Supply chain logistics
Skill evoputa/ai-advisory-board/domains/supply-chain-logistics
Supply Chain advisory panel featuring Jeff Bezos (Amazon), Terry Gou (Foxconn), Amancio Ortega (Zara), Aliko Dangote (Dangote Group), and Kathy Warden (Northrop Grumman).From its SKILL.md
npx -y skills add evoputa/ai-advisory-board --skill supply-chain-logisticsAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
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SKILL.md
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Supply Chain & Logistics Advisory Panel
Advisors
| Name | Region | Lens |
|---|---|---|
| Jeff Bezos | North America | Customer-backward supply chain, last mile, flywheel |
| Terry Gou | Asia | Precision manufacturing at scale, global electronics |
| Amancio Ortega | Europe | Fast fashion logistics, vertical integration, speed |
| Aliko Dangote | Africa | Building supply chains where none exist, infrastructure-as-moat |
| Kathy Warden | North America | Mission-critical supply chain, cybersecurity, defense logistics |
Panel Dynamics
- Speed vs. resilience: Ortega optimizes for speed. Warden optimizes for zero failure. Bezos wants both.
- Build vs. use existing: Dangote builds infrastructure from scratch. Bezos leverages and extends. Different markets demand different approaches.
How It Works
- Read the user's question and identify the core tension
- Load persona details from
references/personas.md - Select 2-4 advisors most relevant to the specific question
- Each advisor speaks in first person - 2-4 sentences in their authentic voice
- Allow disagreement - different philosophies should surface
- Deliver a Panel Synthesis with a specific recommendation and next action
Reference Files
references/personas.md- Full profiles for all advisors on this panel
What ships with it: 1 file
5.7 KB alongside SKILL.md
references/
- personas.md5.7 KB
Gives 0 of the 12 instructions most operations skills give in 305 tokens
Counted across 483 of the 484 authors here whose files we hold, read 2026-08-07
- Collect monitoring data throughout the simulationin 14 of 483, across 6 files
- Set the random seed for reproducibilityin 14 of 483, across 6 files
- Validate simulations against analytical solutionsin 12 of 483, across 4 files
- Clarify goals, constraints, and inputsin 11 of 483, across 2 files
- Implement contract tests for integration pointsin 11 of 483, across 2 files
- Implement strangler fig infrastructure with API gatewayin 11 of 483, across 2 files
- Audit modernized components for security vulnerabilitiesin 11 of 483, across 2 files
- Avoid Python blocking calls in processesin 10 of 483, across 3 files
- Use resource context managers for automatic cleanupin 9 of 483, across 2 files
- Maintain consistent time unitsin 9 of 483, across 2 files
- Validate outcomes against success criteriain 8 of 483, across 1 file
- Analyze the legacy codebase for technical debtin 8 of 483, across 1 file
Said here and by no other author read
- identify the core tension
- load persona details
- select two to four relevant advisors
- speak in first person voice
- allow disagreement between advisors
- deliver a panel synthesis
Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.