Agent skill

Binder Design Tool Selection

by BioTender-max in BioTender-max/awesome-bio-agent-skills

Binder design tool selection and workflow routing guidance. An agent skill from BioTender-max/awesome-bio-agent-skills.

MITAuto-check passedResearch & Science

Install Binder Design Tool Selection

skills CLI
$ npx skills add BioTender-max/awesome-bio-agent-skills --skill binder-design-tool-selection -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install BioTender-max/awesome-bio-agent-skills binder-design-tool-selection --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/BioTender-max/awesome-bio-agent-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/bioclaw_hub/binder-design-tool-selection .claude/skills/binder-design-tool-selection && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
binder-design-tool-selection
GitHub stars
199
Token cost
~1.4k tokens
SKILL.md length
381 words
Files
3 (incl. references)
Skills in repo
23
Repo updated
First seen
Licence
MIT

At a glance

Binder design tool selection and workflow routing guidance. An agent skill from BioTender-max/awesome-bio-agent-skills.

  • Works in 6 steps: Target preparation → Hotspot selection → Design with BoltzGen (Recommended) → …
  • Deciding between BoltzGen
  • SKILL.md covers Decision tree, Tool comparison, Recommended Pipeline: BoltzGen… and Number of designs, plus 6 more sections
  • Calls modal

What it does

Binder Design Tool Selection is an agent skill from BioTender-max/awesome-bio-agent-skills. 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 the individual tool skills (boltzgen, bindcraft, rfdiffusion, etc.).

Its SKILL.md is about 1.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files, including reference files (for example `README.md` and `references/tool-comparison.md`).

It sits in Research & Science. The repository describes itself as: A curated collection of AI agent skills for biomedical research, covering genomics, proteomics, single-cell analysis, clinical AI, and protein design. The licence is MIT.

When your agent uses it

  • Deciding between BoltzGen
  • Planning a binder design campaign
  • Understanding trade-offs between different approaches
  • Selecting tools for specific target types

Example prompts

  • “/binder-design-tool-selection”

Workflow steps

6 steps, taken from the step headings in SKILL.md.

  1. Target preparation
  2. Hotspot selection
  3. Design with BoltzGen (Recommended)
  4. Alternative: RFdiffusion Pipeline
  5. Validation
  6. Filtering

What it can do on your machine

Read from SKILL.md and the folder at commit 8cbdd18. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • modal

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Binder Design Tool Selection loads about 1.4k tokens when it runs, and up to ~2.3k if it reads all its reference files. Until then it costs about 104 tokens; SKILL.md has 381 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~104
When it runs · the whole SKILL.md, loaded when a task matches
~1.4k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~2.3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from BioTender-max/awesome-bio-agent-skills at commit 8cbdd18, republished under its MIT licence (© BioTender-max). 381 words, ~1,421 tokens.

Download SKILL.mdSave it as .claude/skills/binder-design-tool-selection/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
binder-design-tool-selection
description
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 the individual tool skills (boltzgen, bindcraft, rfdiffusion, etc.).
license
MIT
category
orchestration
tags
guidance, tool-selection, workflow

Binder Design Tool Selection

Plain-language role: Use this skill to choose the right binder-design-tool-selection method, not to run the design model itself.

Decision tree

De novo binder design?
│
├─ Standard target → BoltzGen (recommended)
│   All-atom output (no separate ProteinMPNN step needed)
│   Better for ligand/small molecule binding
│   Single-step design (backbone + sequence + side chains)
│
├─ Need diversity/exploration → RFdiffusion + ProteinMPNN
│   Maximum backbone diversity
│   Two-step: backbone then sequence
│
├─ Integrated validation → BindCraft
│   Built-in AF2 validation
│   End-to-end pipeline
│
├─ Ligand binding → BoltzGen ✓
│   All-atom diffusion handles ligand context
│
├─ Peptide/nanobody → Germinal
│   VHH/nanobody design
│   Germline-aware optimization
│
└─ Antibody/Nanobody
    +-- VHH design --> germinal skill

Tool comparison

ToolStrengthsWeaknessesBest For
BoltzGenAll-atom, single-step, ligand-awareHigher GPU requirementStandard (recommended)
BindCraftEnd-to-end, built-in AF2 validationLess diverseProduction campaigns
RFdiffusionHigh diversity, fastRequires ProteinMPNNExploration, diversity
GerminalNanobody/VHH designSpecializedAntibody optimization

BoltzGen provides all-atom design with built-in side-chain packing:

Target → BoltzGen → Validate → Filter
 (pdb)  (all-atom)   (chai1-structure-prediction)     (qc)
1. Target preparation
bash
# Fetch structure from PDB
# Use pdb skill for guidance
  • Trim to binding region + 10A buffer
  • Remove waters and ligands
  • Renumber chains if needed
2. Hotspot selection
  • Choose 3-6 exposed residues
  • Prefer charged/aromatic residues
  • Cluster spatially (within 10-15A)

First, create a YAML config file (e.g., binder.yaml):

yaml
entities:
  - protein:
      id: B
      sequence: 70..100

  - file:
      path: target.cif
      include:
        - chain:
            id: A
      binding_types:
        - chain:
            id: A
            binding: 45,67,89

Then run:

bash
modal run modal_boltzgen.py \
  --input-yaml binder.yaml \
  --protocol protein-anything \
  --num-designs 50

Why BoltzGen?

