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 GPTomics/bioSkills --skill substructure-searchgit clone --depth 1 https://github.com/GPTomics/bioSkillsWrote 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/gptomics/bioskills/substructure-search)<a href="https://agentmods.dev/skills/gptomics/bioskills/substructure-search"><img src="https://agentmods.dev/badge/skills/gptomics/bioskills/substructure-search/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/gptomics/bioskills/substructure-search"><img src="https://agentmods.dev/badge/skills/gptomics/bioskills/substructure-search.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 | $0.00079 | $0.04751 |
| Opus 5 | $0.00039 | $0.02375 |
| Sonnet 5 | $0.00016 | $0.00950 |
| Haiku 4.5 | $0.00008 | $0.00475 |
Grade A, and why
bio-substructure-search 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 6d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- bio-substructure-search — 97% identical, 12 lines differ
How it starts
The opening of the file, as written. The whole thing — 334 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Version Compatibility
Reference examples tested with: RDKit 2024.09+. SMARTS dialect follows Daylight specification with RDKit extensions.
Before using code patterns, verify installed versions match. If versions differ:
- Python:
pip show rdkitthenhelp(rdkit.Chem.MolFromSmarts)to check signatures
If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying.
Substructure Search
Search molecular collections for structural patterns using SMARTS. The choice of SMARTS dialect, atom/bond matching mode, and structural-alert catalog determines whether the search is correctly capturing the intended chemistry. PAINS (Baell & Holloway 2010) is the most-cited but most-misunderstood filter -- it identifies patterns of assay interference, not "bad molecules". Knowing when to apply each catalog and how to interpret hits is essential.
For SMARTS-based reactions (transforming matched substructures), see chemoinformatics/reaction-enumeration. For 3D pharmacophore matching, see chemoinformatics/pharmacophore-modeling.
SMARTS Grammar Essentials
| Token | Meaning | Example |
|---|---|---|
[#6] |
Atom by atomic number | [#6] carbon (any hybridization) |
c |
Lowercase = aromatic | c1ccccc1 benzene aromatic |
C |
Uppercase = aliphatic only | C(=O)O carboxylic acid carbon |
[CX4] |
Atom + connection count X | [CX4] sp3 carbon (4 connections) |
[CX3]=O |
Carbonyl (CX3 = sp2 with 3 bonds) | matches ketone, aldehyde, ester C |
[#6;R] |
Atom in ring | [#6;R] ring carbon |
[#6;!R] |
Atom not in ring | [#6;!R] acyclic carbon |
[#6;r6] |
Atom in 6-membered ring | [#6;r6] six-ring carbon |
[a] |
Any aromatic atom | [a] |
[!#1] |
Anything except H | [!#1] heavy atom |
[N;H2] |
N with exactly 2 H; neighboring chemistry unconstrained | [NH2] also matches non-amine NH2 environments unless context is added |
[N+] |
Positively charged N | [N+](=O)[O-] nitro |
[$(...)] |
Recursive SMARTS | [$(c1ccccc1)] aromatic 6-ring atom |
[c]([F,Cl,Br,I]) |
OR within brackets | aryl halide |
~ |
Any bond type | c~c any aromatic-aromatic bond |
@ |
Ring bond | c@c requires the matched bond to be in a ring |
- |
Single bond explicit | C-C |
= |
Double bond | C=O |
: |
Aromatic bond explicit |
What ships with it
2 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.
- 6d ago First seen · 334 lines · 79 tokens per session scan A 325555538c6d
bio-substructure-search is a skill published in the GitHub repository GPTomics/bioSkills (1,199 stars, last pushed 25d ago), licensed MIT. It adds 79 tokens to every session and 4,751 once invoked, about $0.0004 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 2026-09-03.
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