Molecode
AtomFlow-AI/MoleCode
A skill your agent uses for deterministic molecule understanding, graph-level editing, generation, and validation with MoleCode — an explicit Mermaid graph in which every atom and bond is a typed…
Batch insert reagents into Uni-Lab platform — add chemicals with CAS, SMILES, supplier info.
Install Batch Insert Reagent
$ npx skills add deepmodeling/Uni-Lab-OS --skill batch-insert-reagent -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install deepmodeling/Uni-Lab-OS batch-insert-reagent --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/deepmodeling/Uni-Lab-OS.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.cursor/skills/batch-insert-reagent .claude/skills/batch-insert-reagent && 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 "batch-insert-reagent" agent skill from https://github.com/deepmodeling/Uni-Lab-OS/tree/main/.cursor/skills/batch-insert-reagent into .claude/skills/batch-insert-reagent/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "batch-insert-reagent", 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/deepmodeling/Uni-Lab-OS/tree/main/.cursor/skills/batch-insert-reagentType 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 deepmodeling/Uni-Lab-OS --skill batch-insert-reagent -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install deepmodeling/Uni-Lab-OS batch-insert-reagent --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/deepmodeling/Uni-Lab-OS.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.cursor/skills/batch-insert-reagent .agents/skills/batch-insert-reagent && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "batch-insert-reagent" agent skill from https://github.com/deepmodeling/Uni-Lab-OS/tree/main/.cursor/skills/batch-insert-reagent into .agents/skills/batch-insert-reagent/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "batch-insert-reagent", 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 deepmodeling/Uni-Lab-OS --skill batch-insert-reagent -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install deepmodeling/Uni-Lab-OS batch-insert-reagent --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/deepmodeling/Uni-Lab-OS.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.cursor/skills/batch-insert-reagent .cursor/skills/batch-insert-reagent && 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 "batch-insert-reagent" agent skill from https://github.com/deepmodeling/Uni-Lab-OS/tree/main/.cursor/skills/batch-insert-reagent into .cursor/skills/batch-insert-reagent/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "batch-insert-reagent", 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/deepmodeling/Uni-Lab-OS.git --path .cursor/skills/batch-insert-reagent--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 deepmodeling/Uni-Lab-OS --skill batch-insert-reagent -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install deepmodeling/Uni-Lab-OS batch-insert-reagent --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/deepmodeling/Uni-Lab-OS.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.cursor/skills/batch-insert-reagent .gemini/skills/batch-insert-reagent && 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 "batch-insert-reagent" agent skill from https://github.com/deepmodeling/Uni-Lab-OS/tree/main/.cursor/skills/batch-insert-reagent into .gemini/skills/batch-insert-reagent/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "batch-insert-reagent", 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 deepmodeling/Uni-Lab-OS batch-insert-reagentInstalls 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 deepmodeling/Uni-Lab-OS --skill batch-insert-reagent -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/deepmodeling/Uni-Lab-OS.git skills-src && mkdir -p .github/skills && cp -r skills-src/.cursor/skills/batch-insert-reagent .github/skills/batch-insert-reagent && 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 "batch-insert-reagent" agent skill from https://github.com/deepmodeling/Uni-Lab-OS/tree/main/.cursor/skills/batch-insert-reagent into .github/skills/batch-insert-reagent/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "batch-insert-reagent", 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 deepmodeling/Uni-Lab-OS --skill batch-insert-reagent -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install deepmodeling/Uni-Lab-OS batch-insert-reagent --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/deepmodeling/Uni-Lab-OS.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.cursor/skills/batch-insert-reagent .opencode/skills/batch-insert-reagent && 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 "batch-insert-reagent" agent skill from https://github.com/deepmodeling/Uni-Lab-OS/tree/main/.cursor/skills/batch-insert-reagent into .opencode/skills/batch-insert-reagent/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "batch-insert-reagent", 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
batch-insert-reagent- GitHub stars
- 178
- Token cost
- ~2k tokens
- SKILL.md length
- 342 words
- Files
- 1
- Skills in repo
- 10
- Repo updated
- First seen
- Licence
- GPL-3.0
At a glance
Batch insert reagents into Uni-Lab platform — add chemicals with CAS, SMILES, supplier info.
