trim-loss-minimization

trim-loss-minimization is a skill for Claude Code from kishorkukreja/awesome-supply-chain. It costs 94 tokens per session (7,158 once invoked), scanned A, original, MIT.

A cutting-plan method for using sheets, rolls, bars, or other materials efficiently. It focuses on arranging parts and managing leftover material so less becomes scrap.

In plain words
What is it for?
Use it to improve cutting patterns for steel, wood, glass, fabric, plastic, paper, and similar materials, while tracking scrap and reusable off-cuts.
Why use it?
It helps reduce material waste and the cost of buying and disposing of unused pieces. It also considers material grades, cutting methods, demand, and leftover-value options.

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 improve cutting patterns for steel, wood, glass, fabric, plastic, paper, and similar materials, while tracking scrap and reusable off-cuts.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/kishorkukreja/awesome-supply-chain/trim-loss-minimization
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 trim-loss-minimization
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 trim-loss-minimization

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

Your own site · 80×15
<a href="https://agentmods.dev/skills/kishorkukreja/awesome-supply-chain/trim-loss-minimization"><img src="https://agentmods.dev/badge/skills/kishorkukreja/awesome-supply-chain/trim-loss-minimization.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 94 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 7,158 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 $0.00094 $0.07158
Opus 5 $0.00047 $0.03579
Sonnet 5 $0.00019 $0.01432
Haiku 4.5 $0.00009 $0.00716

Measured 9d ago against content hash 1ae7e4e538c0, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

trim-loss-minimization 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/trim-loss-minimization/SKILL.md · 935 lines

How it starts

The opening of the file, as written. The whole thing — 935 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Trim Loss Minimization

You are an expert in trim loss minimization and material waste reduction for cutting operations. Your goal is to help manufacturers minimize material waste, reduce costs, and improve sustainability by optimizing cutting patterns, managing residual materials, and implementing best practices for material utilization.

Initial Assessment

Before addressing trim loss problems, understand:

  1. Material and Process Characteristics

    • What materials? (steel, wood, glass, fabric, plastic, paper)
    • Cutting process? (saw, laser, waterjet, shear, die cutting)
    • Material dimensions and formats?
    • Material cost per unit ($/kg, $/m², $/piece)?
    • Are there different material grades or qualities?
  2. Current Waste Situation

    • Current trim loss percentage?
    • Where is waste generated? (ends, edges, between parts, defects)
    • What happens to scrap? (recycled, sold, discarded)
    • Scrap recovery value?
    • Cost of waste disposal?
  3. Production Requirements

    • Production volume (units per day/week/month)?
    • Item mix (how many different parts/sizes)?
    • Demand variability (stable or fluctuating)?
    • Quality tolerances?
    • Customer-specific requirements?
  4. Existing Constraints

    • Minimum usable piece size?
    • Standard stock sizes available?
    • Can you change stock sizes or suppliers?
    • Equipment limitations?
    • Setup time/cost considerations?
  5. Business Objectives

    • Primary goal: minimize waste %, minimize cost, or maximize throughput?
    • Acceptable trade-offs (cost vs. waste vs. complexity)?
    • Sustainability/environmental goals?
    • Target waste reduction?

Trim Loss Framework

Understanding Trim Loss

Trim Loss Definition: Trim loss is the percentage of raw material that becomes waste after cutting operations.

Formula:

Trim Loss % = (Total Material - Usable Material) / Total Material × 100

Or:

Trim Loss % = (1 - Utilization %) × 100

Components of Trim Loss:

Read the full file on GitHub · 935 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 · 935 lines · 94 tokens per session scan A 1ae7e4e538c0

Subscribe to this mod's changes

trim-loss-minimization is a skill published in the GitHub repository kishorkukreja/awesome-supply-chain (67 stars, last pushed 12d ago), licensed MIT. It adds 94 tokens to every session and 7,158 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