Awesome Codex Plugins is a curated catalogue and marketplace of installable plugins, skills, and related resources for OpenAI Codex and ChatGPT. It helps people find, create, validate, and submit extensions for Codex workflows across its app, command-line interface, and IDE extensions. The catalogue add-ons are the plugins, skills, agents, and hooks listed or supported by this project.
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 hashgraph-online/awesome-codex-plugins --skill energy-procurementgit clone --depth 1 https://github.com/hashgraph-online/awesome-codex-pluginsWrote 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/hashgraph-online/awesome-codex-plugins/energy-procurement)<a href="https://agentmods.dev/skills/hashgraph-online/awesome-codex-plugins/energy-procurement"><img src="https://agentmods.dev/badge/skills/hashgraph-online/awesome-codex-plugins/energy-procurement/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/hashgraph-online/awesome-codex-plugins/energy-procurement"><img src="https://agentmods.dev/badge/skills/hashgraph-online/awesome-codex-plugins/energy-procurement.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 | $0.00093 | $0.06379 |
| Opus 5.5 | $0.00037 | $0.02552 |
| Sonnet 5.5 | $0.00019 | $0.01276 |
| Haiku 4.5 | $0.00009 | $0.00638 |
Grade A, and why
energy-procurement 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 1mo 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.
Copies of this mod
8 near-identical copies found in the catalogue:
- energy-procurement — 100% identical, 2 lines differ
- energy-procurement — 100% identical, 2 lines differ
- energy-procurement — 100% identical, 0 lines differ
- energy-procurement — 98% identical, 4 lines differ
- energy-procurement — 98% identical, 4 lines differ
- energy-procurement — 97% identical, 47 lines differ
- energy-procurement — 97% identical, 26 lines differ
- energy-procurement — 97% identical, 4 lines differ
How it starts
The opening of the file, as written. The whole thing — 229 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Energy Procurement
Role and Context
You are a senior energy procurement manager at a large commercial and industrial (C&I) consumer with multiple facilities across regulated and deregulated electricity markets. You manage an annual energy spend of $15M–$80M across 10–50+ sites — manufacturing plants, distribution centers, corporate offices, and cold storage. You own the full procurement lifecycle: tariff analysis, supplier RFPs, contract negotiation, demand charge management, renewable energy sourcing, budget forecasting, and sustainability reporting. You sit between operations (who control load), finance (who own the budget), sustainability (who set emissions targets), and executive leadership (who approve long-term commitments like PPAs). Your systems include utility bill management platforms (Urjanet, EnergyCAP), interval data analytics (meter-level 15-minute kWh/kW), energy market data providers (ICE, CME, Platts), and procurement platforms (energy brokers, aggregators, direct ISO market access). You balance cost reduction against budget certainty, sustainability targets, and operational flexibility — because a procurement strategy that saves 8% but exposes the company to a $2M budget variance in a polar vortex year is not a good strategy.
When to Use
- Running an RFP for electricity or natural gas supply across multiple facilities
- Analyzing tariff structures and rate schedule optimization opportunities
- Evaluating demand charge mitigation strategies (load shifting, battery storage, power factor correction)
- Assessing PPA (Power Purchase Agreement) offers for on-site or virtual renewable energy
- Building annual energy budgets and hedge position strategies
- Responding to market volatility events (polar vortex, heat wave, regulatory changes)
How It Works
- Profile each facility's load shape using interval meter data (15-minute kWh/kW) to identify cost drivers
- Analyze current tariff structures and identify optimization opportunities (rate switching, demand response enrollment)
- Structure procurement RFPs with appropriate product specifications (fixed, index, block-and-index, shaped)
- Evaluate bids using total cost of energy (not just $/MWh) including capacity, transmission, ancillaries, and risk premium
- Execute contracts with staggered terms and layered hedging to avoid concentration risk
- Monitor market positions, rebalance hedges on trigger events, and report budget variance monthly
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.
- 1mo ago First seen · 229 lines · 93 tokens per session scan A 327e576abe11
energy-procurement is a skill published in the GitHub repository hashgraph-online/awesome-codex-plugins (1,384 stars, last pushed yesterday), licensed Apache-2.0. It adds 93 tokens to every session and 6,379 once invoked, about $0.0004 per session on Opus 5.5. 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 2026-09-05.
Other skills, from other repositories
awesome-chatgpt
Search this repository's awesome-ChatGPT-repositories list for open-source ChatGPT and LLM projects such as RAG frameworks, agents, chatbots, CLIs, prompts, and browser extensions. Use when the user asks to find tools, libraries, or repos related to ChatGPT, LLMs, or AI development; not for editing or adding list…
awesome-chatgpt-search
Search 2500+ curated ChatGPT and LLM open-source repositories. Use when the user asks to find tools, libraries, or repos related to ChatGPT, LLMs, RAG, agents, langchain, NLP, AI development, or any open-source AI tooling.
sprr
Single PR reviewer for awesome-quant. Use when the user asks to review, validate, comment on, label, close, or merge one specific pull request that adds README.md entries. Triggers include "sprr", "review PR", "check PR", and "validate contribution".
create-entry
Use when the user wants to suggest, draft, create, or add an awesome-quant README entry from a project URL, GitHub issue, or Linear issue, including choosing tags and category placement.
bprr
Bulk PR reviewer for awesome-quant. Use when the user asks to review all open PRs, review unreviewed PRs, bulk review, or mentions "bprr". Reviews open PRs lacking the reviewed label and presents a summary before any merge/comment/label action.
update-pypi-dates
Refresh tracked PyPI last-updated dates in awesome-quant README.md. Use when the user asks to update PyPI dates, refresh PyPI metadata, or run update-pypi-dates.