- Works in 4 steps: ak / sk → AUTH → addr → BASE URL → 获取实验室信息（自动获取 lab_uuid） → …
- The user wants to add reagents
- SKILL.md covers 前置条件（缺一不可）, Session State, 请求约定 and API Endpoints, plus 5 more sections
- Calls curl and python; reaches leap-lab.test.bohrium.com and leap-lab.uat.bohrium.com
What it does
Batch Insert Reagent is an agent skill from deepmodeling/Uni-Lab-OS. Batch insert reagents into Uni-Lab platform — add chemicals with CAS, SMILES, supplier info. Use when the user wants to add reagents, insert chemicals, batch register reagents, or mentions 录入试剂/添加试剂/试剂入库/reagent.
Its SKILL.md is about 2k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Research & Science, covering Drug discovery and cheminformatics. The repository describes itself as: A Platform for Laboratory Automation. The licence is GPL-3.0.
When your agent uses it
- The user wants to add reagents
- Insert chemicals
- Batch register reagents
- Mentions 录入试剂/添加试剂/试剂入库/reagent
Example prompts
- “/batch-insert-reagent”
Requirements
- Python 3
Workflow steps
4 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit 43923ec. 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
Shell commands in SKILL.md call:
curlpython
From the folder's file list and the shell code blocks in SKILL.md.
Network
Hosts in commands or code, which the agent is likely to contact:
leap-lab.test.bohrium.comleap-lab.uat.bohrium.comleap-lab.bohrium.com
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
Batch Insert Reagent loads about 2k tokens when it runs. Until then it costs about 58 tokens; SKILL.md has 342 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); files beside SKILL.md are not scanned.
SKILL.md
The full file from deepmodeling/Uni-Lab-OS at commit 43923ec, republished under its GPL-3.0 licence (© deepmodeling). 342 words, ~2,001 tokens.
Download SKILL.mdSave it as
.claude/skills/batch-insert-reagent/SKILL.md (or your agent's skills folder).- name
- batch-insert-reagent
- description
- Batch insert reagents into Uni-Lab platform — add chemicals with CAS, SMILES, supplier info. Use when the user wants to add reagents, insert chemicals, batch register reagents, or mentions 录入试剂/添加试剂/试剂入库/reagent.
批量录入试剂 Skill
通过云端 API 批量录入试剂信息，支持逐条或批量操作。
前置条件（缺一不可）
使用本 skill 前，必须先确认以下信息。如果缺少任何一项，立即向用户询问并终止，等补齐后再继续。
1. ak / sk → AUTH
询问用户的启动参数，从 --ak --sk 或 config.py 中获取。
生成 AUTH token（任选一种方式）：
# 方式一：Python 一行生成
python -c "import base64,sys; print('Authorization: Lab ' + base64.b64encode(f'{sys.argv[1]}:{sys.argv[2]}'.encode()).decode())" <ak> <sk>
