Agent skill

Ecom Inventory Health

by asgard-ai-platform in asgard-ai-platform/skills

Analyze inventory health using turnover ratios, ABC classification, safety stock calculations, and stockout vs overstock diagnostics.

MITAuto-check passed

Install Ecom Inventory Health

skills CLI
$ npx skills add asgard-ai-platform/skills --skill ecom-inventory-health -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install asgard-ai-platform/skills ecom-inventory-health --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/asgard-ai-platform/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/ecom-inventory-health .claude/skills/ecom-inventory-health && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
ecom-inventory-health
GitHub stars
242
Token cost
~1.2k tokens
SKILL.md length
347 words
Files
4 (incl. references)
Skills in repo
207
Repo updated
First seen
Licence
MIT

At a glance

Analyze inventory health using turnover ratios, ABC classification, safety stock calculations, and stockout vs overstock diagnostics.

  • The user needs to optimize inventory levels
  • SKILL.md covers Overview, Framework, Output Format and Gotchas, plus 1 more section
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
  • Reduce carrying costs

What it does

Ecom Inventory Health is an agent skill from asgard-ai-platform/skills. Analyze inventory health using turnover ratios, ABC classification, safety stock calculations, and stockout vs overstock diagnostics. Use this skill when the user needs to optimize inventory levels, reduce carrying costs, prevent stockouts, or classify products by inventory priority — even if they say 'we have too much stock', 'we keep running out of bestsellers', 'how much safety stock do we need', or 'which products should we focus on'.

Its SKILL.md is about 1.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including reference files (for example `examples/sample_scenario.md`, `references/eoq-model.md` and `references/seasonal-forecasting.md`).

The repository describes itself as: 301 open-source coding agent skills across 22 domains — methodology, judgment & gotchas packaged as Claude Agent Skills for the Asgard AI Platform. The licence is MIT.

When your agent uses it

  • The user needs to optimize inventory levels
  • Reduce carrying costs
  • Prevent stockouts
  • Classify products by inventory priority — even if they say we have too much stock

Example prompts

  • “we have too much stock”
  • “we keep running out of bestsellers”
  • “how much safety stock do we need”
  • “/ecom-inventory-health”

What it can do on your machine

Read from SKILL.md and the folder at commit 4e7f4f8. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Ecom Inventory Health loads about 1.2k tokens when it runs, and up to ~5.9k if it reads all its reference files. Until then it costs about 116 tokens; SKILL.md has 347 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~116
When it runs · the whole SKILL.md, loaded when a task matches
~1.2k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~5.9k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from asgard-ai-platform/skills at commit 4e7f4f8, republished under its MIT licence (© asgard-ai-platform). 347 words, ~1,200 tokens.

Download SKILL.mdSave it as .claude/skills/ecom-inventory-health/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
ecom-inventory-health
description
Analyze inventory health using turnover ratios, ABC classification, safety stock calculations, and stockout vs overstock diagnostics. Use this skill when the user needs to optimize inventory levels, reduce carrying costs, prevent stockouts, or classify products by inventory priority — even if they say 'we have too much stock', 'we keep running out of bestsellers', 'how much safety stock do we need', or 'which products should we focus on'.
metadata.category
WP-01 電商
metadata.tags
e-commerce, inventory, supply-chain, abc-analysis

Inventory Health Analysis

Overview

Inventory health balances two risks: stockouts (lost sales, unhappy customers) and overstock (carrying costs, obsolescence). This skill provides tools to measure, classify, and optimize inventory levels.

Framework

IRON LAW: Not All SKUs Deserve Equal Attention

ABC classification shows that ~20% of SKUs drive ~80% of revenue.
Treat A-items (top 20% revenue) with tight control and frequent review.
C-items (bottom 50% revenue) get simple rules and less attention.
Equal treatment of all SKUs wastes resources on low-impact items.
Key Metrics
MetricFormulaHealthy Range
Inventory TurnoverCOGS / Avg Inventory4-12x/year (industry-dependent)
Days of Inventory (DOI)365 / Inventory Turnover30-90 days
Stockout RateStockout incidents / Total demand occasions< 2-5%
Fill RateOrders filled completely / Total orders> 95%
Carrying CostAvg Inventory × Carrying Cost % (typically 20-30%/year)Minimize
Dead Stock %Items with zero sales in 6+ months / Total SKUs< 10%
ABC Classification
ClassRevenue %SKU %Strategy
A~80%~20%Tight control, frequent review, safety stock optimized
B~15%~30%Moderate control, periodic review
C~5%~50%Simple rules, min/max levels, consider dropping
Safety Stock Calculation
Safety Stock = Z × σ_d × √(Lead Time)

Where:
- Z = service level factor (1.65 for 95%, 2.33 for 99%)
- σ_d = standard deviation of daily demand
- Lead Time = supplier lead time in days
Reorder Point
Reorder Point = (Average Daily Demand × Lead Time) + Safety Stock
Diagnosis Steps

Phase 1: Overall Health Check

  • Calculate turnover and DOI for total inventory
  • Compare to industry benchmarks
  • Identify trend: improving or deteriorating?

Phase 2: ABC Classification

  • Rank all SKUs by revenue contribution
  • Classify into A/B/C
  • Check: are A-items well-stocked? Are C-items over-stocked?

