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 BioTender-max/ProteinClaw --skill iggmgit clone --depth 1 https://github.com/BioTender-max/ProteinClawWrote 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/biotender-max/proteinclaw/iggm)<a href="https://agentmods.dev/skills/biotender-max/proteinclaw/iggm"><img src="https://agentmods.dev/badge/skills/biotender-max/proteinclaw/iggm.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 | $0.00127 | $0.01095 |
| Opus 5 | $0.00063 | $0.00548 |
| Sonnet 5 | $0.00025 | $0.00219 |
| Haiku 4.5 | $0.00013 | $0.00110 |
Grade A, and why
iggm 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 7d 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.
The source is not reproduced here
No licence file
A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.
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.
- 7d ago First seen · 133 lines · 127 tokens per session scan A 9976da7d6b5b
iggm is a skill published in the GitHub repository BioTender-max/ProteinClaw (11 stars, last pushed 6mo ago), with no licence file. It adds 127 tokens to every session and 1,095 once invoked, about $0.0006 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.
Other skills, from other repositories
antibody-design-iggm
Antibody design using IgGM model. Use this skill when: (1) Epitope-conditioned de novo antibody design, (2) Antibody affinity maturation, (3) Using antigen PDB structure and epitope information. For binding affinity evaluation, use prodigy.
germinal
De novo antibody and nanobody (VHH) design with Germinal. Use this skill when: (1) Designing epitope-targeted nanobodies or scFvs, (2) Needing CDR design on a fixed framework, (3) Working on antibody-format binders rather than miniproteins. For miniprotein binders, use binder-design (BoltzGen, BindCraft, RFdiffusion…
antibody-structure-prediction-tfold
Antibody-related structure prediction using tfold model. Use this skill when: (1) Predict antibody and nanobody structure of a given sequence, (2) Predict antigen-antibody complex structure of given sequences, (3) Using local GPU resources. For binding affinity evaluation, use prodigy.
protein-structure-design-boltzgen
All-atom protein design using BoltzGen diffusion model. Use this skill when: (1) Need side-chain aware design from the start, (2) Designing around small molecules or ligands, (3) Want all-atom diffusion (not just backbone), (4) Require precise binding geometries, (5) Using YAML-based configuration. For structure…
boltzgen
All-atom protein design using BoltzGen diffusion model. Use this skill when: (1) Need side-chain aware design from the start, (2) Designing around small molecules or ligands, (3) Want all-atom diffusion (not just backbone), (4) Require precise binding geometries, (5) Using YAML-based configuration. For backbone-only…
esm
ESM protein language models for embeddings, sequence scoring, structure prediction, and binder design. Use this skill when: (1) Computing pseudo-log-likelihood (PLL) or mutation-effect scores, (2) Getting protein embeddings for clustering or filtering, (3) Predicting complex structures with ESMFold2, (4) Designing…