LLM Benchmarking with lm-evaluation-harness
Orchestra-Research/AI-Research-SKILLs
Runs lm-evaluation-harness to benchmark language models on academic suites such as MMLU, GSM8K and HumanEval, compare models and track training checkpoints.
在发布前评估 Agent Skill bundle 的结构完整性、触发质量、产物改进、脚本正确性、安全性、已安装目录树完整性和目标宿主可移植性。
Install Skill Release Gate
$ npx skills add fancyboi999/ai-engineering-from-scratch-zh --skill skill-release-gate -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install fancyboi999/ai-engineering-from-scratch-zh skill-release-gate --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/fancyboi999/ai-engineering-from-scratch-zh.git skills-src && mkdir -p .claude/skills && cp -r skills-src/phases/13-tools-and-protocols/27-skill-evals-packaging-and-portability/outputs/skill-release-gate .claude/skills/skill-release-gate && 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 "skill-release-gate" agent skill from https://github.com/fancyboi999/ai-engineering-from-scratch-zh/tree/main/phases/13-tools-and-protocols/27-skill-evals-packaging-and-portability/outputs/skill-release-gate into .claude/skills/skill-release-gate/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "skill-release-gate", 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/fancyboi999/ai-engineering-from-scratch-zh/tree/main/phases/13-tools-and-protocols/27-skill-evals-packaging-and-portability/outputs/skill-release-gateType 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 fancyboi999/ai-engineering-from-scratch-zh --skill skill-release-gate -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install fancyboi999/ai-engineering-from-scratch-zh skill-release-gate --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/fancyboi999/ai-engineering-from-scratch-zh.git skills-src && mkdir -p .agents/skills && cp -r skills-src/phases/13-tools-and-protocols/27-skill-evals-packaging-and-portability/outputs/skill-release-gate .agents/skills/skill-release-gate && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "skill-release-gate" agent skill from https://github.com/fancyboi999/ai-engineering-from-scratch-zh/tree/main/phases/13-tools-and-protocols/27-skill-evals-packaging-and-portability/outputs/skill-release-gate into .agents/skills/skill-release-gate/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "skill-release-gate", 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 fancyboi999/ai-engineering-from-scratch-zh --skill skill-release-gate -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install fancyboi999/ai-engineering-from-scratch-zh skill-release-gate --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/fancyboi999/ai-engineering-from-scratch-zh.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/phases/13-tools-and-protocols/27-skill-evals-packaging-and-portability/outputs/skill-release-gate .cursor/skills/skill-release-gate && 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 "skill-release-gate" agent skill from https://github.com/fancyboi999/ai-engineering-from-scratch-zh/tree/main/phases/13-tools-and-protocols/27-skill-evals-packaging-and-portability/outputs/skill-release-gate into .cursor/skills/skill-release-gate/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "skill-release-gate", 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/fancyboi999/ai-engineering-from-scratch-zh.git --path phases/13-tools-and-protocols/27-skill-evals-packaging-and-portability/outputs/skill-release-gate--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 fancyboi999/ai-engineering-from-scratch-zh --skill skill-release-gate -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install fancyboi999/ai-engineering-from-scratch-zh skill-release-gate --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/fancyboi999/ai-engineering-from-scratch-zh.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/phases/13-tools-and-protocols/27-skill-evals-packaging-and-portability/outputs/skill-release-gate .gemini/skills/skill-release-gate && 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 "skill-release-gate" agent skill from https://github.com/fancyboi999/ai-engineering-from-scratch-zh/tree/main/phases/13-tools-and-protocols/27-skill-evals-packaging-and-portability/outputs/skill-release-gate into .gemini/skills/skill-release-gate/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "skill-release-gate", 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 fancyboi999/ai-engineering-from-scratch-zh skill-release-gateInstalls 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 fancyboi999/ai-engineering-from-scratch-zh --skill skill-release-gate -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/fancyboi999/ai-engineering-from-scratch-zh.git skills-src && mkdir -p .github/skills && cp -r skills-src/phases/13-tools-and-protocols/27-skill-evals-packaging-and-portability/outputs/skill-release-gate .github/skills/skill-release-gate && 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 "skill-release-gate" agent skill from https://github.com/fancyboi999/ai-engineering-from-scratch-zh/tree/main/phases/13-tools-and-protocols/27-skill-evals-packaging-and-portability/outputs/skill-release-gate into .github/skills/skill-release-gate/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "skill-release-gate", 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 fancyboi999/ai-engineering-from-scratch-zh --skill skill-release-gate -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install fancyboi999/ai-engineering-from-scratch-zh skill-release-gate --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/fancyboi999/ai-engineering-from-scratch-zh.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/phases/13-tools-and-protocols/27-skill-evals-packaging-and-portability/outputs/skill-release-gate .opencode/skills/skill-release-gate && 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 "skill-release-gate" agent skill from https://github.com/fancyboi999/ai-engineering-from-scratch-zh/tree/main/phases/13-tools-and-protocols/27-skill-evals-packaging-and-portability/outputs/skill-release-gate into .opencode/skills/skill-release-gate/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "skill-release-gate", 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.
