PR Babysitter
openinterpreter/openinterpreter
Watches an open GitHub pull request until it merges, handling review comments, diagnosing CI failures and retrying flaky checks along the way.
Regenerate the ranked GitHub LLM applications pool (section/xllmapps.md) with fetchllmapps.py.
$ npx skills add kimtth/azure-openai-llm-notes --skill fetch-llm-apps -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install kimtth/azure-openai-llm-notes fetch-llm-apps --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/kimtth/azure-openai-llm-notes.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agent/skills/fetch-llm-apps .claude/skills/fetch-llm-apps && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "fetch-llm-apps" agent skill from https://github.com/kimtth/azure-openai-llm-notes/tree/main/.agent/skills/fetch-llm-apps into .claude/skills/fetch-llm-apps/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "fetch-llm-apps", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/kimtth/azure-openai-llm-notes/tree/main/.agent/skills/fetch-llm-appsType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add kimtth/azure-openai-llm-notes --skill fetch-llm-apps -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install kimtth/azure-openai-llm-notes fetch-llm-apps --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/kimtth/azure-openai-llm-notes.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.agent/skills/fetch-llm-apps .agents/skills/fetch-llm-apps && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "fetch-llm-apps" agent skill from https://github.com/kimtth/azure-openai-llm-notes/tree/main/.agent/skills/fetch-llm-apps into .agents/skills/fetch-llm-apps/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "fetch-llm-apps", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add kimtth/azure-openai-llm-notes --skill fetch-llm-apps -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install kimtth/azure-openai-llm-notes fetch-llm-apps --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/kimtth/azure-openai-llm-notes.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.agent/skills/fetch-llm-apps .cursor/skills/fetch-llm-apps && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "fetch-llm-apps" agent skill from https://github.com/kimtth/azure-openai-llm-notes/tree/main/.agent/skills/fetch-llm-apps into .cursor/skills/fetch-llm-apps/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "fetch-llm-apps", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/kimtth/azure-openai-llm-notes.git --path .agent/skills/fetch-llm-apps--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add kimtth/azure-openai-llm-notes --skill fetch-llm-apps -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install kimtth/azure-openai-llm-notes fetch-llm-apps --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/kimtth/azure-openai-llm-notes.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.agent/skills/fetch-llm-apps .gemini/skills/fetch-llm-apps && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "fetch-llm-apps" agent skill from https://github.com/kimtth/azure-openai-llm-notes/tree/main/.agent/skills/fetch-llm-apps into .gemini/skills/fetch-llm-apps/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "fetch-llm-apps", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install kimtth/azure-openai-llm-notes fetch-llm-appsInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add kimtth/azure-openai-llm-notes --skill fetch-llm-apps -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/kimtth/azure-openai-llm-notes.git skills-src && mkdir -p .github/skills && cp -r skills-src/.agent/skills/fetch-llm-apps .github/skills/fetch-llm-apps && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "fetch-llm-apps" agent skill from https://github.com/kimtth/azure-openai-llm-notes/tree/main/.agent/skills/fetch-llm-apps into .github/skills/fetch-llm-apps/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "fetch-llm-apps", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add kimtth/azure-openai-llm-notes --skill fetch-llm-apps -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install kimtth/azure-openai-llm-notes fetch-llm-apps --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/kimtth/azure-openai-llm-notes.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.agent/skills/fetch-llm-apps .opencode/skills/fetch-llm-apps && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "fetch-llm-apps" agent skill from https://github.com/kimtth/azure-openai-llm-notes/tree/main/.agent/skills/fetch-llm-apps into .opencode/skills/fetch-llm-apps/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "fetch-llm-apps", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
fetch-llm-appsRegenerate the ranked GitHub LLM applications pool (section/xllmapps.md) with fetchllmapps.py.
Fetch LLM Apps is an agent skill from kimtth/azure-openai-llm-notes. 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.
Its SKILL.md is about 590 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It works with GitHub. The repository describes itself as: A curated collection of resources for 🌌 Azure OpenAI, 🦙 LLMs (+RAG, Agents). Monthly Updates.
Read from SKILL.md and the folder at commit c053950. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Shell commands in SKILL.md call:
pythonFrom the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names these keys or tokens, usually read from environment variables:
GITHUB_TOKENFrom names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Fetch LLM Apps loads about 588 tokens when it runs. Until then it costs about 68 tokens; SKILL.md has 200 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
Without a licence we can't republish the file, so here is its outline and opening line. It has 200 words (~588 tokens).
“section/x_llm_apps.md is generated by code/fetch_llm_apps.py from GitHub topic and phrase searches, deduplicated and sorted by stars. Phrase facets broaden discovery across AI engineering, applications, infrastructure, and learning resources. External catalogs may inform search vocabulary only; never copy their repository records…”
Just SKILL.md in .agent/skills/fetch-llm-apps of kimtth/azure-openai-llm-notes.