# 方式二：手动计算
# base64(ak:sk) → Authorization: Lab <token>2. --addr → BASE URL
--addr 值 | BASE |
|---|---|
test | https://leap-lab.test.bohrium.com |
uat | https://leap-lab.uat.bohrium.com |
local | http://127.0.0.1:48197 |
| 不传（默认） | https://leap-lab.bohrium.com |
确认后设置：
BASE="<根据 addr 确定的 URL>"
AUTH="Authorization: Lab <gen_auth.py 输出的 token>"两项全部就绪后才可发起 API 请求。
Session State
lab_uuid— 实验室 UUID（首次通过 API #1 自动获取，不需要问用户）
请求约定
所有请求使用 curl -s，POST 需加 Content-Type: application/json。
Windows 平台必须使用
curl.exe（而非 PowerShell 的curl别名），示例中的curl均指curl.exe。
API Endpoints
1. 获取实验室信息（自动获取 lab_uuid）
curl -s -X GET "$BASE/api/v1/edge/lab/info" -H "$AUTH"返回：
{ "code": 0, "data": { "uuid": "xxx", "name": "实验室名称" } }记住 data.uuid 为 lab_uuid。
2. 录入试剂
curl -s -X POST "$BASE/api/v1/lab/reagent" \
-H "$AUTH" -H "Content-Type: application/json" \
-d '{
"lab_uuid": "<lab_uuid>",
"cas": "<CAS号>",
"name": "<试剂名称>",
"molecular_formula": "<分子式>",
"smiles": "<SMILES>",
"stock_in_quantity": <入库数量>,
"unit": "<单位字符串>",
"supplier": "<供应商>",
"production_date": "<生产日期 ISO 8601>",
"expiry_date": "<过期日期 ISO 8601>"
}'返回成功时包含试剂 UUID：
{"code": 0, "data": {"uuid": "xxx", ...}}试剂字段说明
| 字段 | 类型 | 必填 | 说明 | 示例 |
|---|---|---|---|---|
lab_uuid | string | 是 | 实验室 UUID（从 API #1 获取） | "8511c672-..." |
cas | string | 是 | CAS 注册号 | "7732-18-3" |
name | string | 是 | 试剂中文/英文名称 | "水" |
molecular_formula | string | 是 | 分子式 | "H2O" |
smiles | string | 是 | SMILES 表示 | "O" |
stock_in_quantity | number | 是 | 入库数量 | 10 |
unit | string | 是 | 单位（字符串，见下表） | "mL" |
supplier | string | 否 | 供应商名称 | "国药集团" |
production_date | string | 否 | 生产日期（ISO 8601） | "2025-11-18T00:00:00Z" |
expiry_date | string | 否 | 过期日期（ISO 8601） | "2026-11-18T00:00:00Z" |
unit 单位值
| 值 | 单位 |
|---|---|
"mL" | 毫升 |
"L" | 升 |
"g" | 克 |
"kg" | 千克 |
"瓶" | 瓶 |
根据试剂状态选择：液体用
"mL"/"L"，固体用"g"/"kg"。
批量录入策略
方式一：用户提供 JSON 数组
用户一次性给出多条试剂数据：
[
{
"cas": "7732-18-3",
"name": "水",
"molecular_formula": "H2O",
"smiles": "O",
"stock_in_quantity": 10,
"unit": "mL"
},
{
"cas": "64-17-5",
"name": "乙醇",
"molecular_formula": "C2H6O",
"smiles": "CCO",
"stock_in_quantity": 5,
"unit": "L"
}
]Agent 自动为每条补充 lab_uuid、production_date、expiry_date 等字段后逐条提交。
Agent 循环调用 API #2 逐条录入，每条记录一次 API 调用。
方式二：用户逐个描述
用户口头描述试剂（如「帮我录入 500mL 的无水乙醇，Sigma 的」），agent 自行补全字段：
- 根据名称查找 CAS 号、分子式、SMILES（参考下方速查表或自行推断）
- 构建完整的请求体
- 向用户确认后提交
方式三：从 CSV/表格批量导入
用户提供 CSV 或表格文件路径，agent 读取并解析：
# 期望的 CSV 格式（首行为表头）
cas,name,molecular_formula,smiles,stock_in_quantity,unit,supplier,production_date,expiry_date
7732-18-3,水,H2O,O,10,mL,农夫山泉,2025-11-18T00:00:00Z,2026-11-18T00:00:00Z日期格式规则（重要）
