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 agentmods add skills/ma-compbio-lab/skillfoundry/rdkit-molecule-standardizationnpx skills add ma-compbio-lab/SkillFoundry --skill rdkit-molecule-standardizationgit clone --depth 1 https://github.com/ma-compbio-lab/SkillFoundryWrote 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/ma-compbio-lab/skillfoundry/rdkit-molecule-standardization)<a href="https://agentmods.dev/skills/ma-compbio-lab/skillfoundry/rdkit-molecule-standardization"><img src="https://agentmods.dev/badge/skills/ma-compbio-lab/skillfoundry/rdkit-molecule-standardization.svg" alt="Measured on agentmods" 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 | $0.00052 | $0.00590 |
| Opus 5 | $0.00026 | $0.00295 |
| Sonnet 5 | $0.00010 | $0.00118 |
| Haiku 4.5 | $0.00005 | $0.00059 |
Grade A, and why
rdkit-molecule-standardization scanned grade A with 0 findings 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 6d 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 56 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Purpose
Turn a single SMILES string into a deterministic standardization summary using RDKit MolStandardize.
When to use
- You need a local starter for the taxonomy leaf
molecule-standardization. - You want to strip salts or counterions before downstream featurization.
- You want a compact JSON summary with fragment-parent, uncharged, and canonical-tautomer SMILES.
When not to use
- You need conformers, docking, or quantum chemistry.
- You need bulk normalization across large compound libraries.
Inputs
- One SMILES string passed by
--smilesor a single-line file passed by--smiles-file - Optional molecule name
- Optional JSON output path
Outputs
- JSON summary with cleaned, fragment-parent, uncharged, and canonical-tautomer SMILES
- Charge before and after standardization
- Formula and heavy-atom count for the standardized molecule
Requirements
slurm/envs/chem-toolswithRDKitandMolStandardize
Procedure
- Run
slurm/envs/chem-tools/bin/python skills/drug-discovery-and-cheminformatics/rdkit-molecule-standardization/scripts/standardize_rdkit_molecule.py --smiles-file skills/drug-discovery-and-cheminformatics/rdkit-molecule-standardization/examples/sodium_acetate.smiles --name sodium-acetate. - Inspect
fragment_parent_smilesto confirm salt stripping. - Inspect
uncharged_smilesandcanonical_tautomer_smilesbefore reusing the molecule downstream.
Validation
- The script exits successfully with the
chem-toolsprefix. - The sodium acetate example standardizes to
CC(=O)O. - The runtime output matches
assets/sodium_acetate_standardized.json.
Failure modes and fixes
- Invalid SMILES: verify the input string or the first non-empty line in the SMILES file.
- Missing RDKit environment: run the script with
slurm/envs/chem-tools/bin/python.
Safety and limits
- This is a molecule-cleanup helper only.
- It does not imply medicinal-chemistry, ADMET, or synthesis interpretation.
Provenance
- RDKit documentation: https://www.rdkit.org/docs/
- RDKit MolStandardize API: https://www.rdkit.org/docs/source/rdkit.Chem.MolStandardize.rdMolStandardize.html
What ships with it
8 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.
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.
- 6d ago First seen · 56 lines · 52 tokens per session scan A 0def739c4ac7
rdkit-molecule-standardization is a skill published in the GitHub repository ma-compbio-lab/SkillFoundry (38 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 52 tokens to every session and 590 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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