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 waggle-recallgit 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/waggle-recall)<a href="https://agentmods.dev/skills/hashgraph-online/awesome-codex-plugins/waggle-recall"><img src="https://agentmods.dev/badge/skills/hashgraph-online/awesome-codex-plugins/waggle-recall/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/waggle-recall"><img src="https://agentmods.dev/badge/skills/hashgraph-online/awesome-codex-plugins/waggle-recall.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 | $0.00226 |
| Opus 5.5 | $0.00011 | $0.00090 |
| Sonnet 5.5 | $0.00006 | $0.00045 |
| Haiku 4.5 | $0.00003 | $0.00023 |
Grade A, and why
waggle-recall 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
1 near-identical copy found in the catalogue:
- waggle-recall — 100% identical, 0 lines differ
What it actually says
Recall project history
- Extract the requested topic from the user's prompt. Ask only if no topic can reasonably be inferred.
- Determine the stable project scope: prefer the credential-free Git remote identity, otherwise the canonical absolute Git root or workspace path.
- Call
query_graphwith the topic, that project scope,agent_id: "codex",retrieval_mode: "hybrid",max_nodes: 10, andmax_depth: 1. - If a useful node needs more context, call
get_relatedwith its node ID andmax_depth: 1. - Answer with a concise synthesis. Identify contradictions, updates, provenance, or uncertainty when returned. Never treat an empty result as evidence that something did not happen.
This is the Codex skill equivalent of /waggle-recall <topic>; invoke it as $waggle-recall followed by the topic.
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 · 15 lines · 28 tokens per session scan A 1e80c13a620b
waggle-recall is a skill published in the GitHub repository hashgraph-online/awesome-codex-plugins (1,384 stars, last pushed today), licensed Apache-2.0. It adds 28 tokens to every session and 226 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.
compress
Vault alignment engine. Detects and fixes 5 types of structural misalignments: broken backlinks, concept fragmentation, entity miscategorization, duplicated entities, and misnamed entities. Delegates all writes to /bedrock:preserve. Supports interactive mode (user confirmation) and cron mode (autonomous mechanical…
drawio-reconstruction
Reconstructs reference images into high-fidelity, editable Draw.io files with rendered previews: native Draw.io elements carry text and structure, SVG covers simple icons that match the reference, and cropped or transparent PNGs preserve complex visuals. Use when the user wants a diagram image, research figure…
memorise
Capture key learnings, patterns, gotchas, or context as persistent memories.
performance-audit
Full-stack performance health check across 12 dimensions. Rendering, bundles, assets, API/network, algorithms, memory, database, caching, Web Vitals, backend runtime, concurrency, and framework-specific pathologies. Evidence-based Impact Models with confidence tiers and a prioritized optimization roadmap. Switches…