Facts
- Skill name
skill-release-gate- GitHub stars
- 1.2k
- Token cost
- ~472 tokens
- SKILL.md length
- 123 words
- Files
- 8 (incl. scripts, references, assets)
- Skills in repo
- 14
- Repo updated
- First seen
- Licence
- MIT
At a glance
在发布前评估 Agent Skill bundle 的结构完整性、触发质量、产物改进、脚本正确性、安全性、已安装目录树完整性和目标宿主可移植性。
- Works in 11 steps: 将 SKILL_ROOT 解析为包含本已安装 SKILL.md… → 从原始工作区工作目录解析 TARGET_ROOT，并将用户提供的候选解析为绝对… → 从 SKILL_ROOT 读取… → …
- AI & LLM Engineering work in your project
- SKILL.md covers 工作流, Output contract and Failure behavior
- Runs Python scripts from its folder
What it does
Skill Release Gate is an agent skill from fancyboi999/ai-engineering-from-scratch-zh. 在发布前评估 Agent Skill bundle 的结构完整性、触发质量、产物改进、脚本正确性、安全性、已安装目录树完整性和目标宿主可移植性。
Its SKILL.md is about 470 tokens, which your agent loads only when the skill is triggered. The skill folder holds 11 other files, including scripts, reference files and assets (for example `assets/hosts.json`, `assets/manifest.json` and `evals/artifacts.json`).
It sits in AI & LLM Engineering. It works with Python. The repository describes itself as: Agent工程师最全学习路径 · 从零精通 AI 工程 · 20 阶段 503 课 · 中文全量翻译 + 配套站点 + 动画讲解视频 · 如何成为 AI Agent 工程师的修成指南. The licence is MIT.
When your agent uses it
- AI & LLM Engineering work in your project
Example prompts
- “/skill-release-gate”
Requirements
- Python 3
Workflow steps
11 steps, taken from the first numbered list in SKILL.md.
- 将 SKILL_ROOT 解析为包含本已安装 SKILL.md 的绝对目录。不要假定进程 cwd 就是已安装 bundle。
- 从原始工作区工作目录解析 TARGET_ROOT，并将用户提供的候选解析为绝对 TARGET_BUNDLE。
- 从 SKILL_ROOT 读取 references/eval-contract.md。
- 检查 TARGET_BUNDLE 下 evals/cases.json 中的正例和近似请求触发案例。
- 检查 TARGET_BUNDLE 下 evals/artifacts.json 中共享的 baseline 与使用 skill 后断言。
- 检查 TARGET_BUNDLE 下 evals/evidence.json 中显式的脚本和安全结果。
- 检查 TARGET_BUNDLE 下 assets/hosts.json 声明的运行时能力，并对照其 assets/manifest.json 验证目标文件哈希。
- 对于生产，用捕获结果替换确定性预测、产物、证据和宿主能力；设置四种捕获模式；并将每个原始触发观察、两份产物、完整证据集和非空宿主矩阵绑定到非空来源及匹配的 SHA-256 溯源摘要。这些本地检查可设置 localEvidenceReady，但可在本地重算的哈希不能证明捕获真实性。
- 获取一份外部 JSON 证明，其 evidenceRoot 与报告相匹配；并从独立受信策略或发布渠道获得其精确字节的 SHA-256。证明必须是目标 bundle 外的常规文件。
- 执行前展示精确解析后的 argv。已安装评估器位于 SKILL_ROOT 下的 scripts/evaluate_skill.py。对随附课程 fixture，用 python3、该绝对评估器路径、--fixture-demo 和绝对 TARGET_BUNDLE 构建…
- 返回 checksPassed、fixturePassed、localEvidenceReady、trustAnchorValid、productionReady 和 passed，同时给出证据根、评估模式、失败检查、精确率、召回率、每个原始触发观察、每案例重复运行率、产物比较…
What it can do on your machine
Read from SKILL.md and the folder at commit 94b9888. It shows what the files ask for, not the result of running them.
