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 adaptyvbio/protein-design-skills --skill binder-designgit clone --depth 1 https://github.com/adaptyvbio/protein-design-skillsWrote 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/adaptyvbio/protein-design-skills/binder-design)<a href="https://agentmods.dev/skills/adaptyvbio/protein-design-skills/binder-design"><img src="https://agentmods.dev/badge/skills/adaptyvbio/protein-design-skills/binder-design/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/adaptyvbio/protein-design-skills/binder-design"><img src="https://agentmods.dev/badge/skills/adaptyvbio/protein-design-skills/binder-design.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 | $0.00091 | $0.01934 |
| Opus 5 | $0.00046 | $0.00967 |
| Sonnet 5 | $0.00018 | $0.00387 |
| Haiku 4.5 | $0.00009 | $0.00193 |
Grade A, and why
binder-design 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 11d 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 — 227 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Binder Design Tool Selection
Which tool wins
No single tool is best for every target. Hit-rate is strongly target-dependent, so choose by target type, what you want to control, and available compute.
The clearest signal comes from head-to-head competitions where many methods design against the same target. On the Adaptyv Nipah de novo target, the public results show:
| Method | Tested | Binders | Hit-rate |
|---|---|---|---|
| Mosaic (gradient, multi-model) | 9 | 8 | 89% |
| ProteinMPNN hybrid | 28 | 7 | 25% |
| RFdiffusion | 60 | 13 | 22% |
| BindCraft | 98 | 7 | 7% |
| BoltzGen | 182 | 6 | 3% |
Mosaic had the highest hit-rate here, but on a small, expert-tuned sample. The ranking shifts on other targets, and that target-dependence is true of every method (BoltzGen, Boltz, BindCraft, Mosaic). You cannot know a priori which will win on a new target, so this is not a fixed leaderboard.
Because of that, choose a starting point by cost and effort to a binder, not by assuming a method has the best hit-rate. BoltzGen is the suggested default because it is turnkey and all-atom, so it gets you testable designs fastest with the least setup. Mosaic is the high-ceiling option when you can invest time tuning the objective. On a hard or important target, running more than one method in parallel is reasonable.
De novo binder design?
│
├─ Lowest cost/effort to testable designs → BoltzGen (default)
├─ Hard/important target, can invest tuning → Mosaic (gradient, multi-model)
├─ Ligand / small-molecule binding → BoltzGen (all-atom)
├─ Diversity / exploration → RFdiffusion + ProteinMPNN
├─ End-to-end with built-in validation → BindCraft
└─ Antibody / nanobody (VHH) → germinal skill (also mber, iggm in biomodals)
Tool comparison
| Tool | Strengths | Weaknesses | Best for |
|---|---|---|---|
| BoltzGen | All-atom, single-step, turnkey | One model in the loop; mid-range cost per design | Lowest-effort default, ligand binding |
| Mosaic | Composable multi-model objective, won hard head-to-heads | Needs tuning, local JAX only | Hard or important targets, expert use |
| BindCraft | End-to-end, built-in AF2 validation | Less diverse | Production campaigns |
| RFdiffusion | High diversity | Requires ProteinMPNN; not in biomodals | Exploration, diversity |
| Germinal | Antibody and nanobody formats | Finicky | scFv / VHH design |
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.
- 11d ago First seen · 227 lines · 91 tokens per session scan A aad5d1b98446
binder-design is a skill published in the GitHub repository adaptyvbio/protein-design-skills (158 stars, last pushed 3mo ago), licensed MIT. It adds 91 tokens to every session and 1,934 once invoked, about $0.0005 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
binder-design
Guidance for choosing the right protein binder design tool. Use this skill when: (1) Deciding between BoltzGen, BindCraft, or RFdiffusion, (2) Planning a binder design campaign, (3) Understanding trade-offs between different approaches, (4) Selecting tools for specific target types. For specific tool parameters, use…
binder-design-tool-selection
Binder design tool selection and workflow routing guidance. Use this skill when: (1) Deciding between BoltzGen, BindCraft, or RFdiffusion, (2) Planning a binder design campaign, (3) Understanding trade-offs between different approaches, (4) Selecting tools for specific target types. For specific tool parameters, use…
binder-design-tool-selection
Binder design tool selection and workflow routing guidance. Use this skill when: (1) Deciding between BoltzGen, BindCraft, or RFdiffusion, (2) Planning a binder design campaign, (3) Understanding trade-offs between different approaches, (4) Selecting tools for specific target types. For specific tool parameters, use…
binder-design
Guidance for choosing the right protein binder design tool. Use this skill when: (1) Deciding between BoltzGen, BindCraft, or RFdiffusion, (2) Planning a binder design campaign, (3) Understanding trade-offs between different approaches, (4) Selecting tools for specific target types. For specific tool parameters, use…
binder-design
Guidance for choosing the right protein binder design tool. Use this skill when: (1) Deciding between BoltzGen, BindCraft, or RFdiffusion, (2) Planning a binder design campaign, (3) Understanding trade-offs between different approaches, (4) Selecting tools for specific target types. For specific tool parameters, use…
binder-design
Guidance for choosing the right protein binder design tool. Use this skill when: (1) Deciding between BoltzGen or BindCraft, (2) Planning a binder design campaign, (3) Understanding trade-offs between different approaches, (4) Selecting tools for specific target types.