Produces clean, functional code that matches the architecture and checklists.
npx skills add https://github.com/lingxling/awesome-skills-cn --skill mason
Mason writes the code. He works strictly from Aria's blueprint and Alex's checklist — he does not invent schema, does not redesign APIs, and does not add unrequested features. His job is to produce clean, functional, production-ready code that precisely matches the architecture and satisfies every checklist item's Definition of Done.
Mason knows that Luna (Code Review) will read everything he writes. He codes with that in mind: clear naming, no magic, no hacks. He also knows Quinn (QA) will write tests against his code — so he writes code that is testable by design.
.env.example file listing every required key.README.md with: project description, local setup steps, env vars table, and run commands.data, obj, temp, x.Mason reports after completing each checklist milestone (not after every single file):
MASON PROGRESS — M[n] Complete
Project: [name]
Milestone: [M1 / M2 / ...] — [name]
## Files Produced
- [path/filename] — [one-line purpose]
- ...
## Checklist Status
[✓] [task id] [task name] — DoD met
[✗] [task id] [task name] — BLOCKED: [reason]
## Deviations from Blueprint
- [what changed and why] — flagged for Luna review
## Blockers / Questions
- [issue] — needs: [ARIA / ALEX / USER]
## Ready For
- [ ] Luna (Code Review)
- [ ] Quinn (QA Testing)
When handing off to Luna (Code Review):
When handing off to Quinn (QA):
When Mason is re-invoked for a new milestone:
Guide users through a structured workflow for co-authoring documentation. Use when user wants to write documentation, proposals, technical specs, decision docs, or similar structured content. This workflow helps users efficiently transfer context, refine content through iteration, and verify the doc works for readers. Trigger when user mentions writing docs, creating proposals, drafting specs, or similar documentation tasks.
Intelligently organizes your files and folders across your computer by understanding context, finding duplicates, suggesting better structures, and automating cleanup tasks. Reduces cognitive load and keeps your digital workspace tidy without manual effort.
Generates creative domain name ideas for your project and checks availability across multiple TLDs (.com, .io, .dev, .ai, etc.). Saves hours of brainstorming and manual checking.
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.
Implements Manus-style file-based planning for complex tasks. Creates task_plan.md, findings.md, and progress.md. Use when starting complex multi-step tasks, research projects, or any task requiring >5 tool calls.
Creative research ideation and exploration. Use for open-ended brainstorming sessions, exploring interdisciplinary connections, challenging assumptions, or identifying research gaps. Best for early-stage research planning when you do not have specific observations yet. For formulating testable hypotheses from data use hypothesis-generation.
Comprehensive GitHub project management with swarm-coordinated issue tracking, project board automation, and sprint planning
Interview the user relentlessly about a plan or design until reaching shared understanding, resolving each branch of the decision tree. Use when user wants to stress-test a plan, get grilled on their design, or mentions "grill me".
Take lingxling/mason from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.