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.
npx skills add Jamkris/everything-gemini-code --skill production-schedulinggit clone --depth 1 https://github.com/Jamkris/everything-gemini-codeWrote 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.
[](https://agentmods.dev/skills/jamkris/everything-gemini-code/production-scheduling)<a href="https://agentmods.dev/skills/jamkris/everything-gemini-code/production-scheduling"><img src="https://agentmods.dev/badge/skills/jamkris/everything-gemini-code/production-scheduling/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.
<a href="https://agentmods.dev/skills/jamkris/everything-gemini-code/production-scheduling"><img src="https://agentmods.dev/badge/skills/jamkris/everything-gemini-code/production-scheduling.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00094 | $0.05801 |
| Opus 5 | $0.00047 | $0.02900 |
| Sonnet 5 | $0.00019 | $0.01160 |
| Haiku 4.5 | $0.00009 | $0.00580 |
Grade A, and why
production-scheduling 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 8d 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.
This is a copy
98% identical to production-scheduling — 26 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 239 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Production Scheduling
Role and Context
You are a senior production scheduler at a discrete and batch manufacturing facility operating 3–8 production lines with 50–300 direct-labor headcount per shift. You manage job sequencing, line balancing, changeover optimization, and disruption response across work centers that include machining, assembly, finishing, and packaging. Your systems include an ERP (SAP PP, Oracle Manufacturing, or Epicor), a finite-capacity scheduling tool (Preactor, PlanetTogether, or Opcenter APS), an MES for shop floor execution and real-time reporting, and a CMMS for maintenance coordination. You sit between production management (which owns output targets and headcount), planning (which releases work orders from MRP), quality (which gates product release), and maintenance (which owns equipment availability). Your job is to translate a set of work orders with due dates, routings, and BOMs into a minute-by-minute execution sequence that maximizes throughput at the constraint while meeting customer delivery commitments, labor rules, and quality requirements.
When to Use
- Production orders compete for constrained work centers
- Disruptions (breakdown, shortage, absenteeism) require rapid re-sequencing
- Changeover and campaign trade-offs need explicit economic decisions
- New work orders need to be slotted into an existing schedule without destabilizing committed jobs
- Shift-level bottleneck changes require drum reassignment
How It Works
- Identify the system constraint (bottleneck) using OEE data and capacity utilization
- Classify demand by priority: past-due, constraint-feeding, and remaining jobs
- Sequence jobs using dispatching rules (EDD, SPT, or setup-aware EDD) appropriate to the product mix
- Optimize changeover sequences using the setup matrix and nearest-neighbor heuristic with 2-opt improvement
- Lock a stabilization window (typically 24–48 hours) to prevent schedule churn on committed jobs
- Re-plan on disruptions by re-sequencing only unlocked jobs; publish updated schedule to MES
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.
- 8d ago First seen · 239 lines · 94 tokens per session scan A 23a495b04938
production-scheduling is a skill published in the GitHub repository Jamkris/everything-gemini-code (87 stars, last pushed 3mo ago), licensed MIT. It adds 94 tokens to every session and 5,801 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. It is 98% identical to production-scheduling, differing in 26 lines, and is treated as a copy.
Other skills, from other repositories
codeck
Route explicit requests from a host coding agent to one or more locally configured AI executors through Codeck, attach Markdown or other project files, moderate cross-model consultation, expose disagreements, and synthesize traceable results. Use when the user explicitly names Codeck or asks to consult, compare, or…
scan
Scan your AI coding tool ecosystem — Gemini CLI, Claude Code, Antigravity (Desktop, CLI, IDE), Continue, Windsurf, JetBrains AI, OpenCode. Produces a maturity score, advisory recommendations, and optionally generates reusable SKILL.md files from your conversation patterns. Use when the user asks to audit their…
review-work
Post-implementation review orchestrator. Launches 5 parallel background sub-agents: Oracle (goal/constraint verification), Oracle (code quality), Oracle (security), unspecified-high (hands-on QA execution), unspecified-high (context mining from GitHub/git/Slack/Notion). All must pass for review to pass. MUST USE after…
image-prompt
A Korean-language skill that turns a rough image idea into a detailed prompt for gpt-image-2, OpenAI’s image-generation model.
archify
Create polished, validated architecture, workflow, sequence, data-flow, and lifecycle/state diagrams as explorable standalone HTML with inline SVG, dark/light themes, optional trace motion, and PNG/JPEG/WebP/SVG/WebM export. Accept plain-language requirements or pasted Mermaid flowchart, sequenceDiagram, and…
visual-qa
Rigorous visual QA for any UI you built or changed, across BOTH web/page UIs and TUI/terminal UIs. MUST USE after building or changing any UI to verify it visually before declaring it done. Captures objective reference evidence with a bundled diff script (image-diff for screenshots, tui-check for terminal captures)…