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 claude-apigit 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/claude-api)<a href="https://agentmods.dev/skills/hashgraph-online/awesome-codex-plugins/claude-api"><img src="https://agentmods.dev/badge/skills/hashgraph-online/awesome-codex-plugins/claude-api/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/claude-api"><img src="https://agentmods.dev/badge/skills/hashgraph-online/awesome-codex-plugins/claude-api.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 | $0.00053 | $0.02123 |
| Opus 5.5 | $0.00021 | $0.00849 |
| Sonnet 5.5 | $0.00011 | $0.00425 |
| Haiku 4.5 | $0.00005 | $0.00212 |
Grade A, and why
claude-api 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:
- claude-api — 100% identical, 4 lines differ
- claude-api — 100% identical, 0 lines differ
- claude-api — 100% identical, 0 lines differ
- claude-api — 89% identical, 34 lines differ
- claude-api — 89% identical, 34 lines differ
- claude-api — 89% identical, 34 lines differ
- claude-api — 89% identical, 34 lines differ
- claude-api — 89% identical, 34 lines differ
How it starts
The opening of the file, as written. The whole thing — 338 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Claude API
Build applications with the Anthropic Claude API and SDKs.
When to Activate
- Building applications that call the Claude API
- Code imports
anthropic(Python) or@anthropic-ai/sdk(TypeScript) - User asks about Claude API patterns, tool use, streaming, or vision
- Implementing agent workflows with Claude Agent SDK
- Optimizing API costs, token usage, or latency
Model Selection
| Model | ID | Best For |
|---|---|---|
| Opus 4.1 | claude-opus-4-1 |
Complex reasoning, architecture, research |
| Sonnet 4 | claude-sonnet-4-0 |
Balanced coding, most development tasks |
| Haiku 3.5 | claude-3-5-haiku-latest |
Fast responses, high-volume, cost-sensitive |
Default to Sonnet 4 unless the task requires deep reasoning (Opus) or speed/cost optimization (Haiku). For production, prefer pinned snapshot IDs over aliases.
Python SDK
Installation
pip install anthropic
Basic Message
import anthropic
client = anthropic.Anthropic() # reads ANTHROPIC_API_KEY from env
message = client.messages.create(
model="claude-sonnet-4-0",
max_tokens=1024,
messages=[
{"role": "user", "content": "Explain async/await in Python"}
]
)
print(message.content[0].text)
Streaming
with client.messages.stream(
model="claude-sonnet-4-0",
max_tokens=1024,
messages=[{"role": "user", "content": "Write a haiku about coding"}]
) as stream:
for text in stream.text_stream:
print(text, end="", flush=True)
System Prompt
message = client.messages.create(
model="claude-sonnet-4-0",
max_tokens=1024,
system="You are a senior Python developer. Be concise.",
messages=[{"role": "user", "content": "Review this function"}]
)
TypeScript SDK
Installation
npm install @anthropic-ai/sdk
Basic Message
import Anthropic from "@anthropic-ai/sdk";
const client = new Anthropic(); // reads ANTHROPIC_API_KEY from env
const message = await client.messages.create({
model: "claude-sonnet-4-0",
max_tokens: 1024,
messages: [
{ role: "user", content: "Explain async/await in TypeScript" }
],
});
console.log(message.content[0].text);
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 · 338 lines · 53 tokens per session scan A b708d716177e
claude-api is a skill published in the GitHub repository hashgraph-online/awesome-codex-plugins (1,352 stars, last pushed yesterday), licensed Apache-2.0. It adds 53 tokens to every session and 2,123 once invoked, about $0.0002 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.
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ax-python-ai
Use when writing Python code with axllm for named deployment profiles, generic provider clients, model selection, OpenAI-compatible calls, Responses, Gemini, Anthropic, routers, and balancers.
ax-python-flow
Use when writing Python code with axllm for flows, nodes, program graphs, nested programs, dynamic options, caching, and optimizer components.