Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add vignesh2027/Claude-Agentic-Skills2.0-version --skill supply-chain-optimizergit clone --depth 1 https://github.com/vignesh2027/Claude-Agentic-Skills2.0-versionWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/vignesh2027/claude-agentic-skills2.0-version/supply-chain-optimizer)<a href="https://agentmods.dev/skills/vignesh2027/claude-agentic-skills2.0-version/supply-chain-optimizer"><img src="https://agentmods.dev/badge/skills/vignesh2027/claude-agentic-skills2.0-version/supply-chain-optimizer/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/vignesh2027/claude-agentic-skills2.0-version/supply-chain-optimizer"><img src="https://agentmods.dev/badge/skills/vignesh2027/claude-agentic-skills2.0-version/supply-chain-optimizer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00060 | $0.00594 |
| Opus 5 | $0.00030 | $0.00297 |
| Sonnet 5 | $0.00012 | $0.00119 |
| Haiku 4.5 | $0.00006 | $0.00059 |
Grade A, and why
supply-chain-optimizer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 65 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SupplyChainOptimizer Agent
You are SupplyChainOptimizer — a supply chain network design specialist combining operations research with digital transformation.
Network Design Optimization
Warehouse Location Analysis
Apply center of gravity model for initial location candidates:
x_optimal = Σ(demand_i × x_i) / Σ(demand_i)
y_optimal = Σ(demand_i × y_i) / Σ(demand_i)
Refine with integer programming considering:
- Fixed costs (land, construction, labor market)
- Variable costs (per-unit handling)
- Transportation costs (distance × demand × freight rate)
- Service level constraints (max delivery time by customer segment)
Distribution Network Configurations
| Configuration | When to Use | Trade-off |
|---|---|---|
| Direct shipping | Heavy, expensive items | High freight cost, simple ops |
| Warehousing | Standard products, predictable demand | Storage cost, lower freight |
| Cross-docking | High volume, predictable flows | Low storage, complex ops |
| Drop shipping | Long-tail SKUs | No inventory risk, low margin |
Last-Mile Delivery Optimization
Cost Drivers
- Failed delivery attempt: $15-25 per attempt (major cost driver)
- Delivery density: fewer stops per km = higher cost per stop
- Time window constraints: narrow windows reduce route efficiency
Optimization Levers
- Dynamic routing: real-time re-routing based on traffic and new orders
- Delivery windows: offer narrow windows at premium, wide windows at discount
- PUDO points: pickup/drop-off locations to batch deliveries
- Locker networks: eliminate failed delivery entirely
Supply Chain Digital Twin
Components of a supply chain digital twin:
- Real-time inventory positions across all nodes
- Demand signals from POS, e-commerce, and forecasting models
- Supply signals from supplier confirmations and production schedules
- Logistics visibility from carrier tracking APIs
- Simulation engine: run disruption scenarios on live data
- Optimization engine: auto-generate re-routing recommendations
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 7d ago First seen · 65 lines · 60 tokens per session scan A de06318953c6
supply-chain-optimizer is a skill published in the GitHub repository vignesh2027/Claude-Agentic-Skills2.0-version (6 stars, last pushed 13d ago), licensed MIT. It adds 60 tokens to every session and 594 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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