By jezweb
Cross-cutting skills for working well with an AI agent: planning and stress-testing ideas, prompt-writing (text and image), don't-trust-memory verification (facts, tooling, and visuals), reasoning over images, stranger-testing docs before they ship, delegation and multi-agent orchestration, role agents and self-refining loops, and the occasional step-back reflection. The thinking, not just the filing. See skills/README.md for the current set.
Use when about to delegate a discrete task to a sub-agent, deciding whether to spawn one at all, how much to specify it, and how to keep its work from bloating the main thread. The one-off-task layer below run-a-role-agent. Triggers, "delegate this", "spawn a sub-agent", "should this be a sub-agent or a script", "fan this out".
Use after any non-trivial build, before commit or deploy. Convene two or more frontier models from different families and providers to review the change for Critical/High/Medium/Low findings; fix cross-validated Criticals before commit and Highs before deploy. Also when the same bug won't fix on the first attempt, or for a whole-codebase pass before a release.
Use before committing to a plan or brief, to stress-test it, surface the unstated assumptions, the unknowns, the scope that will change, and the user/business needs the brief doesn't mention. The adversarial counterpart to imagine, and the planning-time counterpart to brains-trust. Triggers, "challenge this", "roast my plan", "poke holes", "what am I missing", "pressure-test", "devil's advocate", "what are my assumptions".
Use when planning, to think past the immediate request and find the bigger product hiding inside it, what the users and the business will need that nobody's asked for yet. Produces a north-star vision, not a task list. The expansive counterpart to challenge. Triggers, "imagine", "think big", "what could this become", "where could this go", "what are we missing".
Use when deciding how to arrange agents for a piece of work: one agent or several, which pattern (single loop, pipeline, routing, parallel, orchestrator-workers, evaluator loop, triage funnel), how to match roles to model temperaments, how to bound a model-driven control loop so it's safe to trust instead of hand-coding a deterministic spine, and the mechanics that keep multi-agent work safe and cheap. The layer above agent-delegation (one-off hand-offs) and run-a-role-agent (one ongoing role).
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A copy-and-go workspace for working alongside an AI agent. Your knowledge lives as plain markdown the agent reads and keeps up to date, so you never solve the same thing twice. You don't need to be a developer, and it works for any job, not just code.
No app, no database, no cloud. It's just folders. Clone it, open your agent in the folder, and go.
Keep what you learn as one file per thing: a client, a decision, a project, a gotcha, an idea. Over time it compounds: instead of re-researching, you and the agent read what's already there and add to it. Three moves, the whole loop:
You don't set anything up by hand; your agent does it. Tell it (Claude Code, or whatever you use):
Clone https://github.com/jezweb/dotjez into a new folder for me, then help me set up the workspace.
That's the whole install. The agent gets the folder, reads the briefs inside, then interviews you, or borrows a profile from an AI you already use (ChatGPT, Claude, Gemini), and writes your about.md.
Prefer to fetch it yourself? git clone https://github.com/jezweb/dotjez ~/workspace, then open your agent in the folder and say "help me set up this workspace."
Name the folder whatever you like; nothing inside cares. Once it holds real client data, keep it private: don't push your filled-in workspace to a public remote (the agent re-points the git remote during setup).
You → "help me set up this workspace"
Agent → interviews you (or borrows a profile from an AI you already use),
writes about.md.
You → "new client signed — Acme Digital, web + email, contact Jane"
Agent → copies the clients/ example to clients/acme-digital.md, fills it in.
...you work...
Agent → at the end, logs a line to journal/: what you did, what's next.
Next time, the agent reads about.md and the last journal entry first, so it already knows who you are and where you left off. Every session starts ahead of the last.
Your brief is CLAUDE.md (how to operate this workspace, loads automatically in Claude Code) and .jez/CLAUDE.md (the detail on how it's organised; it only auto-loads when you work inside .jez/, so read it yourself). Follow them; don't reinvent the conventions. In short: read .jez/about.md to learn who you serve (run .jez/playbooks/onboard.md if it's still blank), then run Ask → Add → Tidy and keep the briefs current.
dotjez/ ← clone this; it becomes your workspace
├── CLAUDE.md the agent's brief (how to operate this workspace)
├── .jez/ your knowledge hub, shared across every project
│ ├── CLAUDE.md how it's organised (the detail)
│ ├── about.md who you are + how you like to work (filled in first)
│ ├── clients/ contacts/ decisions/ projects/
│ ├── knowledge/ playbooks/ research/ ideas/
│ ├── journal/ the agent's running log, per session
│ ├── inbox/ somewhere to drop notes to file later
│ └── secrets/ where credentials go (and don't)
├── skills/ reusable agent skills (use in place, or install)
└── sample-project/ what a project's own .jez looks like
Most folders ship a worked example; copy it to make a real one. A .jez works at any level: the workspace has one (knowledge across all your work), and each project gets its own (scratch for that project). The question that decides where something goes: will another project ever care about this? The agent makes new folders as your work grows; it doesn't need them up front.
Two notes for browsing it yourself: .jez is a hidden folder, so your agent always sees it but Finder won't until you press Cmd+Shift+. (or just ask the agent to open a file). And the name honours the workspace's first user; call your folder anything, but keep the .jez/ directory name itself: it's what the briefs and sibling tools key on.
The capabilities travel two ways. The workspace briefs load when your agent is opened in (or under) this folder; during setup the agent offers to add a pointer in your agent's global config so sessions started elsewhere still find the workspace. The skills install once and travel everywhere: in Claude Code, /plugin marketplace add jezweb/dotjez, then install dotjez from the /plugin menu.
npx claudepluginhub jezweb/dotjez --plugin dotjezLocal business SEO setup with JSON-LD schema, meta tags, robots.txt, and sitemap.
Scaffold Cloudflare Workers, Hono APIs, D1/Drizzle schemas, D1 migration workflows, full-stack Vite+Workers apps, and TanStack Start SSR dashboards.
Social media content creation — platform-formatted posts for LinkedIn, Facebook, Instagram, and Reddit with character limits, hashtag strategies, and image specs.
Manage Shopify stores: product creation, bulk imports, content pages, blog posts, and SEO metadata.
Generate colour palettes, favicon packages, custom SVG icon sets, and image processing (resize, convert, optimise).
Comprehensive skill pack with 66 specialized skills for full-stack developers: 12 language experts (Python, TypeScript, Go, Rust, C++, Swift, Kotlin, C#, PHP, Java, SQL, JavaScript), 10 backend frameworks, 6 frontend/mobile, plus infrastructure, DevOps, security, and testing. Features progressive disclosure architecture for 50% faster loading.
Tools to maintain and improve CLAUDE.md files - audit quality, capture session learnings, and keep project memory current.
Develop, test, build, and deploy Godot 4.x games with Claude Code. Includes GdUnit4 testing, web/desktop exports, CI/CD pipelines, and deployment to Vercel/GitHub Pages/itch.io.
Upstash Context7 MCP server for up-to-date documentation lookup. Pull version-specific documentation and code examples directly from source repositories into your LLM context.
A growing collection of Claude-compatible academic workflow bundles. Covers scientific figures, manuscript writing and polishing, reviewer assessment, citation retrieval, data availability, paper reading, literature search, response letters, paper-to-PPTX conversion, and evidence-grounded Chinese invention patent drafting. Rules are organized as reusable skill folders with explicit workflows and quality checks.
Create new skills, improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, update or optimize an existing skill, run evals to test a skill, or benchmark skill performance with variance analysis.