inventory-demand-planning

inventory-demand-planning is a skill for Claude Code, Codex from JunMystery/Agent-Guidance-Python. It costs 86 tokens per session (955 once invoked), scanned A, original, MIT.

Codified expertise for demand forecasting, safety stock optimization, replenishment planning, and promotional lift estimation at multi-location retailers. Informed by demand planners with 15+ years experience managing hundreds of SKUs. Includes forecasting method selection, ABC/XYZ analysis, seasonal transition…

Skill for Claude CodeCodex

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.

agentmods
npx agentmods add skills/junmystery/agent-guidance-python/inventory-demand-planning
Any agent
npx skills add JunMystery/Agent-Guidance-Python --skill inventory-demand-planning
Clone the repo
git clone --depth 1 https://github.com/JunMystery/Agent-Guidance-Python

Made for: Claude Code, Codex.

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 inventory-demand-planning

README.md
[![agentmods](https://agentmods.dev/badge/skills/junmystery/agent-guidance-python/inventory-demand-planning.svg)](https://agentmods.dev/skills/junmystery/agent-guidance-python/inventory-demand-planning)
Your own site
<a href="https://agentmods.dev/skills/junmystery/agent-guidance-python/inventory-demand-planning"><img src="https://agentmods.dev/badge/skills/junmystery/agent-guidance-python/inventory-demand-planning.svg" alt="Measured on agentmods" height="20"></a>
Per session 86 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 955 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin unknown 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 $0.00086 $0.00955
Opus 5 $0.00043 $0.00477
Sonnet 5 $0.00017 $0.00191
Haiku 4.5 $0.00009 $0.00096

Measured today against content hash cf021417924d, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

inventory-demand-planning 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 today.

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/inventory-demand-planning/SKILL.md · 66 lines

How it starts

The opening of the file, as written. The whole thing — 66 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Inventory Demand Planning

Role and Context

You are a senior demand planner at a multi-location retailer operating 40–200 stores with regional distribution centers. You manage 300–800 active SKUs across categories including grocery, general merchandise, seasonal, and promotional assortments. Your systems include a demand planning suite (Blue Yonder, Oracle Demantra, or Kinaxis), an ERP (SAP, Oracle), a WMS for DC-level inventory, POS data feeds at the store level, and vendor portals for purchase order management. You sit between merchandising (which decides what to sell and at what price), supply chain (which manages warehouse capacity and transportation), and finance (which sets inventory investment budgets and GMROI targets). Your job is to translate commercial intent into executable purchase orders while minimizing both stockouts and excess inventory.

When to Use

  • Generating or reviewing demand forecasts for existing or new SKUs
  • Setting safety stock levels based on demand variability and service level targets
  • Planning replenishment for seasonal transitions, promotions, or new product launches
  • Evaluating forecast accuracy and adjusting models or overrides
  • Making buy decisions under supplier MOQ constraints or lead time changes

How It Works

  1. Collect demand signals (POS sell-through, orders, shipments) and cleanse outliers
  2. Select forecasting method per SKU based on ABC/XYZ classification and demand pattern
  3. Apply promotional lifts, cannibalization offsets, and external causal factors
  4. Calculate safety stock using demand variability, lead time variability, and target fill rate
  5. Generate suggested purchase orders, apply MOQ/EOQ rounding, and route for planner review
  6. Monitor forecast accuracy (MAPE, bias) and adjust models in the next planning cycle

Examples

  • Seasonal promotion planning: Merchandising plans a 3-week BOGO promotion on a top-20 SKU. Estimate promotional lift using historical promo elasticity, calculate the forward buy quantity, coordinate with the vendor on advance PO and logistics capacity, and plan the post-promo demand dip.
  • New SKU launch: No demand history available. Use analog SKU mapping (similar category, price point, brand) to generate an initial forecast, set conservative safety stock at 2 weeks of projected sales, and define the review cadence for the first 8 weeks.
  • DC replenishment under lead time change: Key vendor extends lead time from 14 to 21 days due to port congestion. Recalculate safety stock across all affected SKUs, identify which are at risk of stockout before the new POs arrive, and recommend bridge orders or substitute sourcing.

Read the full file on GitHub · 66 lines

Files

What ships with it

5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. today First seen · 66 lines · 86 tokens per session scan A cf021417924d

Subscribe to this mod's changes

inventory-demand-planning is a skill published in the GitHub repository JunMystery/Agent-Guidance-Python (2 stars, last pushed 1mo ago), licensed MIT. It adds 86 tokens to every session and 955 once invoked, about $0.0004 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

debug-optimize-lcp

Guides debugging and optimizing Largest Contentful Paint (LCP) using Chrome DevTools MCP tools. Use this skill whenever the user asks about LCP performance, slow page loads, Core Web Vitals optimization, or wants to understand why their page's main content takes too long to appear. Also use when the user mentions…

ChromeDevTools/chrome-devtools-mcp · 99 tokens

arkana-analyse

British English alias for the arkana-analyze skill. Binary analysis skill for Arkana. Triggers on: analyse, analyze, binary, malware, reverse engineer.

JameZUK/Arkana · 38 tokens

apitap

ApiTap gives AI agents cheap access to web data through three layers.

n1byn1kt/apitap · 0 tokens

compliance-frameworks

ISO 27001, NIST CSF 2.0, CIS Controls v8.1, EU CRA compliance mapping, multi-standard alignment per Hack23 ISMS policies.

Hack23/European-Parliament-MCP-Server · 40 tokens

frontmcp-setup

Use when starting, scaffolding, or organizing a FrontMCP project. Covers creating a new project (CLI scaffold or manual) for Node, Vercel, and other targets; standalone versus Nx-monorepo layout, naming conventions, generators, and dependency rules; composing multiple @App classes, ESM packages, and remote MCP servers…

agentfront/frontmcp · 176 tokens

add-adapter

Playbook for adding a new source-agent adapter to pond - spec the format from the upstream writer, capture a sandboxed fixture, implement the bidirectional codec, and prove conformance. Use when adding an adapter under packages/pond/src/adapter/ or reworking an existing one.

tenequm/pond · 61 tokens