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Restaurant Digital AI Expert helps food-service operators and consultants assess digital transformation across restaurant formats and business chains. It combines a five-dimension maturity model with vendor selection, AI-scenario prioritization, ROI analysis, and food-safety frameworks, covering supply, kitchen operations, POS, delivery, members, and franchising. It is a methodology workbench, and its license limits use to personal learning, research, and non-commercial work.

Retail Digital AI Expert is a Chinese-language workbench for retail transformation across convenience stores, supermarkets, apparel, discount retail, DTC, e-commerce, franchises, and large chains. It combines maturity assessment, vendor selection, five-year TCO and ROI analysis, and AI-use-case prioritization, helping teams move from current-state diagnosis to a roadmap and proof-of-concept plan. Its license limits use to personal learning, research, and non-commercial work.

Explain Architecture scans the important parts of a codebase, such as manifests, entry points, migrations, and routes, then produces readable Mermaid diagrams for modules, data flow, ERD, request lifecycle, and deployment. It also writes a plain-English ARCHITECTURE.md, an AI-CONTEXT.md brief, and editable diagram sources, with PNG and PDF renderings for people to review.

Restaurant Digital AI Expert is an English workbench for global food-service transformation. It maps restaurant formats and business chains from supply and central kitchens through front-of-house, POS, delivery, members, finance, and franchising, then applies maturity assessment, vendor scoring, HACCP controls, AI-use-case prioritization, and ROI analysis. It is intended for operators and advisors planning technology choices and rollout, and its license limits use to personal learning, research, and non-commercial work.

Retail Digital AI Expert is an English international workbench for retail transformation across convenience, grocery, apparel, DTC, e-commerce, franchise, and global chains. It combines format diagnosis with maturity assessment, vendor selection, five-year TCO and ROI analysis, AI-use-case prioritization, and implementation roadmaps. The repository’s license limits use to personal learning, research, and non-commercial work unless the author gives written permission.

GB/T 9704 Format standardizes applicable government-document layout rules in Word files through a Claude skill or standalone command-line tool. It fixes margins, headings, fonts, spacing, page numbers, punctuation, numbering, and table formatting while leaving the document text untouched. Uncertain content issues are reported rather than guessed, and the Python-based tool does not require Word or WPS.

Salary Negotiation turns an offer letter and a few context answers into a single-file HTML playbook. It diagnoses leverage across base, equity, sign-on, and bonus, maps both sides’ power, drafts phone and email scripts, simulates recruiter pushback for two rounds, and sets SIGN, WALK, and FREEZE stop-lines. Compensation numbers must trace to market or user-provided sources; the final choice remains yours.

iphone-malware-assessment pulls crash logs, creates a resumable encrypted backup, and scans the backup and crash reports with MVT, libimobiledevice, and downloaded indicator feeds. Its report separates actual indicator matches from heuristic notes and includes coverage plus a full file sweep. It runs locally on macOS but cannot prove an unknown zero-day is absent; you need Homebrew, a USB connection, and a backup password you can retain.

Biomedical Research Analyst gives Claude a disciplined workflow for verifying a public dataset against the research question, choosing suitable statistics, and keeping data-derived findings separate from cited literature. Before delivery, it requires specific claims, pathway-gene assignments, thresholds, and inferential language to be checked against the underlying results. Included Python components support GEO parsing, differential expression, figures, and PPTX assembly, but the outputs remain hypothesis-generating unless the study design supports stronger conclusions.

storm-research adapts Stanford’s STORM method into a Claude Code skill that creates an outline and a citation-checked HTML briefing. It discovers a panel of perspectives or uses a fixed market panel, interviews them, records contradictions and open questions, and verifies source claims before rendering the report. The method is aimed at decisions and due diligence; simple lookups do not justify its multi-agent cost.

Travel Planner collects missing trip details in one round, then previews the itinerary, budget, risks, and every item it plans to write. After confirmation, it creates a linked Apple Notes itinerary and checklist, Calendar events for fixed times, Reminders for pre-departure tasks, and Apple Maps links. Writing to Apple apps requires macOS and the relevant AppleScript automation permissions.

Use the skill in audit, scan, guide, or harden mode to review a backend project. It detects the stack, maps the attack surface, traces untrusted input to dangerous sinks, checks dependencies and configuration, and reports verified findings with file locations, severity, and fix guidance. Its coverage is anchored to OWASP and ASVS, but it is not runtime testing, a professional penetration test, or a compliance program, and it does not edit code without approval.

Claude to Codex adds a /handoff command that packages the current Claude transcript, writes hot working context, captures a git snapshot, and starts an interactive Codex terminal. Durable details stay on disk while the prompt carries only hot state and pointers, so Codex can verify the repository before acting. Setup requires authenticated Claude Code and Codex CLI plus Node.js 22 or newer.

Give the skill leads, findings, files, or any other list that needs human judgment, and it builds one self-contained HTML page with a card for every item. Reviewers can mark keep, review, or drop, add notes, follow source links, and copy the final selection back to the agent. The page opens offline, needs no server or build step, and preserves progress in localStorage.

zuiti-jiafang handles client messages about discounts, extra requests, delayed payment, or restoring an earlier version without moving the deadline. It explains the implied cost transfer, then offers polite, pointed, and firm replies organized around scope, timing, definitions, and value. Its firmest advice stays within documentation, contract, and lawful remedies; it does not encourage threats, public shaming, or retaliation.

Ask about a container tradelane, port, liner service, carrier network, or freight-rate movement, and the skill searches public alliance documents, carrier releases, port statistics, indices, and trade reporting with citations. It bundles a research method rather than a dataset and excludes air, inland, bulk, and tanker transport. Exact rotations, transit times, cut-offs, and rates still need confirmation from the carrier or forwarder before a commercial decision.

Learn From Failure organizes sourced corporate case studies by failure mechanism, such as fraud, governance, cash burn, denial, or scaling too fast. Describe a decision and it can point to three to six relevant cases with the warning questions those companies raise, or you can browse the Markdown site and checklist without AI. It is a reflection tool, not a prediction engine, and its public cases should be checked against their sources.

ai-security-guard combines zero-dependency TypeScript runtime guards with a Claude skill for prompt injection, replayed-history attacks, privilege escalation, forged action markers, cross-tenant PII leaks, media abuse, and unsafe rendering. It can log blocked attacks and propose new patterns, but each candidate must pass a regression check before a human promotes it, so nothing becomes live automatically. The reference code uses Express-style functions that can be ported to other stacks.