Open the folder on GitHubat commit c053950
Fetch LLM Apps next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Fetch LLM Apps this skillkimtth/azure-openai-llm-notes | 410 | — | ~588 | Automated safety check: Pass | None | |
| PR Babysitteropeninterpreter/openinterpreter | 69k | 3 repos | ~4.2k | Automated safety check: Pass | Apache-2.0 | |
| Diagnosing Superpowers Sessionsobra/superpowers | 296k | 3 repos | ~1.7k | Automated safety check: Pass | MIT | |
| GitHub Deep Researchbytedance/deer-flow | 83k | 5 repos | ~1.3k | Automated safety check: Pass | MIT | |
| Greplooponyx-dot-app/onyx | 32k | 4 repos | ~3.3k | Automated safety check: Pass | MIT | |
| Update V8 Versionopeninterpreter/openinterpreter | 69k | 2 repos | ~845 | Automated safety check: Pass | Apache-2.0 |
openinterpreter/openinterpreter
Watches an open GitHub pull request until it merges, handling review comments, diagnosing CI failures and retrying flaky checks along the way.
obra/superpowers
Investigates a session where Superpowers went wrong, reads the transcripts on disk and produces an evidence-cited report, optionally prepared as a bug report for the maintainers.
bytedance/deer-flow
Researches a GitHub repository over four rounds using the GitHub API and web search, then writes a structured markdown report with timeline, metrics and Mermaid diagrams.
onyx-dot-app/onyx
Iteratively improves a PR (GitHub), MR (GitLab), or shelved changelist (Perforce) until Greptile gives it a 5/5 confidence score with zero unresolved comments.
openinterpreter/openinterpreter
Bumps the pinned v8 and rusty_v8 versions in Codex, validates the release-candidate path with the v8-canary check, and traces failures to upstream build changes.
mvanhorn/last30days-skill
Research what people actually say about any topic in the last 30 days.
kimtth/azure-openai-llm-notes
Refresh the LLM landscape paper pool (section/xllmpapers.md) with fetchllmpapers.py.
kimtth/azure-openai-llm-notes
Format new entries from temp.md into tempentries.md, ready to insert into the section files.
kimtth/azure-openai-llm-notes
Update citation counts for papers in the ranked sections of section/bestpractices.md with updatecitationcounts.py.
kimtth/azure-openai-llm-notes
Insert formatted entries from tempentries.md into the section files.
Works with
Regenerate the ranked GitHub LLM applications pool (section/xllmapps.md) with fetchllmapps.py. Fetch LLM Apps is an agent skill from kimtth/azure-openai-llm-notes.py.
Fetch LLM Apps fits situations like: : refreshing the pool linked from applications.md; : hand-curating entries in applications.md; adding star badges to the generated file.
Run `npx skills add kimtth/azure-openai-llm-notes --skill fetch-llm-apps -a claude-code`. Or copy the skill folder (.agent/skills/fetch-llm-apps in kimtth/azure-openai-llm-notes) into .claude/skills/fetch-llm-apps in your project. Claude Code loads it when a task matches its description.
Run `npx skills add kimtth/azure-openai-llm-notes --skill fetch-llm-apps -a codex`. Or copy the skill folder (.agent/skills/fetch-llm-apps in kimtth/azure-openai-llm-notes) into .agents/skills/fetch-llm-apps in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add kimtth/azure-openai-llm-notes --skill fetch-llm-apps -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/fetch-llm-apps, .gemini/skills/fetch-llm-apps, .github/skills/fetch-llm-apps and .opencode/skills/fetch-llm-apps in your project.
Going by SKILL.md and its folder, Fetch LLM Apps needs the command-line tools its instructions call (python) and credentials named GITHUB_TOKEN. Our summary lists: A credential in GITHUB_TOKEN.
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
No licence was found for Fetch LLM Apps or its repository. Without one, default copyright applies: ask the author before reusing or redistributing it.
About 588 tokens (SKILL.md is roughly 2.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Fetch LLM Apps: PR Babysitter (openinterpreter/openinterpreter, 69k stars), Diagnosing Superpowers Sessions (obra/superpowers, 296k stars), GitHub Deep Research (bytedance/deer-flow, 83k stars) and Greploop (onyx-dot-app/onyx, 32k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
kimtth (a GitHub user) maintains it in kimtth/azure-openai-llm-notes, which has 410 GitHub stars. The repository holds 5 skills in this directory. The repository was last updated on October 2, 2026.
Source: kimtth/azure-openai-llm-notes on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.