所有日期字段（production_date、expiry_date）必须使用 ISO 8601 完整格式：YYYY-MM-DDTHH:MM:SSZ。
- 用户输入
2025-03-01→ 转换为"2025-03-01T00:00:00Z" - 用户输入
2025/9/1→ 转换为"2025-09-01T00:00:00Z" - 用户未提供日期 → 使用当天日期 +
T00:00:00Z，有效期默认 +1 年
禁止发送不带时间部分的日期字符串（如 "2025-03-01"），API 会拒绝。
执行与汇报
每次 API 调用后：
- 检查返回
code（0 = 成功） - 记录成功/失败数量
- 全部完成后汇总：「共录入 N 条试剂，成功 X 条，失败 Y 条」
- 如有失败，列出失败的试剂名称和错误信息
常见试剂速查表
| 名称 | CAS | 分子式 | SMILES |
|---|---|---|---|
| 水 | 7732-18-3 | H2O | O |
| 乙醇 | 64-17-5 | C2H6O | CCO |
| 乙酸 | 64-19-7 | C2H4O2 | CC(O)=O |
| 甲醇 | 67-56-1 | CH4O | CO |
| 丙酮 | 67-64-1 | C3H6O | CC(C)=O |
| 二甲基亚砜(DMSO) | 67-68-5 | C2H6OS | CS(C)=O |
| 乙酸乙酯 | 141-78-6 | C4H8O2 | CCOC(C)=O |
| 二氯甲烷 | 75-09-2 | CH2Cl2 | ClCCl |
| 四氢呋喃(THF) | 109-99-9 | C4H8O | C1CCOC1 |
| N,N-二甲基甲酰胺(DMF) | 68-12-2 | C3H7NO | CN(C)C=O |
| 氯仿 | 67-66-3 | CHCl3 | ClC(Cl)Cl |
| 乙腈 | 75-05-8 | C2H3N | CC#N |
| 甲苯 | 108-88-3 | C7H8 | Cc1ccccc1 |
| 正己烷 | 110-54-3 | C6H14 | CCCCCC |
| 异丙醇 | 67-63-0 | C3H8O | CC(C)O |
| 盐酸 | 7647-01-0 | HCl | Cl |
| 硫酸 | 7664-93-9 | H2SO4 | OS(O)(=O)=O |
| 氢氧化钠 | 1310-73-2 | NaOH | [Na]O |
| 碳酸钠 | 497-19-8 | Na2CO3 | [Na]OC([O-])=O.[Na+] |
| 氯化钠 | 7647-14-5 | NaCl | [Na]Cl |
| 乙二胺四乙酸(EDTA) | 60-00-4 | C10H16N2O8 | OC(=O)CN(CCN(CC(O)=O)CC(O)=O)CC(O)=O |
此表仅供快速参考。对于不在表中的试剂，agent 应根据化学知识推断或提示用户补充。
完整工作流 Checklist
Task Progress:
- [ ] Step 1: 确认 ak/sk → 生成 AUTH token
- [ ] Step 2: 确认 --addr → 设置 BASE URL
- [ ] Step 3: GET /edge/lab/info → 获取 lab_uuid
- [ ] Step 4: 收集试剂信息（用户提供列表/逐个描述/CSV文件）
- [ ] Step 5: 补全缺失字段（CAS、分子式、SMILES 等）
- [ ] Step 6: 向用户确认待录入的试剂列表
- [ ] Step 7: 循环调用 POST /lab/reagent 逐条录入（每条需含 lab_uuid）
- [ ] Step 8: 汇总结果（成功/失败数量及详情）完整示例
用户说：「帮我录入 3 种试剂：500mL 无水乙醇、1kg 氯化钠、2L 去离子水」
Agent 构建的请求序列：
// 第 1 条
{"lab_uuid": "8511c672-...", "cas": "64-17-5", "name": "无水乙醇", "molecular_formula": "C2H6O", "smiles": "CCO", "stock_in_quantity": 500, "unit": "mL", "supplier": "国药集团", "production_date": "2025-01-01T00:00:00Z", "expiry_date": "2026-01-01T00:00:00Z"}
// 第 2 条
{"lab_uuid": "8511c672-...", "cas": "7647-14-5", "name": "氯化钠", "molecular_formula": "NaCl", "smiles": "[Na]Cl", "stock_in_quantity": 1, "unit": "kg", "supplier": "", "production_date": "2025-01-01T00:00:00Z", "expiry_date": "2026-01-01T00:00:00Z"}
// 第 3 条
{"lab_uuid": "8511c672-...", "cas": "7732-18-3", "name": "去离子水", "molecular_formula": "H2O", "smiles": "O", "stock_in_quantity": 2, "unit": "L", "supplier": "", "production_date": "2025-01-01T00:00:00Z", "expiry_date": "2026-01-01T00:00:00Z"}© deepmodeling, GPL-3.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in .cursor/skills/batch-insert-reagent of deepmodeling/Uni-Lab-OS.
