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 structural-alignmentgit 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/structural-alignment)<a href="https://agentmods.dev/skills/gptomics/bioskills/structural-alignment"><img src="https://agentmods.dev/badge/skills/gptomics/bioskills/structural-alignment/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/structural-alignment"><img src="https://agentmods.dev/badge/skills/gptomics/bioskills/structural-alignment.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 | $0.00102 | $0.06081 |
| Opus 5.5 | $0.00041 | $0.02432 |
| Sonnet 5.5 | $0.00020 | $0.01216 |
| Haiku 4.5 | $0.00010 | $0.00608 |
Grade A, and why
bio-alignment-structural 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 1mo 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-alignment-structural — 98% identical, 12 lines differ
How it starts
The opening of the file, as written. The whole thing — 331 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Version Compatibility
Reference examples tested with: Foldseek 8+, TM-align 20220412+, US-align 20231222+, Foldmason 1+, BioPython 1.83+, pymol-open-source 3.0+
Before using code patterns, verify installed versions match. If versions differ:
- CLI:
foldseek --version,TMalign,USalign,foldmason --version - Python:
pip show <package>thenhelp(module.function)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.
Structural Alignment
"Align two protein structures" -> Compute backbone-aware superposition and a fold-similarity score (TM-score, RMSD, or LDDT).
- CLI pairwise:
TMalign A.pdb B.pdb,USalign A.pdb B.pdb - CLI search at scale:
foldseek easy-search query/ AFDB result.m8 tmp/ - CLI structural MSA:
foldmason easy-msa structures/*.pdb out tmp/ - Python pairwise:
Bio.PDB.Superimposer, orsubprocesswrappingTMalign/USalign(seeexamples/tm_align_pairwise.py) - GUI / scripted molecular-graphics superposition: ChimeraX
matchmaker, PyMOLsuper/cealign
"Find structural homologs of an AlphaFold model" -> Search a structure database by 3Di-encoded structural alphabet (Foldseek) or by full TM-align rotation (DALI, US-align).
When to Use Structural Alignment
| Sequence identity | Recommended approach |
|---|---|
| >= 40% | Sequence DP (Bio.Align, BLASTP) is sufficient |
| 25-40% | Sensitive sequence (MMseqs2, jackhmmer, profile-profile HHsearch) |
| 15-25% | Profile-profile (HHsearch) OR Foldseek if structures available |
| < 15% (dark proteome / twilight zone) | Foldseek (3Di), TM-align, US-align, pLM aligners |
Sequence alignment below 15% identity is statistically indistinguishable from random pairings. The exact twilight-zone cutoff is length-dependent: Rost 1999 (Prot Eng) showed the curve drops to 25% at length 80, 20% at length 250 -- short alignments need higher identity for the same statistical signal, so a 15-25% rule of thumb is shorthand for "twilight zone for proteins of typical domain size (~150-300 residues)". If reasonable structural models exist (PDB, AlphaFoldDB, ESMFold), structural alignment is far more reliable in this regime.
What ships with it
5 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.
- 1mo ago First seen · 331 lines · 102 tokens per session scan A 5053d6163e1f
bio-alignment-structural is a skill published in the GitHub repository GPTomics/bioSkills (1,223 stars, last pushed 2mo ago), licensed MIT. It adds 102 tokens to every session and 6,081 once invoked, about $0.0004 per session on Opus 5.5. 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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