  • All-atom output (no separate ProteinMPNN step needed)
  • Better for ligand/small molecule binding
  • Single-step design (backbone + sequence + side chains)
4. Alternative: RFdiffusion Pipeline

For maximum diversity or when backbone-only is preferred:

bash
# Step 1: Backbone generation
modal run modal_rfdiffusion.py \
  --pdb target.pdb \
  --contigs "A1-150/0 70-100" \
  --hotspot "A45,A67,A89" \
  --num-designs 500

# Step 2: Sequence design
modal run modal_ligandmpnn.py \
  --pdb-path backbone.pdb \
  --num-seq-per-target 16 \
  --sampling-temp 0.1
5. Validation
bash
modal run modal_chai1.py \
  --input-faa sequences.fasta \
  --out-dir predictions/
6. Filtering

Apply standard thresholds:

  • pLDDT > 0.80
  • ipTM > 0.50
  • PAE_interface < 10
  • scRMSD < 2.0 A

See protein-design-qc skill for details.

Number of designs

StageCountPurpose
Backbone generation500-1000Diversity
Sequences per backbone8-16Sequence space
AF2 predictionsAllValidation
After filtering50-200Candidates
Experimental testing10-50Final selection

Common mistakes

Wrong hotspots
  • Using buried residues
  • Too many hotspots (over-constrain)
  • Wrong chain/residue numbers
Insufficient diversity
  • Too few designs generated
  • Low temperature in ProteinMPNN
  • Not exploring multiple backbones
Show full SKILL.md (149 more words)Show less
Poor target preparation
  • Including full protein instead of binding region
  • Missing important structural features
  • Wrong protonation states

Timeline guide

StepCompute Time
RFdiffusion (500 designs)2-4 hours
ProteinMPNN (8000 sequences)1-2 hours
AF2 prediction (8000 sequences)12-24 hours
Filtering and analysis1-2 hours

Total: 1-2 days of compute

Templates and Demo

  • Planning template: templates/binder-design-tool-selection/target-brief.md
  • Minimal walkthrough: examples/minimal-binder-campaign/README.md
  • Example filled brief: examples/minimal-binder-campaign/target-brief.md

Inputs

  • A design objective such as de novo binder generation, ligand binding, or nanobody optimization.
  • Target context including structure availability, hotspot knowledge, and diversity requirements.
  • Compute and timeline constraints that affect tool choice.

Outputs

  • A recommended tool choice or tool combination for the target and campaign goal.
  • A staged workflow covering target preparation, generation, validation, and filtering.
  • Suggested handoffs into skills such as pdb, boltzgen, rfdiffusion, chai1-structure-prediction, and protein-design-qc.

Next Step

Use pdb to prepare the target, then execute the chosen design path with boltzgen, bindcraft, or rfdiffusion.

© BioTender-max, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 2 other files (references) in skills/bioclaw_hub/binder-design-tool-selection of BioTender-max/awesome-bio-agent-skills.

  • SKILL.md
  • README.md
  • references/tool-comparison.md

Open the folder on GitHubat commit 8cbdd18

Compare with similar skills

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Peer Reviewspacering-net/codeg3.9k17 repos~5.9kAutomated safety check: NotesMIT

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Questions about Binder Design Tool Selection

What does Binder Design Tool Selection do?

Binder design tool selection and workflow routing guidance. An agent skill from BioTender-max/awesome-bio-agent-skills. Binder Design Tool Selection is an agent skill from BioTender-max/awesome-bio-agent-skills. Binder design tool selection and workflow routing guidance.

When should I use Binder Design Tool Selection?

Binder Design Tool Selection fits situations like: deciding between BoltzGen; planning a binder design campaign; understanding trade-offs between different approaches; selecting tools for specific target types.

How do I install Binder Design Tool Selection in Claude Code?

Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill binder-design-tool-selection -a claude-code`. Or copy the skill folder (skills/bioclaw_hub/binder-design-tool-selection in BioTender-max/awesome-bio-agent-skills) into .claude/skills/binder-design-tool-selection in your project. Claude Code loads it when a task matches its description.

How do I install Binder Design Tool Selection in Codex?

Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill binder-design-tool-selection -a codex`. Or copy the skill folder (skills/bioclaw_hub/binder-design-tool-selection in BioTender-max/awesome-bio-agent-skills) into .agents/skills/binder-design-tool-selection in your project. Codex loads it when a task matches its description.

Can I use Binder Design Tool Selection in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add BioTender-max/awesome-bio-agent-skills --skill binder-design-tool-selection -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/binder-design-tool-selection, .gemini/skills/binder-design-tool-selection, .github/skills/binder-design-tool-selection and .opencode/skills/binder-design-tool-selection in your project.

What does Binder Design Tool Selection need to run?

Going by SKILL.md and its folder, Binder Design Tool Selection needs the command-line tools its instructions call (modal).

Does Binder Design Tool Selection access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Binder Design Tool Selection safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Binder Design Tool Selection use?

Binder Design Tool Selection is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Binder Design Tool Selection use?

About 1.4k tokens (SKILL.md is roughly 5.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 923 tokens, read only when the agent opens those files.

What are the alternatives to Binder Design Tool Selection?

Skills that share tags, products or a category with Binder Design Tool Selection: Hypothesis Generation (spacering-net/codeg, 3.9k stars), GitHub Deep Research (bytedance/deer-flow, 84k stars), Nature Paper Card (Yuan1z0825/nature-skills, 47k stars) and Content Research Writer (weapp-tailwindcss/weapp-tailwindcss, 1.9k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Binder Design Tool Selection?

BioTender-max (a GitHub user) maintains it in BioTender-max/awesome-bio-agent-skills, which has 199 GitHub stars. The repository holds 23 skills in this directory. The repository was last updated on July 1, 2026.

Source: BioTender-max/awesome-bio-agent-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.