Open the folder on GitHubat commit 43923ec
Compare with similar skills
Batch Insert Reagent 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 |
|---|---|---|---|---|---|---|
| Batch Insert Reagent this skilldeepmodeling/Uni-Lab-OS | 178 | — | ~2k | Automated safety check: Pass | GPL-3.0 | |
| MolecodeAtomFlow-AI/MoleCode | 305 | — | ~1.9k | Automated safety check: Pass | MIT | |
| Drug DiscoveryTommy-yw/RunbookHermes | 546 | 1 repos | ~2.3k | Automated safety check: Pass | MIT | |
| DiffDock Molecular DockingK-Dense-AI/scientific-agent-skills | 48k | 1 repos | ~3k | Automated safety check: Notes | MIT | |
| Biomedical Analysis Dispatchxjtulyc/MedgeClaw | 617 | 1 repos | ~2k | Automated safety check: Pass | None | |
| Edu Chem Reactionwy51ai/edulab | 1.4k | — | ~1.2k | Automated safety check: Pass | Apache-2.0 |
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Filter Workflow By Tags
deepmodeling/Uni-Lab-OS
Query backend workflow list, aggregate all tags, and filter workflows by domain/scenario requirements using tags.
Submit Agent Result
deepmodeling/Uni-Lab-OS
Submit historical experiment results (agentresult) to Uni-Lab cloud platform (leap-lab) notebook — read data files, assemble JSON payload, PUT to cloud API.
Add Device
deepmodeling/Uni-Lab-OS
Guide for adding new devices to Uni-Lab-OS (接入新设备). An agent skill from deepmodeling/Uni-Lab-OS.
Add Resource
deepmodeling/Uni-Lab-OS
Guide for adding new resources (materials, bottles, carriers, decks, warehouses) to Uni-Lab-OS (添加新物料/资源).
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Questions about Batch Insert Reagent
What does Batch Insert Reagent do?
Batch insert reagents into Uni-Lab platform — add chemicals with CAS, SMILES, supplier info. Batch Insert Reagent is an agent skill from deepmodeling/Uni-Lab-OS. Batch insert reagents into Uni-Lab platform — add chemicals with CAS, SMILES, supplier info.
When should I use Batch Insert Reagent?
Batch Insert Reagent fits situations like: the user wants to add reagents; insert chemicals; batch register reagents; mentions 录入试剂/添加试剂/试剂入库/reagent.
How do I install Batch Insert Reagent in Claude Code?
Run `npx skills add deepmodeling/Uni-Lab-OS --skill batch-insert-reagent -a claude-code`. Or copy the skill folder (.cursor/skills/batch-insert-reagent in deepmodeling/Uni-Lab-OS) into .claude/skills/batch-insert-reagent in your project. Claude Code loads it when a task matches its description.
How do I install Batch Insert Reagent in Codex?
Run `npx skills add deepmodeling/Uni-Lab-OS --skill batch-insert-reagent -a codex`. Or copy the skill folder (.cursor/skills/batch-insert-reagent in deepmodeling/Uni-Lab-OS) into .agents/skills/batch-insert-reagent in your project. Codex loads it when a task matches its description.
Can I use Batch Insert Reagent 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 deepmodeling/Uni-Lab-OS --skill batch-insert-reagent -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/batch-insert-reagent, .gemini/skills/batch-insert-reagent, .github/skills/batch-insert-reagent and .opencode/skills/batch-insert-reagent in your project.
What does Batch Insert Reagent need to run?
Going by SKILL.md and its folder, Batch Insert Reagent needs the command-line tools its instructions call (curl and python). Our summary lists: Python 3.
Does Batch Insert Reagent access the network?
SKILL.md names 3 domains. In commands or code: leap-lab.test.bohrium.com, leap-lab.uat.bohrium.com and leap-lab.bohrium.com; the agent is likely to contact these when it follows the instructions. This is read from the text; nothing was executed.
Is Batch Insert Reagent 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. Review the folder before installing.
What licence does Batch Insert Reagent use?
Batch Insert Reagent is published under the GPL-3.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Batch Insert Reagent use?
About 2k tokens (SKILL.md is roughly 8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Batch Insert Reagent?
Skills that share tags, products or a category with Batch Insert Reagent: Molecode (AtomFlow-AI/MoleCode, 305 stars), Drug Discovery (Tommy-yw/RunbookHermes, 546 stars), DiffDock Molecular Docking (K-Dense-AI/scientific-agent-skills, 48k stars) and Biomedical Analysis Dispatch (xjtulyc/MedgeClaw, 617 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Batch Insert Reagent?
deepmodeling (a GitHub organization) maintains it in deepmodeling/Uni-Lab-OS, which has 178 GitHub stars. The repository holds 10 skills in this directory. The repository was last updated on September 24, 2026.
Source: deepmodeling/Uni-Lab-OS on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.