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 Zhang-Henry/CoEvoSkills --skill evo-molecular-similaritygit clone --depth 1 https://github.com/Zhang-Henry/CoEvoSkillsWrote 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/zhang-henry/coevoskills/evo-molecular-similarity)<a href="https://agentmods.dev/skills/zhang-henry/coevoskills/evo-molecular-similarity"><img src="https://agentmods.dev/badge/skills/zhang-henry/coevoskills/evo-molecular-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/zhang-henry/coevoskills/evo-molecular-similarity"><img src="https://agentmods.dev/badge/skills/zhang-henry/coevoskills/evo-molecular-similarity.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00060 | $0.00672 |
| Opus 5 | $0.00030 | $0.00336 |
| Sonnet 5 | $0.00012 | $0.00134 |
| Haiku 4.5 | $0.00006 | $0.00067 |
Grade A, and why
evo-molecular-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 13d 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 — 72 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Molecular Similarity Skill
Overview
Given a target chemical name and a PDF file listing chemical names (one per line), this skill identifies the top-k most structurally similar chemicals from the PDF pool.
Pipeline:
- Extract chemical names from the PDF using pdfplumber
- Resolve each name to SMILES via PubChemPy at runtime (no manual mapping)
- Compute Morgan fingerprints via RDKit
- Compute pairwise Tanimoto similarity between target and each pool molecule
- Return top-k names sorted by descending similarity, alphabetical tie-breaking
Runtime SMILES lookups are cached to a temp directory keyed by the PDF path hash, so repeated calls avoid redundant API requests. No pre-built mappings are embedded.
End-to-End Usage
import sys
sys.path.insert(0, '/app/environment/skills/evo-molecular-similarity/scripts')
from utils import topk_tanimoto_similarity_molecules
# Example: find top-k similar molecules from any PDF pool
result = topk_tanimoto_similarity_molecules(
target_molecule_name="Benzene", # any chemical name
molecule_pool_filepath="pool.pdf", # path to PDF with one name per line
top_k=5
)
print(result) # list of up to top_k chemical name strings
# Basic validation
assert isinstance(result, list)
assert len(result) <= 5
assert all(isinstance(n, str) for n in result)
Configuration
The fingerprint parameters are set by the task contract:
- radius: 2
- useChirality: True
- nBits: 2048 (RDKit default for bit-vector Morgan)
These are passed as defaults in _compute_morgan_fingerprint() and can be
overridden if a different task contract requires it.
Key Functions
topk_tanimoto_similarity_molecules(target_molecule_name, molecule_pool_filepath, top_k) -> list
End-to-end entry point. Accepts any target name, any PDF path, and any k. Returns a list of chemical names from the PDF pool.
Internal helpers
_extract_molecule_names_from_pdf(pdf_path)— PDF text extraction, one name per line_resolve_name_to_smiles(name)— PubChem lookup with exponential-backoff retry_build_smiles_lookup(names, cache_path)— Cached batch resolution with retry passes_compute_morgan_fingerprint(smiles)— Morgan fingerprint bit-vector_compute_tanimoto(fp1, fp2)— Tanimoto similarity
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.
- 13d ago First seen · 72 lines · 60 tokens per session scan A 9acd30234838
evo-molecular-similarity is a skill published in the GitHub repository Zhang-Henry/CoEvoSkills (66 stars, last pushed 23d ago), licensed Apache-2.0. It adds 60 tokens to every session and 672 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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