Phase 3: Problem Identification

  • Overstock: DOI > 90 days, dead stock > 10%, carrying costs rising
  • Stockout: Fill rate < 95%, lost sales reports, customer complaints
  • Imbalance: A-items understocked while C-items overstocked

Phase 4: Optimization

  • Set safety stock by ABC class
  • Implement reorder points for A-items
  • Liquidate dead stock (discount, bundle, donate)
  • Reduce lead times through supplier negotiation

Output Format

markdown
# Inventory Health Report: {Business}

## Summary
| Metric | Current | Target | Status |
|--------|---------|--------|--------|
| Turnover | {X}x | {X}x | 🟢/🟡/🔴 |
| DOI | {X} days | {X} days | 🟢/🟡/🔴 |
| Fill Rate | {X%} | >95% | 🟢/🟡/🔴 |
| Dead Stock | {X%} | <10% | 🟢/🟡/🔴 |

## ABC Distribution
| Class | SKUs | Revenue % | Avg DOI | Issue |
|-------|------|----------|---------|-------|
| A | {N} | {%} | {days} | {stockout risk?} |
| B | {N} | {%} | {days} | ... |
| C | {N} | {%} | {days} | {overstock?} |

## Top Issues
1. {issue with specific SKUs and data}

## Recommendations
1. {action with expected impact}

Gotchas

  • Seasonal products need separate treatment: Swimsuits in January will show as "dead stock" but shouldn't be liquidated. Use seasonal adjustment or analyze by season.
  • Inventory turnover varies hugely by industry: Grocery: 20-50x/year. Fashion: 4-6x. Electronics: 6-12x. Always benchmark within industry.
  • Low turnover ≠ bad if intentional: Strategic inventory (buying ahead of price increases, securing supply) may justify lower turnover.
  • ABC classifications shift: A product that was A-class last year may be C-class this year. Reclassify quarterly.
  • Carrying cost is often underestimated: Include: warehouse rent, insurance, obsolescence, capital cost (opportunity cost of money tied up), handling labor. Total is typically 20-30% of inventory value per year.

References

  • For EOQ (Economic Order Quantity) model, see references/eoq-model.md
  • For seasonal demand forecasting, see references/seasonal-forecasting.md

© asgard-ai-platform, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 3 other files (references) in ecom-inventory-health of asgard-ai-platform/skills.

  • SKILL.md
  • examples/sample_scenario.md
  • references/eoq-model.md
  • references/seasonal-forecasting.md

Open the folder on GitHubat commit 4e7f4f8

Compare with similar skills

Ecom Inventory Health next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Ecom Inventory Health compared with similar skills
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Ecom Inventory Health this skillasgard-ai-platform/skills242—~1.2kAutomated safety check: PassMIT
Skin Health Analyzersickn33/agentic-awesome-skills47k2 repos~293Automated safety check: PassMIT
Codebase Health Dashboardgarrytan/gstack136k—~11kAutomated safety check: NotesMIT
Python Type Safetywshobson/agents40k—~1.4kAutomated safety check: PassMIT
Healthagenticnotetaking/arscontexta3.5k—~7.1kAutomated safety check: NotesMIT
Health Wellnesssickn33/agentic-awesome-skills47k1 repos~3.5kAutomated safety check: PassMIT

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Questions about Ecom Inventory Health

What does Ecom Inventory Health do?

Analyze inventory health using turnover ratios, ABC classification, safety stock calculations, and stockout vs overstock diagnostics. Ecom Inventory Health is an agent skill from asgard-ai-platform/skills. Analyze inventory health using turnover ratios, ABC classification, safety stock calculations, and stockout vs overstock diagnostics.

When should I use Ecom Inventory Health?

Ecom Inventory Health fits situations like: the user needs to optimize inventory levels; reduce carrying costs; prevent stockouts; classify products by inventory priority — even if they say we have too much stock.

How do I install Ecom Inventory Health in Claude Code?

Run `npx skills add asgard-ai-platform/skills --skill ecom-inventory-health -a claude-code`. Or copy the skill folder (ecom-inventory-health in asgard-ai-platform/skills) into .claude/skills/ecom-inventory-health in your project. Claude Code loads it when a task matches its description.

How do I install Ecom Inventory Health in Codex?

Run `npx skills add asgard-ai-platform/skills --skill ecom-inventory-health -a codex`. Or copy the skill folder (ecom-inventory-health in asgard-ai-platform/skills) into .agents/skills/ecom-inventory-health in your project. Codex loads it when a task matches its description.

Can I use Ecom Inventory Health in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add asgard-ai-platform/skills --skill ecom-inventory-health -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/ecom-inventory-health, .gemini/skills/ecom-inventory-health, .github/skills/ecom-inventory-health and .opencode/skills/ecom-inventory-health in your project.

What does Ecom Inventory Health need to run?

SKILL.md names no scripts, command-line tools or credentials: Ecom Inventory Health is instructions for the agent only.

Does Ecom Inventory Health access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Ecom Inventory Health safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Ecom Inventory Health use?

Ecom Inventory Health is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Ecom Inventory Health use?

About 1.2k tokens (SKILL.md is roughly 4.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 4.7k tokens, read only when the agent opens those files.

What are the alternatives to Ecom Inventory Health?

Skills that share tags, products or a category with Ecom Inventory Health: Skin Health Analyzer (sickn33/agentic-awesome-skills, 47k stars), Codebase Health Dashboard (garrytan/gstack, 136k stars), Python Type Safety (wshobson/agents, 40k stars) and Health (agenticnotetaking/arscontexta, 3.5k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Ecom Inventory Health?

asgard-ai-platform (a GitHub organization) maintains it in asgard-ai-platform/skills, which has 242 GitHub stars. The repository holds 207 skills in this directory. The repository was last updated on June 6, 2026.

Source: asgard-ai-platform/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.