nano-banana-pro-prompts-recommend-skill
AI skill for OpenClaw & Claude Code — recommend from 10000+ Nano Banana Pro (Gemini) image prompts. Smart search by use case, content remix, sample images.
Convert molecules between IUPAC, SMILES, and molecular formula using PubChem as the source of truth. Use this whenever the user asks to convert, normalize, or cross-check molecular representations in chemistry/science workflows (including Intern research tasks). Prefer API lookup over memory; do not guess.
请根据来源仓库和你的 AI 工具说明安装此技能。先阅读技能文件和依赖要求,再添加到工作流。
SkillHub CLI
skillhub install guox18/intern-pubchem-name-conversion打开来源仓库,查看说明和兼容环境后,按来源提供的命令或步骤安装。
将来源链接提供给你的 Agent,让它先读取说明、核对依赖,并向你说明将执行的安装步骤。
Convert one molecular representation into all three fields:
smiles
iupac
formula
Use this skill when the user asks to:
Do not use this skill for:
Expect one input value and one type:
input_type: iupac or smiles
input_value: raw stringIf the user gives only one string without type:
=, #, [, ], @) as smiles
iupac/name queryAlways query PubChem first. Do not answer from memory when tools are available.
ENCODED=$(python3 -c 'import urllib.parse,sys; print(urllib.parse.quote(sys.argv[1], safe=""))' "$INPUT_VALUE")
input_type == iupac:
https://pubchem.ncbi.nlm.nih.gov/rest/pug/compound/name/{ENCODED}/property/SMILES,IUPACName,MolecularFormula/JSON
input_type == smiles:
https://pubchem.ncbi.nlm.nih.gov/rest/pug/compound/smiles/{ENCODED}/property/SMILES,IUPACName,MolecularFormula/JSON
smiles primary endpoint is non-200, retry once with:https://pubchem.ncbi.nlm.nih.gov/rest/pug/compound/fastidentity/smiles/{ENCODED}/property/SMILES,IUPACName,MolecularFormula/JSON
.../compound/name/{ENCODED}/cids/JSON
.../compound/smiles/{ENCODED}/cids/JSON
.../compound/cid/{CID}/property/SMILES,IUPACName,MolecularFormula/JSON
PropertyTable.Properties[0] and map:smiles <- SMILES (fallback ConnectivitySMILES)iupac <- IUPACName
formula <- MolecularFormula
Return JSON only (no markdo...
这些信息来自收录时的来源分析,可能滞后;使用前请核对最新来源文件。
# Intern PubChem Name Conversion
Convert one molecular representation into all three fields:
- `smiles`
- `iupac`
- `formula`
## When to use
Use this skill when the user asks to:
- convert IUPAC <-> SMILES
- fetch molecular formula from IUPAC/SMILES
- validate molecule identity against PubChem
Do not use this skill for:
- reaction mechanism explanation
- quantum chemistry simulation
- docking or property prediction beyond PubChem identifiers
## Input contract
Expect one input value and one type:
- `input_type`: `iupac` or `smiles`
- `input_value`: raw string
If the user gives only one string without type:
- treat strings with many bond symbols (`=`, `#`, `[`, `]`, `@`) as `smiles`
- otherwise treat as `iupac`/name query
## Required behavior
Always query PubChem first. Do not answer from memory when tools are available.
1) URL-encode the full input string:
```bash
ENCODED=$(python3 -c 'import urllib.parse,sys; print(urllib.parse.quote(sys.argv[1], safe=""))' "$INPUT_VALUE")
```
2) Build the primary endpoint:
- If `input_type == iupac`:
- `https://pubchem.ncbi.nlm.nih.gov/rest/pug/compound/name/{ENCODED}/property/SMILES,IUPACName,MolecularFormula/JSON`
- If `input_type == smiles`:
- `https://pubchem.ncbi.nlm.nih.gov/rest/pug/compound/smiles/{ENCODED}/property/SMILES,IUPACName,MolecularFormula/JSON`
3) If `smiles` primary endpoint is non-200, retry once with:
- `https://pubchem.ncbi.nlm.nih.gov/rest/pug/compound/fastidentity/smiles/{ENCODED}/property/SMILES,IUPACName,MolecularFormula/JSON`
4) If still non-200, do CID fallback:
- Resolve CID:
- iupac: `.../compound/name/{ENCODED}/cids/JSON`
- smiles: `.../compound/smiles/{ENCODED}/cids/JSON`
- Then fetch properties by CID:
- `.../compound/cid/{CID}/property/SMILES,IUPACName,MolecularFormula/JSON`
5) Parse `PropertyTable.Properties[0]` and map:
- `smiles <- SMILES` (fallback `ConnectivitySMILES`)
- `iupac <- IUPACName`
- `formula <- MolecularFormula`
## Output format
Return JSON only (no markdo...AI skill for OpenClaw & Claude Code — recommend from 10000+ Nano Banana Pro (Gemini) image prompts. Smart search by use case, content remix, sample images.
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