vaccine-design-orchestratorUse this skill when the user wants to evaluate a new nanoparticle vaccine candidate, redesign a computational screening workflow, define gate criteria, or pr...
Install via ClawdBot CLI:
clawdbot install barrett-cryptodna/vaccine-design-orchestratorGrade Limited — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Generated May 5, 2026
A biotech startup uses the skill to computationally assess a new lipid nanoparticle vaccine design for influenza, evaluating antigen display, structural stability, and epitope accessibility before committing to wet-lab experiments.
A pharmaceutical company aims to redesign their existing screening pipeline for virus-like particle vaccines, leveraging the skill's default workflow and gate system to increase throughput and reduce false positives.
An academic research group uses the skill to produce a data-driven decision on whether to advance a novel self-assembling protein nanoparticle vaccine candidate to animal studies, based on MD simulation outcomes.
A vaccine developer evaluates a metal-dependent nanoparticle system that requires stability at low pH (stomach), triggering the CpHMD workflow in Level 2 to simulate gastrointestinal transit.
A large pharma company compares the binding free energies of three finalist vaccine candidates using TI/FEP (Level 3) to select the most stable formulation for clinical trials.
Offer the vaccine design orchestrator as a cloud-based subscription service for biotech firms, with tiered pricing based on computational usage and number of projects.
Provide expert services to clients: running the full workflow for their vaccine candidates, delivering Go/Hold/Kill decisions and detailed reports.
Embed the skill into a larger computational drug discovery platform, licensing it to pharma companies as part of a suite of AI tools for vaccine and therapeutic design.
💬 Integration Tip
Integrate via API with existing molecular dynamics (GROMACS) and structure prediction (AF2, ESMFold) pipelines; ensure gate criteria are configurable for different projects.
Scored Apr 19, 2026
Meta-skill for AI agent self-improvement. Analyzes runtime logs to detect error patterns, regressions, and inefficiencies, then generates structured improvem...
Stop waiting for prompts. Keep working.
Turn OpenClaw into a learning-loop agent with seeded workspace rules, skill promotion, reflective memory, and proactive maintenance.
Meta-agent skill for orchestrating complex tasks through autonomous sub-agents. Decomposes macro tasks into subtasks, spawns specialized sub-agents with dynamically generated SKILL.md files, coordinates file-based communication, consolidates results, and dissolves agents upon completion. MANDATORY TRIGGERS: orchestrate, multi-agent, decompose task, spawn agents, sub-agents, parallel agents, agent coordination, task breakdown, meta-agent, agent factory, delegate tasks
Complete toolkit for creating autonomous AI agents and managing Discord channels for OpenClaw. Use when setting up multi-agent systems, creating new agents, or managing Discord channel organization.
Billions decentralized identity for agents. Link agents to human identities using Billions ERC-8004 and Attestation Registries. Verify and generate authentic...