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BC restaurant-digital-ai-expert-international

Restaurant Digital & AI Transformation Expert —— A full-stack digital and AI transformation super-workbench for the global food service industry. Achieve world-class restaurant digital & AI expertise from zero. Core Positioning: End-to-end digital transformation skills covering all food service formats (street food stalls to regional chains to national chains to global 10,000+ store brands), all business chains (supply chain & procurement to central kitchen to back-of-house to front-of-house to delivery & takeout to membership & CRM to finance & HR to brand & marketing to franchise control to food safety), and all technology stacks (POS/KDS/ERP/CRM/CDP/SCM/HRM/BI/AI Platform/IoT/Cloud). Format Coverage: Street food stalls, breakfast shops, QSR, Fast Casual, Casual Dining, Fine Dining, hot pot restaurants, BBQ restaurants, tea & coffee shops, bakery & dessert shops, institutional catering/canteens, hotel F&B, cloud kitchens/ghost kitchens, food courts, franchise brands, global 10,000+ store brands — every format has a tailored digital solution. Methodology-Driven: Built-in Restaurant Digital Maturity Five-Dimension Model (R-DMM: Technology/Operations/Data/Organization/Customer), Restaurant AI Scenario Priority RICE Scorecard, Restaurant Tech Selection Seven-Dimension Decision Matrix, Restaurant Digital ROI/TCO Calculator, Restaurant Omnichannel Maturity Model, Restaurant Food Safety HACCP Digital Framework, Restaurant Supply Chain Four-Stream Integration Model, Restaurant Franchise Digital Control Five-Layer Model, Restaurant Private Domain AIPL Model, Full-Chain 56-Scenario Digital-Intelligent Benchmarking Framework. Deliverable Template Factory: Digital Maturity Assessment Report, Digital Transformation 3-Year Roadmap, Technology Selection & Vendor Evaluation Report, AI Scenario Priority Scorecard & Implementation Roadmap, ROI/TCO Business Case Report, Implementation Plan & Milestone Plan, Change Management & Training Plan, Food Safety Digital Solution, Supply Chai

ClawHub Agent Skills author: yinjianheng v1.2.0-intl MIT-0 64 files body ≈ 9 312 tokens Open the sourceclawhub.ai↗ analyzed 20 h ago

Restaurant Digital & AI Transformation Expert —— A full-stack digital and AI transformation super-workbench for the global food service industry.

As a process C 55/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, execution cost

GeneratorWhatsAppMarketingData and analyticsSales and CRMtype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
B
80/100
safety, quality, tests
Safety 60%
100
Quality 40%
49
Run on models
none yet
Process rating
C
55/100
Has gaps
Inputs and preconditions w 11
0
When it triggers w 12
20
Running it twice w 4
30
the three weakest of ten parameters · all ten

How to improve

  1. Shorten the description to 1024 characters.
  2. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 0

✓ No critical or high findings

Files scanned: 64. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • error description-long description is 2848 chars, limit 1024
  • warning body-long SKILL.md body ≈ 9312 tokens (recommended < 5000); move details to references/
  • note description-budget description takes 2848 of the ~15000-char shared budget for all skills
  • note frontmatter-key unknown frontmatter key "contact"
  • note frontmatter-key unknown frontmatter key "language"

Process rating: all ten parameters 55/100

  • 0Inputs and preconditions. Does not say what the process needs to start
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 10 mutating operations with no state check
  • 40Execution cost. Instruction body is 9312 tokens: crowds the task out of the window
  • 60Tools and files. Uses tools (bash) that frontmatter does not declare
  • 60Result and completion. Output format stated, no completion criterion
  • 70Failures and branches. 12 branches
  • 85Steps. 17 steps, 3 vague phrases
  • 100Consistency. Name and required fields are in place
  • 100Progress reporting. Reports progress

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +5Description has no quoted example phrases that should trigger the skill
  • +4Description does not say when NOT to use the skill (false activations)
  • +3Description length 2848: 120–800 characters recommended
  • +2Single-language instructions
  • +4Structure: 40 headings
  • +3Step-by-step instructions: 17 items
  • +3Output format is stated explicitly
  • +4Has examples (3 code blocks)
  • +4Reference files are cited in the instructions (1 of 6)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 49.

External checks

ClawHub: clean
This is a restaurant digital-transformation knowledge skill with some privacy-sensitive recommendations, but no hidden execution, credential use, exfiltration, or destructive behavior was found.
LLM: benign (medium) · VirusTotal: · 11 Jul 2026