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Agent skill

Algo Sc Eoq

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

Calculate Economic Order Quantity to minimize total inventory cost (ordering + holding).

MITAuto-check passed

Install Algo Sc Eoq

skills CLI
$ npx skills add asgard-ai-platform/skills --skill algo-sc-eoq -a claude-code

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

GitHub CLI
$ gh skill install asgard-ai-platform/skills algo-sc-eoq --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/algo-sc-eoq .claude/skills/algo-sc-eoq && 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
algo-sc-eoq
GitHub stars
242
Token cost
~1k tokens
SKILL.md length
407 words
Files
4 (incl. scripts, references)
Skills in repo
207
Repo updated
First seen
Licence
MIT

At a glance

Calculate Economic Order Quantity to minimize total inventory cost (ordering + holding).

  • Works in 4 steps: Input Validation → Core Algorithm → Verification → …
  • The user needs to determine optimal order size
  • SKILL.md covers Overview, When to Use, Algorithm and Output Format, plus 4 more sections
  • Runs Python scripts from its folder; calls python

What it does

Algo Sc Eoq is an agent skill from asgard-ai-platform/skills. Calculate Economic Order Quantity to minimize total inventory cost (ordering + holding). Use this skill when the user needs to determine optimal order size, balance ordering frequency against storage costs, or set reorder points — even if they say 'how much to order', 'optimal batch size', or 'inventory cost minimization'.

Its SKILL.md is about 1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files, including scripts and reference files (for example `examples/sample_input.json`, `references/eoq-discounts.md` and `scripts/eoq.py`).

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 determine optimal order size
  • Balance ordering frequency against storage costs
  • Set reorder points — even if they say how much to order
  • Optimal batch size

Example prompts

  • “how much to order”
  • “optimal batch size”
  • “inventory cost minimization”
  • “/algo-sc-eoq”

Requirements

  • Python 3

Workflow steps

4 steps, taken from the step headings in SKILL.md.

  1. Input Validation
  2. Core Algorithm
  3. Verification
  4. Output

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

    Ships 1 file in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python

    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

Algo Sc Eoq loads about 1k tokens when it runs, and up to ~3.9k if it reads all its reference files. Until then it costs about 84 tokens; SKILL.md has 407 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~84
When it runs · the whole SKILL.md, loaded when a task matches
~1k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~3.9k

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); the scripts in this folder are not scanned.

SKILL.md

The full file from asgard-ai-platform/skills at commit 4e7f4f8, republished under its MIT licence (© asgard-ai-platform). 407 words, ~1,023 tokens.

Download SKILL.mdSave it as .claude/skills/algo-sc-eoq/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
algo-sc-eoq
description
Calculate Economic Order Quantity to minimize total inventory cost (ordering + holding). Use this skill when the user needs to determine optimal order size, balance ordering frequency against storage costs, or set reorder points — even if they say 'how much to order', 'optimal batch size', or 'inventory cost minimization'.
metadata.category
WP-41 供應鏈演算法
metadata.tags
supply-chain, eoq, inventory, ordering

Economic Order Quantity (EOQ)

Overview

EOQ determines the order quantity that minimizes total inventory cost = ordering cost + holding cost. Formula: EOQ = √(2DS/H) where D=annual demand, S=ordering cost per order, H=holding cost per unit per year. Assumes constant demand and instantaneous replenishment.

When to Use

Trigger conditions:

  • Setting standard order quantities for inventory replenishment
  • Balancing ordering frequency against warehousing costs
  • Baseline calculation before applying safety stock adjustments

When NOT to use:

  • When demand is highly uncertain (use newsvendor model)
  • When products are perishable with short shelf life
  • When quantity discounts change the cost structure significantly

Algorithm

IRON LAW: EOQ Assumes CONSTANT, KNOWN Demand
If demand is variable or uncertain, EOQ gives the wrong answer.
Real-world application: use EOQ as a starting point, then add
safety stock for demand variability and lead time uncertainty.
Total cost curve is flat near EOQ — ±20% from optimal Q changes
total cost by only ~2%.
Phase 1: Input Validation

Determine: D (annual demand in units), S (fixed cost per order), H (holding cost per unit per year = unit cost × holding rate, typically 20-30% of unit value). Gate: All costs positive, demand estimate reasonable.

