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 skills add Kdevos12/ALKYL --skill rdkitgit clone --depth 1 https://github.com/Kdevos12/ALKYLWrote 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/kdevos12/alkyl/rdkit)<a href="https://agentmods.dev/skills/kdevos12/alkyl/rdkit"><img src="https://agentmods.dev/badge/skills/kdevos12/alkyl/rdkit/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/kdevos12/alkyl/rdkit"><img src="https://agentmods.dev/badge/skills/kdevos12/alkyl/rdkit.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00058 | $0.01151 |
| Opus 5.5 | $0.00023 | $0.00460 |
| Sonnet 5.5 | $0.00012 | $0.00230 |
| Haiku 4.5 | $0.00006 | $0.00115 |
Grade A, and why
rdkit 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 1mo 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 — 97 lines — stays where its author put it; the contents beside it link to each section on GitHub.
RDKit
The primary Python library for cheminformatics. Molecular manipulation, descriptors, fingerprints, 3D generation, reactions, and more.
When to Use This Skill
- Reading/writing molecules from SMILES, SDF, MOL, PDB files
- Calculating molecular properties and drug-likeness filters (Ro5, QED)
- Computing and comparing molecular fingerprints (Morgan/ECFP, MACCS, RDKit FP)
- Generating 3D conformers (ETKDG, MMFF, UFF)
- Substructure searching and SMARTS queries
- Maximum Common Substructure (MCS) analysis
- Chemical reactions via SMARTS or RXN files
- Molecular fragmentation (BRICS, RECAP, Murcko scaffolds)
- Stereochemistry assignment and analysis
- Tautomer enumeration and molecule standardization
- Molecular visualization (2D SVG/PNG, similarity maps)
Quick Start
from rdkit import Chem
from rdkit.Chem import AllChem, Descriptors, Draw, rdMolDescriptors
# Load molecule
mol = Chem.MolFromSmiles('CC(=O)Oc1ccccc1C(=O)O') # aspirin
# Basic properties
print(Descriptors.MolWt(mol)) # 180.16
print(Descriptors.MolLogP(mol)) # 1.31
print(rdMolDescriptors.CalcNumHBD(mol)) # 1
print(rdMolDescriptors.CalcNumHBA(mol)) # 4
print(rdMolDescriptors.CalcTPSA(mol)) # 63.6
# Morgan fingerprint (ECFP4-like)
fpgen = AllChem.GetMorganGenerator(radius=2)
fp = fpgen.GetFingerprint(mol)
# 2D image
img = Draw.MolToImage(mol, size=(300, 200))
Router — What to Read
| Task | Reference |
|---|---|
| SMILES, SDF, MOL, PDB, SMARTS I/O, serialization | references/io-molecules.md |
| Descriptors, Lipinski Ro5, QED, ADME, drug filters | references/properties-descriptors.md |
| Morgan, MACCS, RDKit FP, atom pair, similarity, diversity | references/fingerprints-similarity.md |
| 3D conformers (ETKDG), MMFF/UFF optimization, 3D descriptors | references/3d-conformers.md |
| Reactions (SMARTS), BRICS, RECAP, Murcko, tautomers, standardization | references/transformations.md |
| Substructure search (SMARTS), MCS, rings, stereochemistry, pharmacophores | references/analysis-search.md |
| Visualization: SVG/PNG, highlighting, similarity maps, grids | references/visualization.md |
What ships with it
7 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.
- 1mo ago First seen · 97 lines · 58 tokens per session scan A 3c1e9e5c3069
rdkit is a skill published in the GitHub repository Kdevos12/ALKYL (7 stars, last pushed 7mo ago), licensed MIT. It adds 58 tokens to every session and 1,151 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-08-31.
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