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 task-plannergit 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/task-planner)<a href="https://agentmods.dev/skills/hashgraph-online/awesome-codex-plugins/task-planner"><img src="https://agentmods.dev/badge/skills/hashgraph-online/awesome-codex-plugins/task-planner/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/task-planner"><img src="https://agentmods.dev/badge/skills/hashgraph-online/awesome-codex-plugins/task-planner.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00028 | $0.00290 |
| Opus 5.5 | $0.00011 | $0.00116 |
| Sonnet 5.5 | $0.00006 | $0.00058 |
| Haiku 4.5 | $0.00003 | $0.00029 |
Grade A, and why
task-planner 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.
What it actually says
Task Planner
Use this skill when the user wants help organizing work into a schedule.
Workflow
- Gather the planning window, available hours, deadlines, and any fixed meetings or blocked days.
- Group the work into concrete tasks with estimated effort and priority.
- Produce a schedule that is realistic, not just complete.
- Flag overflow, risky deadlines, and missing information.
Output Format
Return the plan in markdown with these sections:
SummaryScheduleFollow-UpsRisks
For each scheduled item, include:
- task name
- planned date
- estimated effort
- short reason for placement
Scheduling Rules
- Put urgent and high-priority work first.
- Avoid filling a day past the stated hour limit.
- Break large work into smaller steps when that makes the plan easier to follow.
- Keep at least one buffer slot when the schedule is tight.
- Call out tasks that do not fit inside the requested window.
Script Assist
When the user provides structured JSON tasks, you can use:
python .\scripts\build_schedule.py --input <tasks.json>
The script builds a first-pass markdown schedule that you can refine in your response.
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 · 50 lines · 28 tokens per session scan A b99c691cbcd7
task-planner is a skill published in the GitHub repository hashgraph-online/awesome-codex-plugins (1,326 stars, last pushed today), licensed Apache-2.0. It adds 28 tokens to every session and 290 once invoked, about $0.0001 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 2026-08-30.
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".
web-design-guidelines
Review UI code for Web Interface Guidelines compliance. Use when asked to "review my UI", "check accessibility", "audit design", "review UX", or "check my site against best practices".
frontend-ux-engineer
Use for frontend features, Next.js/React/Vue/Svelte UI, accessibility, responsive layout, design polish, state handling, forms, visual QA, or product workflow improvements.
research-agent
Use for current web/X research, library/API verification, competitive analysis, source-backed technical decisions, or updating docs with recent facts.