Phase 2: Core Algorithm
  1. EOQ = √(2 × D × S / H)
  2. Number of orders per year = D / EOQ
  3. Reorder point = d × L (daily demand × lead time in days)
  4. Total annual cost = (D/Q × S) + (Q/2 × H) at Q = EOQ
Phase 3: Verification

Check: ordering cost component ≈ holding cost component (they're equal at EOQ). Total cost is at minimum. Gate: Ordering cost ≈ holding cost (±5%).

Phase 4: Output

Return EOQ with cost breakdown and reorder point.

Output Format

json
{
  "eoq": 500,
  "orders_per_year": 20,
  "reorder_point": 150,
  "annual_cost": {"ordering": 2000, "holding": 2000, "total": 4000},
  "metadata": {"demand": 10000, "order_cost": 100, "holding_cost": 4.0}
}

Examples

Sample I/O

Input: D=10,000 units/year, S=$100/order, H=$4/unit/year Expected: EOQ = √(2×10000×100/4) = √500000 = 707 units

Show full SKILL.md (182 more words)Show less
Edge Cases
InputExpectedWhy
Very high S, low HLarge EOQ, few ordersMinimize expensive ordering
Very low S, high HSmall EOQ, frequent ordersMinimize expensive holding
D = 0EOQ = 0, no orderingNo demand, no orders needed

Gotchas

  • Holding cost underestimation: H should include: capital cost, storage, insurance, obsolescence, handling. Companies often only count warehouse rent, understating true H.
  • Flat cost curve: Total cost is insensitive near EOQ. Rounding EOQ to a convenient number (full pallet, container) costs very little.
  • Quantity discounts: Price breaks at certain quantities may make it cheaper to order MORE than EOQ. Compare total cost at EOQ vs discount breakpoints.
  • Lead time variability: EOQ doesn't address when to order, only how much. Add safety stock: SS = z × σ_demand × √(lead time).
  • Multi-item coordination: When multiple items share ordering costs (same supplier), use joint replenishment models, not individual EOQs.

Scripts

ScriptDescriptionUsage
scripts/eoq.pyCompute Economic Order Quantity and cost breakdownpython scripts/eoq.py --help

Run python scripts/eoq.py --verify to execute built-in sanity tests.

References

  • For EOQ with quantity discounts, see references/eoq-discounts.md
  • For safety stock calculation, see algo-sc-safety-stock

© 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 (scripts, references) in algo-sc-eoq of asgard-ai-platform/skills.

  • SKILL.md
  • examples/sample_input.json
  • references/eoq-discounts.md
  • scripts/eoq.py

Open the folder on GitHubat commit 4e7f4f8

Compare with similar skills

Algo Sc Eoq 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.

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Inventory Stock Reconciliationsickn33/agentic-awesome-skills47k1 repos~6.4kAutomated safety check: PassMIT
Video Template Frame Build Minimalnexu-io/open-design100k—~371Automated safety check: PassApache-2.0

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Questions about Algo Sc Eoq

What does Algo Sc Eoq do?

Calculate Economic Order Quantity to minimize total inventory cost (ordering + holding). Algo Sc Eoq is an agent skill from asgard-ai-platform/skills. Calculate Economic Order Quantity to minimize total inventory cost (ordering + holding).

When should I use Algo Sc Eoq?

Algo Sc Eoq fits situations like: the user needs to determine optimal order size; balance ordering frequency against storage costs; set reorder points — even if they say how much to order; optimal batch size.

How do I install Algo Sc Eoq in Claude Code?

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

How do I install Algo Sc Eoq in Codex?

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

Can I use Algo Sc Eoq 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 algo-sc-eoq -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/algo-sc-eoq, .gemini/skills/algo-sc-eoq, .github/skills/algo-sc-eoq and .opencode/skills/algo-sc-eoq in your project.

What does Algo Sc Eoq need to run?

Going by SKILL.md and its folder, Algo Sc Eoq needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3.

Does Algo Sc Eoq 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 Algo Sc Eoq 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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Algo Sc Eoq use?

Algo Sc Eoq 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 Algo Sc Eoq use?

About 1k tokens (SKILL.md is roughly 4.1k 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 2.9k tokens, read only when the agent opens those files.

What are the alternatives to Algo Sc Eoq?

Skills that share tags, products or a category with Algo Sc Eoq: Minimalism (sickn33/agentic-awesome-skills, 47k stars), Unit Economics Calculator (revfactory/harness-100, 1.3k stars), Asset Inventory (sickn33/agentic-awesome-skills, 47k stars) and Inventory Stock Reconciliation (sickn33/agentic-awesome-skills, 47k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Algo Sc Eoq?

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.