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Jimmy-s-Claude
Jimmy-s-Claude contains 35 collected skills from eisenjimmy, with repository-level occupation coverage and site-owned skill detail pages.
Skills in this repository
House style for generated HTML documents. Use whenever the user asks to generate, write, or update an HTML document (guides, architecture docs, requests, reports, walkthroughs). Applies the warm-paper palette and panel/callout/TOC structure from the Loop architecture doc, in a compact form with ui-sans-serif as the default font.
Architecture playbook for LLM-powered data assistants over secured SQL (distilled from secure reference patterns). Use when designing, building, reviewing, or debugging any feature where an LLM authors SQL, reads firm data, or streams rich answers — tool loops, row-level security, sensitive-data masking, data-reference hydration, output guarding, audit — and for Blazor Server app design around streaming LLM UIs (service scoping, circuits, SignalR, JS interop). Also applies when porting these patterns to a new app.
Methodical feedback-loop harness — turn a goal into a Reason→Act→Observe→Check loop with a checkable done-criteria, real verification, a hard iteration cap, memory between passes, and a logged trail. Use when a task needs iteration to reach quality rather than a one-shot answer ("loop on this until…", "keep iterating until X", "run a goal loop", "set up a feedback loop", overnight/unattended goal runs, "build me X and make it actually good"). Invoke with /loop-mode <goal>. Composes with the built-in /loop, which supplies the cadence/trigger; this skill supplies the action and the stop-condition.
Connect to a SQL database (SQL Server, PostgreSQL, MySQL, etc.) for read-only introspection — listing databases, inspecting columns/keys, sampling rows. Read-only by default; DDL/DML needs explicit per-conversation approval and ships as a repo script with rollback. Use for any app/project whenever a task needs to query, introspect, or verify against the database.
Produce a full relational data-model document from an app's in-memory/demo models or an existing schema. Reads the real source (never invents), reshapes it into the house DB schema (tbl{Object}, abbreviated int PKs, f-prefixed FKs, join tables, audit columns), separates STORED vs DERIVED, and adds integrity constraints, indexes, finalize/lock immutability, and year-scoping. Optionally convenes the board (Elon + Tony Stark) for normalization & maintainability review. Outputs a self-contained HTML doc via html-doc-style into the project's _documentation/. Use when asked to "show / document / design the data model", "turn the demo data into a schema", or "what tables back this app".
Draw an entity-relationship / schema diagram as a self-contained inline SVG (no CDN, no image files, no mermaid) that drops straight into an HTML doc or stands alone. Renders each table as a colored-header box listing PK/FK/key columns, connects them with arrow-marker lines that point to the "many" side, color-codes relationships by layer, and adds a legend plus a collapsible ASCII fallback. Use when asked for a "schema diagram", "ER diagram", "data-model diagram", "draw the tables", or to add a visual to a data-model doc.
Convene your 3-person design board - "Elon Musk" (systems / architecture / data-model), "Steve Jobs" (taste & user experience), and "Tony Stark" (longevity & maintainability) - to spar with you on a new design or plan before you build. Each advisor reviews independently in parallel, then you get a synthesis of where they agree, where they clash, and the calls only you can make. Use when planning a new design or feature; invoke with /ask-the-board <what you are designing>.
Premium brand-kit image generation skill for creating high-end brand-guidelines boards, logo systems, identity decks, and visual-world presentations. Trained for minimalist, cinematic, editorial, dark-tech, luxury, cultural, security, gaming, developer-tool, and consumer-app brand systems. Optimized for intentional logo concepting, refined composition, sparse typography, strong symbolic meaning, premium mockups, art-directed imagery, and flexible grid layouts.
Tests in real browsers via Chrome DevTools MCP. Use when building or debugging anything that runs in a browser. Use when you need to inspect the DOM, capture console errors, analyze network requests, profile performance, or verify visual output with real runtime data. Requires the chrome-devtools MCP server to be configured.
Conducts multi-axis code review. Use before merging any change. Use when reviewing code written by yourself, another agent, or a human. Use when you need to assess code quality across multiple dimensions before it enters the main branch.
Anti-slop frontend skill for landing pages, portfolios, and redesigns. The agent reads the brief, infers the right design direction, and ships interfaces that do not look templated. Real design systems when applicable, audit-first on redesigns, strict pre-flight check.
Subjects every non-trivial decision to a fresh-context adversarial review before it stands. Use when correctness matters more than speed, when working in unfamiliar code, when stakes are high (production, security-sensitive logic, irreversible operations), or any time a confident output would be cheaper to verify now than to debug later.
Builds production-quality UIs. Use when building or modifying user-facing interfaces. Use when creating components, implementing layouts, managing state, or when the output needs to look and feel production-quality rather than AI-generated.
Overrides default LLM truncation behavior. Enforces complete code generation, bans placeholder patterns, and handles token-limit splits cleanly. Apply to any task requiring exhaustive, unabridged output.
Teaches the AI to design like a high-end agency. Defines the exact fonts, spacing, shadows, card structures, and animations that make a website feel expensive. Blocks all the common defaults that make AI designs look cheap or generic.
