern Python project setup with uv, ruff, and pyright. Use when initializing a new Python project, configuring the Python environment, setting up linting/formatting, or when a project needs uv (the fast Python package manager). Trigger on: 'set up Python', 'new Python project', 'configure uv', 'install uv', 'ruff', 'pyright', 'Python linting', 'Python formatting', or when a task requires Python and no pyproject.toml exists yet.

Use this skill whenever a PDF file is being produced, opened, transformed, filled, or read. That includes: extracting text or tables from an existing PDF; combining, carving, rotating, cropping, or watermarking pages; composing a fresh PDF (report, invoice, certificate); filling AcroForm fields or overlaying text onto a non-fillable scanned form; encrypting or unlocking a PDF; running OCR over a scanned document; rendering pages to PNG/JPEG for visual analysis. Trigger on mentions of 'PDF', a filename ending in .pdf, requests like 'turn this into a PDF report', or references to AcroForm / form fields.

You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes

Extract non-obvious learnings from sessions into structured knowledge artifacts

Use when implementation is complete, all tests pass, and you need to decide how to integrate the work

Use when you have a spec or requirements for a multi-step task, before touching code

Use when completing tasks, implementing major features, or before merging to verify work meets requirements

Use when implementing any feature or bugfix, before writing implementation code

Use when about to claim work is complete, fixed, or passing - requires running verification commands before making any success claims