Skill Claude CodeCodex
A design campaign only learns when lab outcomes are joined back to the in-silico predictions that produced them. This skill is the wet-lab feedback loop closer: it ingests lab readouts (Adaptyv batch CSVs, internal ELISA plate-reader output, BLI/Octet kinetics, expression QC), joins them to the per-design feature…
Skill Claude CodeCodex
Closing the design feedback loop requires understanding why designs fail, not just that they fail. This skill compares the distribution of every continuous feature between PASS and FAIL designs using non-parametric statistics, ranks features by discriminating power, and translates the result into concrete threshold or…
Skill Claude CodeCodex
Picking the wrong design strategy on a novel target wastes a GPU day. This skill forces an explicit, structured debate before any compute is spent: three hypothesis agents propose competing strategies in parallel, then a reflection agent ranks them against a fixed rubric. The winner becomes the campaign config.
Skill Claude CodeCodex
Persistent structured memory that turns isolated campaigns into a learning system. Each campaign writes outcomes, top designs, and failure modes into a JSON-backed graph so the next campaign benefits from prior art without re-running compute.
Skill Claude CodeCodex
Thorough target research before design prevents wasted compute and failed campaigns. This skill defines an 8-phase pipeline that retrieves, validates, and packages research findings with quality gates and anti-drift checkpoints at every stage.
Skill Claude CodeCodex
Interpret and apply BY custom scoring metrics for protein and antibody design. This skill covers ipSAE (interface Predicted Structural Accuracy Error) — the primary custom metric that differentiates BY from generic structure prediction tools — along with ipTM, pLDDT, RMSD, liability scoring, and the BY composite…
Skill Claude CodeCodex
Comprehensive screening battery for evaluating protein binder and antibody designs produced by PXDesign and BoltzGen. This skill encodes all quality filters, scoring thresholds, liability checks, and developability assessments used to triage designs before experimental validation.
Skill Claude CodeCodex
Session initialization and configuration for BY projects. This skill defines the full session-start sequence (banner, environment check, status display) and the first-run configuration questionnaire that writes .by/config.json. It is not optional — it runs every time a new session opens in a BY project directory.
Skill Claude CodeCodex
Protenix v1 is an AF3-class structure prediction model (368M parameters) for proteins, complexes, and protein-ligand systems. This skill wraps the protenix CLI with a documented input spec, an input-validating Python entry point, and a multi-seed ensemble aggregator so that callers can drive predictions through…
Skill Claude CodeCodex
You are an expert at designing de novo protein binders using PXDesign. This skill covers YAML config construction, CLI invocation, output parsing, and result interpretation. PXDesign achieves 17–82% pass rate for de novo binder design depending on target difficulty (see references/de-novo-strategy.md).
Plugin Claude Code
Plugin marketplace listing 1 plugin: harness-forge.
Skill Claude CodeCodex
Run one iteration of proteus memory-summary evolution. Called by metaharness.py.
Skill Claude CodeCodex
Run a Meta-Harness-style optimization loop NATIVELY — automatically search over the scaffolding around a FIXED base model (memory, retrieval, context construction, prompt templates, summarization, tool-selection logic) by proposing candidate variants, scoring each on a cheap deterministic eval, and keeping a Pareto…