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 ma-compbio-lab/SkillFoundry --skill rdkit-scaffold-analysis-startergit 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-scaffold-analysis-starter)<a href="https://agentmods.dev/skills/ma-compbio-lab/skillfoundry/rdkit-scaffold-analysis-starter"><img src="https://agentmods.dev/badge/skills/ma-compbio-lab/skillfoundry/rdkit-scaffold-analysis-starter.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 | $0.00041 | $0.00543 |
| Opus 5 | $0.00020 | $0.00271 |
| Sonnet 5 | $0.00008 | $0.00109 |
| Haiku 4.5 | $0.00004 | $0.00054 |
Grade A, and why
rdkit-scaffold-analysis-starter 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 8d 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 — 54 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Purpose
Analyze a small local TSV of SMILES strings with RDKit Murcko scaffolds and emit a compact JSON summary that can feed later smoke integration or scaffold triage workflows.
When to use
- You need a local scaffold grouping summary for a small curated molecule set.
- You want canonical SMILES, Murcko scaffolds, generic scaffolds, and group counts from one deterministic run.
When not to use
- You need large library clustering, matched molecular pair analysis, or SAR interpretation.
- You need remote compound lookup or medicinal-chemistry recommendations.
Inputs
- A TSV file with columns
nameandsmiles - Optional JSON output path
Outputs
- JSON with per-molecule canonical SMILES, Murcko scaffold, generic scaffold, scaffold groups, generic scaffold groups, and summary counts
Requirements
slurm/envs/chem-tools/bin/python- RDKit available in that environment
Procedure
- Inspect
examples/molecules.tsv. - Run
slurm/envs/chem-tools/bin/python skills/drug-discovery-and-cheminformatics/rdkit-scaffold-analysis-starter/scripts/run_rdkit_scaffold_analysis.py --input skills/drug-discovery-and-cheminformatics/rdkit-scaffold-analysis-starter/examples/molecules.tsv. - Review
molecules,scaffold_groups, andsummary.
Validation
- The bundled example returns at least one scaffold group with count
>= 2. - Invalid SMILES input returns a non-zero exit code with a clear error message.
Failure modes and fixes
- Invalid SMILES: fix the offending row in the input TSV.
- Missing RDKit environment: rerun with
slurm/envs/chem-tools/bin/python. - Missing
nameorsmilescolumns: use a header row with exactly those field names.
Safety and limits
- Local scaffold computation only.
- No medicinal-chemistry conclusions are implied by the grouping.
Provenance
- RDKit docs: https://www.rdkit.org/docs/index.html
- RDKit Murcko scaffold API: https://www.rdkit.org/docs/source/rdkit.Chem.Scaffolds.MurckoScaffold.html
- RDKit repository: https://github.com/rdkit/rdkit
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.
- 8d ago First seen · 54 lines · 41 tokens per session scan A d7c195fb2348
rdkit-scaffold-analysis-starter is a skill published in the GitHub repository ma-compbio-lab/SkillFoundry (38 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 41 tokens to every session and 543 once invoked, about $0.0002 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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