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 OpenLAIR/OpenSkill --skill evo-molecule-similaritygit clone --depth 1 https://github.com/OpenLAIR/OpenSkillWrote 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/openlair/openskill/evo-molecule-similarity)<a href="https://agentmods.dev/skills/openlair/openskill/evo-molecule-similarity"><img src="https://agentmods.dev/badge/skills/openlair/openskill/evo-molecule-similarity/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/openlair/openskill/evo-molecule-similarity"><img src="https://agentmods.dev/badge/skills/openlair/openskill/evo-molecule-similarity.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 | $0.00000 | $0.00561 |
| Opus 5 | $0.00000 | $0.00280 |
| Sonnet 5 | $0.00000 | $0.00112 |
| Haiku 4.5 | $0.00000 | $0.00056 |
Grade A, and why
evo-molecule-similarity 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 today.
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 — 67 lines — stays where its author put it; the contents beside it link to each section on GitHub.
evo-molecule-similarity
Description
Find top-k similar chemicals from a PDF molecule pool using Morgan fingerprints with Tanimoto similarity. Converts chemical names to SMILES via PubChemPy, computes Morgan fingerprints (radius=2, chirality=True), and ranks by Tanimoto similarity with alphabetical tie-breaking.
Key Concepts
- PDF Extraction: Uses pdfplumber to extract chemical names (one per line)
- Name-to-SMILES: Uses PubChemPy (external resource, no manual mapping)
- Morgan Fingerprints: radius=2, useChirality=True, default 2048 bits
- Tanimoto Similarity: Standard similarity metric for molecular fingerprints
- Sorting: Descending by similarity, alphabetical for ties
Dependencies
- pdfplumber (PDF text extraction)
- pubchempy (chemical name to SMILES conversion)
- rdkit (fingerprints and similarity)
Usage
import sys
sys.path.insert(0, '/app/environment/skills/evo-molecule-similarity/scripts')
from utils import (
topk_tanimoto_similarity_molecules,
extract_molecule_names,
name_to_smiles,
smiles_to_fingerprint,
compute_tanimoto_similarity
)
# Main function - find top k similar molecules
results = topk_tanimoto_similarity_molecules(
target_molecule_name='Aspirin',
molecule_pool_filepath='/root/molecules.pdf',
top_k=5
)
print(results)
# ['Acetylsalicylic acid', 'Aspirin', 'Methyl 2-acetoxybenzoate', ...]
Function Reference
topk_tanimoto_similarity_molecules(target_molecule_name, molecule_pool_filepath, top_k) -> list
Main entry point. Returns list of top-k molecule names sorted by descending Tanimoto similarity, alphabetical for ties.
extract_molecule_names(filepath) -> list
Extract chemical names from PDF file (one per line).
name_to_smiles(name) -> str or None
Convert chemical name to canonical SMILES via PubChemPy.
smiles_to_fingerprint(smiles) -> fingerprint or None
Convert SMILES to Morgan fingerprint (radius=2, chirality=True).
compute_tanimoto_similarity(fp1, fp2) -> float
Compute Tanimoto similarity between two fingerprints.
What ships with it
1 file 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.
- today First seen · 67 lines · 0 tokens per session scan A dc23a1a74a1d
evo-molecule-similarity is a skill published in the GitHub repository OpenLAIR/OpenSkill (88 stars, last pushed yesterday), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 561 tokens. 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 2026-09-11.
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