awesome-ChatGPT-repositories is a curated, searchable directory of open-source repositories related to ChatGPT, the OpenAI API, and Codex. It is for people looking for tools such as retrieval systems, agent libraries, chatbot interfaces, and command-line utilities, with catalogue entries that support searching the collection through coding-agent extensions.
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 taishi-i/awesome-ChatGPT-repositories --skill awesome-chatgpt-searchgit clone --depth 1 https://github.com/taishi-i/awesome-ChatGPT-repositoriesWrote 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/taishi-i/awesome-chatgpt-repositories/awesome-chatgpt-search)<a href="https://agentmods.dev/skills/taishi-i/awesome-chatgpt-repositories/awesome-chatgpt-search"><img src="https://agentmods.dev/badge/skills/taishi-i/awesome-chatgpt-repositories/awesome-chatgpt-search/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/taishi-i/awesome-chatgpt-repositories/awesome-chatgpt-search"><img src="https://agentmods.dev/badge/skills/taishi-i/awesome-chatgpt-repositories/awesome-chatgpt-search.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 | $0.00063 | $0.04027 |
| Opus 5.5 | $0.00025 | $0.01611 |
| Sonnet 5.5 | $0.00013 | $0.00805 |
| Haiku 4.5 | $0.00006 | $0.00403 |
Grade B, and why
awesome-chatgpt-search scanned grade B with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Enumerates other installed skillsmediumAgent snooping
Other skills' SKILL.md files reveal prompts, capabilities and secrets that should be invisible to peers.
find "$PWD" "$HOME/.agents/skills" "$HOME/.claude/skills" "${CODEX_HOME:-$HOME/.codex}/skills" -type f -name repos-unity.json -path "*awesome-chatgpt-search*" 2>/dev/null | head -1 How it starts
The opening of the file, as written. The whole thing — 257 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Search the awesome-ChatGPT-repositories database for the user's query.
Instructions
Ground rules — they apply whether this skill was invoked explicitly or picked automatically:
- Present only repositories from the bundled data files, even when the list has just a few matches — then say so and suggest other keywords rather than filling the gap from elsewhere.
- Don't search the web or open repository pages to add or verify details (setup, license, activity) unless the user explicitly asks for that: the curated list is the source of truth here, and its star counts and descriptions are snapshots. Copy names, URLs, and star counts exactly as they appear in the records.
- The output templates in Steps 5b–7 are fixed: keep their Markdown headings (
##,###), field labels, and order, and don't restyle them (for example, turning the result list into a table or a prose summary). - If the data files can't be read (for example, shell commands are blocked), say so and link https://github.com/taishi-i/awesome-ChatGPT-repositories instead of substituting other sources.
Step 1 — Interpret the query
The query is the text the user passed to this skill (the same skill runs in Claude Code, Codex, and other agents):
- Claude Code: the arguments of
/awesome-chatgpt-search, appended at the end asARGUMENTS: …. - Codex and other agents: the user's message that invoked this skill (
$awesome-chatgpt-searchin Codex), minus the skill mention itself.
If there is no explicit query text, use the user's latest request.
Supported query modifiers:
category:<name>— filter to one categorylanguage:<lang>— filter by programming languagelist categoriesorcategories— skip to Step 5b- Plain text — keyword search across all categories
The descriptions are in English, so convert non-English queries to English keywords before searching.
Examples:
| User query | English keywords to search |
|---|---|
| RAGを使ったチャットボット | RAG, retrieval, chatbot, vector |
| 코드 생성 도구 (Korean) | code generation, copilot, autocomplete |
| 中文问答系统 | chinese, QA, question answering |
| outil de résumé (French) | summarization, summary, text |
| LLMを使ったエージェント | agent, autonomous, LLM, tool use |
What ships with it
19 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- agents/openai.yaml 210 B
- data/repos-awesome-lists.json 35 KB
- data/repos-browser-extensions-a.json 38 KB
- data/repos-browser-extensions-b.json 50 KB
- data/repos-chatbots-a.json 58 KB
- data/repos-chatbots-b.json 72 KB
- data/repos-clis-a.json 40 KB
- data/repos-clis-b.json 50 KB
- data/repos-langchain.json 61 KB
- data/repos-nlp-a.json 59 KB
- data/repos-nlp-b.json 73 KB
- data/repos-openai-a.json 44 KB
- data/repos-openai-b.json 50 KB
- data/repos-others-a.json 55 KB
- data/repos-others-b.json 66 KB
- data/repos-prompts.json 65 KB
- data/repos-reimplementations.json 13 KB
- data/repos-tutorials.json 7.5 KB
- data/repos-unity.json 5.1 KB
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.
- 11d ago First seen · 257 lines · 63 tokens per session scan B 904d00849699
awesome-chatgpt-search is a skill published in the GitHub repository taishi-i/awesome-ChatGPT-repositories (3,297 stars, last pushed yesterday), licensed CC0-1.0. It adds 63 tokens to every session and 4,027 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it B with 1 finding (enumerates other installed skills). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-05.
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paper-daily
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fetch-llm-apps
Regenerate the ranked GitHub LLM applications pool (section/xllmapps.md) with fetchllmapps.py. USE FOR: refreshing the pool linked from applications.md. DO NOT USE FOR: hand-curating entries in applications.md or adding star badges to the generated file.
fetch-llm-papers
Refresh the LLM landscape paper pool (section/xllmpapers.md) with fetchllmpapers.py. USE FOR: refreshing citation counts or expanding topic coverage. DO NOT USE FOR: hand-curated entries (use add-new-entry-from-temp-md) or bestpractices.md citation counts (use update-cite-count).
ai-application-engineer
Expert-level AI Application Engineer with deep knowledge of RAG systems, LangChain, LlamaIndex, vector databases, prompt engineering, LLM API integration, and agent frameworks.
nlp-engineer
Elite NLP Engineer skill with expertise in transformer architectures (BERT, GPT, T5), text processing pipelines, LLM fine-tuning, RAG systems, and production NLP deployment. Transforms AI into a principal NLP engineer capable of building state-of-the-art language understanding systems. Use when: nlp, llm…