Tool permissions
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.
Runs code
Ships 1 file in scripts/ (Python), which the agent can run.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Skill Release Gate loads about 472 tokens when it runs, and up to ~1.3k if it reads all its reference files. Until then it costs about 23 tokens; SKILL.md has 123 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.
Safety
Auto-check passed
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); the scripts in this folder are not scanned.
SKILL.md
The full file from fancyboi999/ai-engineering-from-scratch-zh at commit 94b9888, republished under its MIT licence (© fancyboi999). 123 words, ~472 tokens.
Download SKILL.mdSave it as
.claude/skills/skill-release-gate/SKILL.md (or your agent's skills folder). This skill also uses 7 other files; get the full folder from GitHub.- name
- skill-release-gate
- description
- 在发布前评估 Agent Skill bundle 的结构完整性、触发质量、产物改进、脚本正确性、安全性、已安装目录树完整性和目标宿主可移植性。
- license
- MIT
- metadata.lesson
- 27
Skill 发布门禁
在发布或分发 Agent Skill 目录 bundle 前使用此 skill。
工作流
- 将
SKILL_ROOT解析为包含本已安装SKILL.md的绝对目录。不要假定进程 cwd 就是已安装 bundle。 - 从原始工作区工作目录解析
TARGET_ROOT，并将用户提供的候选解析为绝对TARGET_BUNDLE。 - 从
SKILL_ROOT读取references/eval-contract.md。 - 检查
TARGET_BUNDLE下evals/cases.json中的正例和近似请求触发案例。 - 检查
TARGET_BUNDLE下evals/artifacts.json中共享的 baseline 与使用 skill 后断言。 - 检查
TARGET_BUNDLE下evals/evidence.json中显式的脚本和安全结果。 - 检查
TARGET_BUNDLE下assets/hosts.json声明的运行时能力，并对照其assets/manifest.json验证目标文件哈希。 - 对于生产，用捕获结果替换确定性预测、产物、证据和宿主能力；设置四种捕获模式；并将每个原始触发观察、两份产物、完整证据集和非空宿主矩阵绑定到非空来源及匹配的 SHA-256 溯源摘要。这些本地检查可设置
localEvidenceReady，但可在本地重算的哈希不能证明捕获真实性。 - 获取一份外部 JSON 证明，其
evidenceRoot与报告相匹配；并从独立受信策略或发布渠道获得其精确字节的 SHA-256。证明必须是目标 bundle 外的常规文件。 - 执行前展示精确解析后的 argv。已安装评估器位于
SKILL_ROOT下的scripts/evaluate_skill.py。对随附课程 fixture，用python3、该绝对评估器路径、--fixture-demo和绝对TARGET_BUNDLE构建 argv。对生产，使用同一已安装脚本并传入--attestation、--trusted-attestation-sha256和绝对TARGET_BUNDLE，但不传--fixture-demo。 - 返回
checksPassed、fixturePassed、localEvidenceReady、trustAnchorValid、productionReady和passed，同时给出证据根、评估模式、失败检查、精确率、召回率、每个原始触发观察、每案例重复运行率、产物比较、脚本和安全证据、已安装目录树验证及可移植性矩阵。包含已解析脚本路径、已解析目标路径、cwd、精确 argv 和退出码。将不可用观察标为未验证。
Output contract
返回完整 JSON 评估报告。保留每项分层检查及其证据，避免一个通过的汇总掩盖路由、产物、脚本、安全、已安装目录树或可移植性失败。fixturePassed 表示教学 fixture 成功；localEvidenceReady 仅表示本地摘要完整性；只有 productionReady 也具有有效的包外信任锚时，passed 才为 true。
Failure behavior
若配置无效、溯源缺失或不匹配、受信证明缺失或无效、文件哈希不同、必需能力缺失，或任一生产门禁失败，均以非零结果停止并报告失败层。显式 --fixture-demo 路径仅在 fixturePassed 为 true 时才可成功退出，且绝不作出发布声明。绝不自动发布、安装到其他位置、修复证据、创建信任决策或放宽阈值。
不要仅因 SKILL.md 能解析或一个正例 prompt 被激活就发布 bundle。目标宿主丢弃必需伴随文件或忽略必需运行时扩展时，不要将包标为可移植。
© fancyboi999, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 7 other files (scripts, references, assets) in phases/13-tools-and-protocols/27-skill-evals-packaging-and-portability/outputs/skill-release-gate of fancyboi999/ai-engineering-from-scratch-zh.
