medchem
by K-Dense-AImedchem is a medicinal chemistry filtering skill for Scientific workflows. Use it to apply Lipinski, Veber, PAINS, structural alerts, and complexity metrics for compound prioritization, library cleanup, lead optimization, and compound quality review.
This skill scores 84/100 and is worth listing. It gives directory users a clear install/use case for medicinal chemistry filtering, with explicit triggers, a real installation command, and substantial workflow content that should help agents act with less guesswork than a generic prompt.
- Clear, practical trigger scope for drug-likeness filtering, PAINS/structural alerts, and compound prioritization.
- Strong operational detail: frontmatter is valid, the body is substantial, and the page includes a direct install command (`uv pip install medchem`).
- Multiple concrete workflow sections and rule lists make it easier for an agent to choose the right medicinal chemistry checks quickly.
- No support files, references, or scripts were provided, so users must trust the documentation without extra validation or examples beyond the main skill file.
- The skill is Python-library oriented; non-Python agents or users needing richer automation scaffolding may need to adapt it manually.
Overview of medchem skill
What the medchem skill does
medchem is a medicinal chemistry filtering skill for prioritizing compounds in drug discovery. It helps you apply rule-based checks such as Lipinski, Veber, PAINS, structural alerts, and complexity metrics so you can triage large libraries faster and with less manual review.
Who it is for
This medchem skill is best for scientific users working on hit triage, lead optimization, library cleanup, or compound quality review. If you need a practical way to separate promising molecules from risky ones, medchem for Scientific workflows is a strong fit.
Why people install it
The main reason to install medchem is decision support: it turns a rough compound set into a more defensible shortlist. It is especially useful when you want consistent filtering rules, scalable batch screening, and a way to explain why a molecule was flagged.
How to Use medchem skill
medchem install and first check
Install the medchem skill with:
uv pip install medchem
Before using it in a workflow, read SKILL.md first to confirm the supported rule families and input patterns. Since the repository is lightweight and does not include extra support folders, the skill file is the primary source of truth.
Turn a vague goal into usable input
The medchem usage pattern works best when you specify three things: the molecule format, the decision goal, and the filter strictness. For example, instead of asking for “compound filtering,” ask for “screen these SMILES for Lipinski, PAINS, and structural alerts, then return pass/fail plus reasons.”
Practical workflow for best results
Use medchem when you already know the filtering question you want answered. A good workflow is: normalize your molecules, choose the relevant rule set, run the filters, then review borderline compounds separately rather than discarding them automatically. That matters because medchem rules are guidelines, not absolute truth.
Files to read first
Start with SKILL.md, then inspect the sections on installation, when to use the skill, and core capabilities. If you are adapting the logic into a larger pipeline, map the rule names and filter types to your own assay, library, or property constraints before running batch jobs.
medchem skill FAQ
Is medchem only for drug-likeness filtering?
No. The medchem skill also covers structural alerts, PAINS-style screening, prioritization, and complexity-related checks. If your task is broader medicinal chemistry triage, it can still be useful.
Do I need this instead of a normal prompt?
Use a normal prompt if you just want a quick conceptual explanation. Install medchem when you need a repeatable, rule-driven workflow for Scientific compound filtering with fewer interpretation errors.
Is medchem beginner-friendly?
Yes, if you can provide SMILES or another clear molecule representation and you know what outcome you want. It is less beginner-friendly when the input set is messy, unlabeled, or missing the property context needed to choose the right filters.
When should I not use medchem?
Do not rely on medchem alone for final go/no-go decisions. It is a screening and prioritization tool, so it should be paired with assay data, target context, and medicinal chemistry judgment.
How to Improve medchem skill
Give the skill a sharper screening brief
The strongest medchem outputs come from inputs that name the rule families, the molecule format, and the decision threshold. For example: “Screen these 2,000 SMILES for Rule of Five, Veber, and PAINS; flag failures with reasons; keep borderline cases separate.”
Provide context that changes the filter choice
If you are working on CNS, oral, fragment-like, or lead-like compounds, say so up front. That context changes whether the medchem skill should emphasize Lipinski-style rules, leadlike constraints, or more specialized medicinal chemistry filters.
Ask for reasons, not just labels
A pass/fail list is less useful than a labeled output with the rule triggered, the structural alert, and the compound identifier. Asking for reasons makes medchem easier to audit and easier to refine in the next pass.
Iterate on false positives and false negatives
After the first run, inspect compounds that were unexpectedly flagged or missed, then tighten the prompt around those edge cases. That feedback loop is the fastest way to make medchem more useful for your specific library and screening policy.