replenishment-strategy

replenishment-strategy is a skill for Claude Code from kishorkukreja/awesome-supply-chain. It costs 103 tokens per session (7,869 once invoked), scanned A, original, MIT.

A guide to deciding when and how much inventory to move between locations. It covers approaches such as min-max levels, demand-driven planning, distribution requirements planning, and vendor-managed inventory.

In plain words
What is it for?
Use it to design replenishment policies, set order quantities and frequencies, and improve inventory flow between suppliers, distribution centers, stores, and customers.
Why use it?
It helps balance the risk of running out of stock against the cost of holding too much inventory. It also accounts for demand variation, lead times, order limits, transport, and storage capacity.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: positional $N argument.

Part of the supply-chain-skills plugin — 133 skills shipped together , and of supply-chain-skills

Good fit Use it to design replenishment policies, set order quantities and frequencies, and improve inventory flow between suppliers, distribution centers, stores, and customers.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/kishorkukreja/awesome-supply-chain/replenishment-strategy
Install

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.

Any agent
npx skills add kishorkukreja/awesome-supply-chain --skill replenishment-strategy
Clone the repo
git clone --depth 1 https://github.com/kishorkukreja/awesome-supply-chain

Made for: Claude Code.

Or install supply-chain-skills, the plugin that ships this one along with the rest of its 133 skills.

Wrote 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.

agentmods badge for replenishment-strategy

README.md
[![agentmods](https://agentmods.dev/badge/skills/kishorkukreja/awesome-supply-chain/replenishment-strategy/github.svg)](https://agentmods.dev/skills/kishorkukreja/awesome-supply-chain/replenishment-strategy)
Your own site
<a href="https://agentmods.dev/skills/kishorkukreja/awesome-supply-chain/replenishment-strategy"><img src="https://agentmods.dev/badge/skills/kishorkukreja/awesome-supply-chain/replenishment-strategy/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.

agentmods 80×15 button for replenishment-strategy

Your own site · 80×15
<a href="https://agentmods.dev/skills/kishorkukreja/awesome-supply-chain/replenishment-strategy"><img src="https://agentmods.dev/badge/skills/kishorkukreja/awesome-supply-chain/replenishment-strategy.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 103 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 7,869 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00103 $0.07869
Opus 5 $0.00051 $0.03934
Sonnet 5 $0.00021 $0.01574
Haiku 4.5 $0.00010 $0.00787

Measured 9d ago against content hash 1935fe1ec9c2, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

replenishment-strategy 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 9d 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.

skills/replenishment-strategy/SKILL.md · 1,074 lines

How it starts

The opening of the file, as written. The whole thing — 1,074 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Replenishment Strategy

You are an expert in inventory replenishment strategies and demand-driven supply chain planning. Your goal is to help design efficient, responsive replenishment systems that maintain optimal inventory levels while minimizing stockouts and excess inventory.

Initial Assessment

Before designing replenishment strategies, understand:

  1. Network Structure

    • Supply chain tiers? (supplier → DC → store/customer)
    • Number of locations at each tier?
    • Inventory holding locations?
    • Replenishment relationships (which locations feed which)?
  2. Demand Characteristics

    • Demand variability at each tier?
    • Lead times between tiers?
    • Order patterns (steady, lumpy, seasonal)?
    • Forecast accuracy at each level?
  3. Operational Constraints

    • Minimum order quantities (MOQs)?
    • Order frequency limits? (daily, weekly, monthly)
    • Transportation constraints (full truckload preferred)?
    • Storage capacity limits?
  4. Current State

    • Current replenishment method?
    • Stockout frequency and excess inventory issues?
    • Replenishment lead times?
    • Service level performance?

Replenishment Strategy Framework

Core Replenishment Methods

1. Continuous Review (s, Q)

  • Monitor inventory continuously
  • Order fixed quantity Q when inventory hits reorder point s
  • Best for: High-value items, automated systems

2. Periodic Review (R, S)

  • Review inventory every R periods
  • Order up to level S
  • Best for: Multiple items from same supplier, coordinated replenishment

3. Min-Max (s, S)

  • When inventory ≤ min (s), order up to max (S)
  • Hybrid of continuous and periodic
  • Best for: Retail, simple systems

4. Demand-Driven Replenishment (DDR)

  • Based on actual consumption/sales
  • Pull-based, responsive to demand
  • Best for: Variable demand, short lead times

5. Vendor-Managed Inventory (VMI)

  • Supplier manages inventory levels
  • Supplier responsible for replenishment
  • Best for: Strong supplier relationships, consignment

Read the full file on GitHub · 1,074 lines

Changes

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.

  1. 9d ago First seen · 1,074 lines · 103 tokens per session scan A 1935fe1ec9c2

Subscribe to this mod's changes

replenishment-strategy is a skill published in the GitHub repository kishorkukreja/awesome-supply-chain (67 stars, last pushed 12d ago), licensed MIT. It adds 103 tokens to every session and 7,869 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 2026-09-03.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

local-ai-agents

Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…

microsoft/ai-agents-for-beginners · 200 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens

chat-pet-sprite-creation

Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.

microsoft/vscode · 53 tokens

cpu-profile-analysis

Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…

microsoft/vscode · 71 tokens

insight-error-page

Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…

vercel/next.js · 83 tokens