- SKILL.md
- assets/hosts.json
- assets/manifest.json
- evals/artifacts.json
- evals/cases.json
- evals/evidence.json
- references/eval-contract.md
- scripts/evaluate_skill.py
Open the folder on GitHubat commit 94b9888
Compare with similar skills
Skill Release Gate 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 |
|---|---|---|---|---|---|---|
| Skill Release Gate this skillfancyboi999/ai-engineering-from-scratch-zh | 1.2k | — | ~472 | Automated safety check: Pass | MIT | |
| LLM Benchmarking with lm-evaluation-harnessOrchestra-Research/AI-Research-SKILLs | 13k | 8 repos | ~3k | Automated safety check: Pass | MIT | |
| Segment Anything Model GuideOrchestra-Research/AI-Research-SKILLs | 13k | 8 repos | ~3.3k | Automated safety check: Pass | MIT | |
| Chroma Vector DatabaseOrchestra-Research/AI-Research-SKILLs | 13k | 7 repos | ~2.3k | Automated safety check: Pass | MIT | |
| CLIP Image-Text MatchingOrchestra-Research/AI-Research-SKILLs | 13k | 7 repos | ~1.7k | Automated safety check: Pass | MIT | |
| Paddle Design DistributedPaddlePaddle/Paddle | 24k | — | ~660 | Automated safety check: Pass | Apache-2.0 |
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Questions about Skill Release Gate
What does Skill Release Gate do?
在发布前评估 Agent Skill bundle 的结构完整性、触发质量、产物改进、脚本正确性、安全性、已安装目录树完整性和目标宿主可移植性。. Skill Release Gate is an agent skill from fancyboi999/ai-engineering-from-scratch-zh.
When should I use Skill Release Gate?
Skill Release Gate fits situations like: AI & LLM Engineering work in your project.
How do I install Skill Release Gate in Claude Code?
Run `npx skills add fancyboi999/ai-engineering-from-scratch-zh --skill skill-release-gate -a claude-code`. Or copy the skill folder (phases/13-tools-and-protocols/27-skill-evals-packaging-and-portability/outputs/skill-release-gate in fancyboi999/ai-engineering-from-scratch-zh) into .claude/skills/skill-release-gate in your project. Claude Code loads it when a task matches its description.
How do I install Skill Release Gate in Codex?
Run `npx skills add fancyboi999/ai-engineering-from-scratch-zh --skill skill-release-gate -a codex`. Or copy the skill folder (phases/13-tools-and-protocols/27-skill-evals-packaging-and-portability/outputs/skill-release-gate in fancyboi999/ai-engineering-from-scratch-zh) into .agents/skills/skill-release-gate in your project. Codex loads it when a task matches its description.
Can I use Skill Release Gate in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add fancyboi999/ai-engineering-from-scratch-zh --skill skill-release-gate -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/skill-release-gate, .gemini/skills/skill-release-gate, .github/skills/skill-release-gate and .opencode/skills/skill-release-gate in your project.
What does Skill Release Gate need to run?
Going by SKILL.md and its folder, Skill Release Gate needs Python for the scripts in its folder. Our summary lists: Python 3.
Does Skill Release Gate access the network?
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.
Is Skill Release Gate safe to install?
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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
What licence does Skill Release Gate use?
Skill Release Gate is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Skill Release Gate use?
About 472 tokens (SKILL.md is roughly 1.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 855 tokens, read only when the agent opens those files.
What are the alternatives to Skill Release Gate?
Skills that share tags, products or a category with Skill Release Gate: LLM Benchmarking with lm-evaluation-harness (Orchestra-Research/AI-Research-SKILLs, 13k stars), Segment Anything Model Guide (Orchestra-Research/AI-Research-SKILLs, 13k stars), Chroma Vector Database (Orchestra-Research/AI-Research-SKILLs, 13k stars) and CLIP Image-Text Matching (Orchestra-Research/AI-Research-SKILLs, 13k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Skill Release Gate?
fancyboi999 (a GitHub user) maintains it in fancyboi999/ai-engineering-from-scratch-zh, which has 1,195 GitHub stars. The repository holds 14 skills in this directory. The repository was last updated on October 9, 2026.
Source: fancyboi999/ai-engineering-from-scratch-zh on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.