cycle-counting

cycle-counting is a skill for Claude Code from kishorkukreja/awesome-supply-chain. It costs 81 tokens per session (7,569 once invoked), scanned A, original, MIT.

A framework for counting selected inventory regularly instead of waiting for one large annual count. It uses stock value, risk, and known problem areas to help decide what to count and how often.

In plain words
What is it for?
Use it to design counting schedules, improve warehouse inventory accuracy, investigate differences between records and stock, and connect counting work with barcode scanning or a warehouse system.
Why use it?
It helps find record errors earlier while limiting disruption and labor compared with a full physical inventory.

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 counting schedules, improve warehouse inventory accuracy, investigate differences between records and stock, and connect counting work with barcode scanning or a warehouse system.

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

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

Your own site · 80×15
<a href="https://agentmods.dev/skills/kishorkukreja/awesome-supply-chain/cycle-counting"><img src="https://agentmods.dev/badge/skills/kishorkukreja/awesome-supply-chain/cycle-counting.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 81 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 7,569 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 $0.00081 $0.07569
Opus 5 $0.00041 $0.03785
Sonnet 5 $0.00016 $0.01514
Haiku 4.5 $0.00008 $0.00757

Measured 12d ago against content hash 57d1e9b484f0, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

cycle-counting 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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

skills/cycle-counting/SKILL.md · 1,060 lines

How it starts

The opening of the file, as written. The whole thing — 1,060 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Cycle Counting

You are an expert in cycle counting and inventory accuracy management. Your goal is to help design and optimize cycle counting programs that maintain high inventory accuracy while minimizing operational disruption and labor costs.

Initial Assessment

Before implementing cycle counting, understand:

  1. Current State

    • Current inventory accuracy level?
    • Existing cycle counting program? (frequency, method)
    • Last physical inventory? (annual, semi-annual)
    • Known accuracy pain points?
  2. Operational Context

    • SKU count and warehouse size?
    • Warehouse management system (WMS) in place?
    • RF scanning and barcode infrastructure?
    • Labor availability for counting?
  3. Business Impact

    • Cost of inaccuracy? (stockouts, excess, expediting)
    • Order fill rate and customer service impact?
    • Financial audit requirements?
    • Regulatory compliance (FDA, SOX, etc.)?
  4. Inventory Characteristics

    • ABC classification of inventory?
    • High-value items requiring tight control?
    • Items with known accuracy issues?
    • Storage types (pallets, shelving, bulk)?

Cycle Counting Framework

Why Cycle Count?

Benefits vs. Annual Physical Inventory:

Aspect Annual Physical Inventory Cycle Counting
Accuracy Once per year Continuous improvement
Disruption Shutdown operations (1-3 days) No shutdown needed
Cost High (labor spike, lost production) Lower (spread over year)
Root Cause Difficult (old variances) Timely (find issues quickly)
Compliance Meets minimum requirement Exceeds (continuous verification)

Target Accuracy:

  • Class A items: 99%+ accuracy
  • Class B items: 97%+ accuracy
  • Class C items: 95%+ accuracy
  • Overall: 98%+ accuracy

Cycle Counting Methods

1. ABC Cycle Counting

Most Common Method:

  • Count high-value items (A) more frequently
  • Count medium-value items (B) moderately
  • Count low-value items (C) less frequently

Read the full file on GitHub · 1,060 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. 12d ago First seen · 1,060 lines · 81 tokens per session scan A 57d1e9b484f0

Subscribe to this mod's changes

cycle-counting is a skill published in the GitHub repository kishorkukreja/awesome-supply-chain (67 stars, last pushed 12d ago), licensed MIT. It adds 81 tokens to every session and 7,569 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 2026-08-30.

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