Refines raw ideas into sharp, actionable concepts through structured divergent and convergent thinking. Use when an idea is still vague, when you need to stress-test assumptions before committing to a plan, or when you want to expand options before converging on one. Triggers on "ideate", "refine this idea", or "stress-test my plan".
Elite website image-to-code skill for Codex. For visually important web tasks, it must first generate the design image(s) itself, deeply analyze them, then implement the website to match them as closely as possible. In Codex, it must prefer large, readable, section-specific images instead of tiny compressed boards, generate fresh standalone images for sections or detail views instead of cropping old ones, avoid lazy under-generation, avoid cards-inside-cards-inside-cards UI, and keep the hero clean, spacious, readable, and visible on a small laptop.
Elite mobile app image-generation skill for creating premium, app-native screen concepts and flows. Designed for iOS, Android, and cross-platform mobile products. Prioritizes clean hierarchy, comfortably readable text, strong multi-screen consistency, controlled color palettes, non-generic creative direction, textured surfaces, image-led composition, tasteful custom iconography, and clean phone mockup framing. By default, screens should be shown inside a subtle premium iPhone or similar phone mockup with a visible frame, while the main focus stays on the app content itself. This skill generates images only. It does not write code.
Elite frontend image-direction skill for generating premium, conversion-aware website design references. CRITICAL OUTPUT RULE — generate ONE separate horizontal image FOR EVERY section. A landing page with 8 sections produces 8 images. Never compress multiple sections into one image. Enforces composition variety (not always left-text / right-image), background-image freedom, varied CTAs, varied hero scales (giant / mid / mini minimalist), narrative concept spine, second-read moments, and a single consistent palette across all images. Optimized for landing pages, marketing sites, and product comps that developers or coding models can accurately recreate.
Capture a lesson from the current conversation and patch the setup so the same mistake never recurs — add a Gotchas section to the relevant skill, tighten CLAUDE.md/instructions, fix an agent prompt, or write a memory. Use proactively right after the user corrects your output or course-corrects you, and when wrapping up a substantial session. Invoke directly with /improve-system.
Delivers changes incrementally. Use when implementing any feature or change that touches more than one file. Use when you're about to write a large amount of code at once, or when a task feels too big to land in one step.
Bring an external resource — a URL, article, YouTube transcript, PDF, or pasted text — into the system as a structured, reusable knowledge note filed where it will be found again. Use when the user shares something to "ingest", "save", "remember this resource", or "add to my knowledge". Invoke directly with /ingest-resource.
Extracts what the user actually wants instead of what they think they should want. Achieves this through one-question-at-a-time interview until ~95% confidence about the underlying intent. Use when an ask is underspecified ("build me X" without "for whom" or "why now"), when the user explicitly invokes ("interview me", "grill me", "are we sure?", "stress-test my thinking"), or when you catch yourself silently filling in ambiguous requirements before any plan, spec, or code exists.
Clean editorial-style interfaces. Warm monochrome palette, typographic contrast, flat bento grids, muted pastels. No gradients, no heavy shadows.
Instruments code so production behavior is visible and diagnosable. Use when adding logging, metrics, tracing, or alerting. Use when shipping any feature that runs in production and you need evidence it works. Use when production issues are reported but you can't tell what happened from the available data.
Optimizes application performance. Use when performance requirements exist, when you suspect performance regressions, or when Core Web Vitals or load times need improvement. Use when profiling reveals bottlenecks that need fixing.
Upgrades existing websites and apps to premium quality. Audits current design, identifies generic AI patterns, and applies high-end design standards without breaking functionality. Works with any CSS framework or vanilla CSS.
Hardens code against vulnerabilities. Use when handling user input, authentication, data storage, or external integrations. Use when building any feature that accepts untrusted data, manages user sessions, or interacts with third-party services.
Prepares production launches. Use when preparing to deploy to production. Use when you need a pre-launch checklist, when setting up monitoring, when planning a staged rollout, or when you need a rollback strategy.
Grounds every implementation decision in official documentation. Use when you want authoritative, source-cited code free from outdated patterns. Use when building with any framework or library where correctness matters.
Creates specs before coding. Use when starting a new project, feature, or significant change and no specification exists yet. Use when requirements are unclear, ambiguous, or only exist as a vague idea.
Semantic Design System Skill for Google Stitch. Generates agent-friendly DESIGN.md files that enforce premium, anti-generic UI standards — strict typography, calibrated color, asymmetric layouts, perpetual micro-motion, and hardware-accelerated performance.
Drives development with tests. Use when implementing any logic, fixing any bug, or changing any behavior. Use when you need to prove that code works, when a bug report arrives, or when you're about to modify existing functionality.
Discovers and invokes agent skills. Use when starting a session or when you need to discover which skill applies to the current task. This is the meta-skill that governs how all other skills are discovered and invoked.
Daily changelog habit. Use when the user asks to log/record today's work, write a changelog, or wrap up the day — and proactively offer it after a substantial work session. Writes a per-day markdown entry in the project's _changelog folder named YYYY.MM.DD_changelog.md, appending if the file already exists.