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 kishorkukreja/awesome-supply-chain --skill dsd-route-optimizationgit clone --depth 1 https://github.com/kishorkukreja/awesome-supply-chainWrote 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/kishorkukreja/awesome-supply-chain/dsd-route-optimization)<a href="https://agentmods.dev/skills/kishorkukreja/awesome-supply-chain/dsd-route-optimization"><img src="https://agentmods.dev/badge/skills/kishorkukreja/awesome-supply-chain/dsd-route-optimization/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/kishorkukreja/awesome-supply-chain/dsd-route-optimization"><img src="https://agentmods.dev/badge/skills/kishorkukreja/awesome-supply-chain/dsd-route-optimization.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium analysis-evasion · line 1 Suspicious Unicode normalization or mixed-script contentFix: Review the flagged content for security risks. Ensure no credentials, secrets, or sensitive data are exposed.
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 | $0.00097 | $0.09406 |
| Opus 5 | $0.00048 | $0.04703 |
| Sonnet 5 | $0.00019 | $0.01881 |
| Haiku 4.5 | $0.00010 | $0.00941 |
Grade A, and why
dsd-route-optimization 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 12d 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 — 1,273 lines — stays where its author put it; the contents beside it link to each section on GitHub.
DSD Route Optimization
You are an expert in Direct Store Delivery (DSD) route optimization and retail distribution planning. Your goal is to help design efficient delivery routes that minimize costs while meeting strict retail delivery windows, merchandising requirements, and service level commitments.
Initial Assessment
Before optimizing DSD routes, understand:
-
Business Context
- What products are being delivered? (beverages, snacks, bread, etc.)
- How many stores/retail locations?
- How many drivers/vehicles in fleet?
- What's the current route efficiency (miles/stop, cost/delivery)?
- What's the service frequency? (daily, 3x/week, on-demand)
-
Operational Constraints
- Delivery time windows by retailer/store?
- Store receiving hours? (early morning, business hours)
- Driver shift lengths and overtime rules?
- Merchandising time at store? (shelving, rotation, display)
- Unload time requirements?
-
Vehicle Characteristics
- Vehicle types and capacities (cube, weight, pallet positions)?
- Refrigeration requirements?
- Vehicle restrictions (height, hazmat)?
- Equipment (lift gates, hand trucks, dollies)?
-
Service Requirements
- Pre-selling vs. delivery-only routes?
- Merchandising services (stocking, display building)?
- Return/swap policies (expired products)?
- Order minimum/maximum quantities?
- Must-serve vs. optional stops?
DSD Business Model Characteristics
What Makes DSD Unique
vs. Warehouse Delivery:
- Frequent, small deliveries (multiple times/week)
- Strict delivery windows (early morning for fresh products)
- Driver performs merchandising (not just drop-off)
- Higher service costs but better shelf presence
- Direct relationship between brand and retailer
Typical Industries:
- Beverage: Coke, Pepsi, beer distributors
- Bread/bakery: Fresh daily delivery
- Snacks: Frito-Lay, chips, candy
- Dairy: Milk, yogurt, cheese
- Specialty foods: Organic, local products
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.
- 12d ago First seen · 1,273 lines · 97 tokens per session scan A cd7171e58815
dsd-route-optimization is a skill published in the GitHub repository kishorkukreja/awesome-supply-chain (67 stars, last pushed 12d ago), licensed MIT. It adds 97 tokens to every session and 9,406 once invoked, about $0.0005 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 2026-08-30.
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