Binder gauntlet: validate and profile designed binders before anyone orders DNA

A structure predictor's interface confidence is the field's standard first filter, and it is only that. This skill is the rest of the computational diligence a protein-engineering or pharma team expects to see next to a table of designed binders: (A) evidence the binding claim survives checks the design loop did not optimise against, with controls; (B) a developability profile of each design; (C) an honest dossier that says what was not checked. It is target-agnostic and tool-agnostic — use whatever predictors and utilities are installed — but names common open tools and literature thresholds (see references/thresholds.md). Budget it explicitly: time one complex prediction per predictor and multiply — A1 for 30 designs × 2 predictors × 3 seeds is ≈180 complex predictions plus the monomer refolds and controls; A6–A9 on 10 leads roughly doubles that; part B is CPU-minutes.

Before you start

• Script: ${CLAUDE_SKILL_DIR}/scripts/sequence_profile.py (standard library only) turns one or many sequences (a FASTA file, or --seq) into Part B's sequence-level table: size, pI and net charge, GRAVY, A280 measurability, cysteines, liability motifs with their positions, hydrophobic and charged windows, candidate protease sites; one row per design, CSV or --json. Run it on the shortlist every round instead of re-deriving the motif rules. First use in a new environment: python3 "${CLAUDE_SKILL_DIR}/scripts/sequence_profile.py" --self-test should end "self-test passed".
• Where to write: a working folder in the user's directory, for example gauntlet/<target>/ with one sub-folder per round. Never write into the skill's folder.
• References: references/thresholds.md (where every pass mark comes from), references/developability-checks.md (how to compute each Part B item), references/dossier-template.md (Part C), references/honest-limits.md (the sentences to use).
• On a cluster: where GPU work is dispatched as Kubernetes or Slurm jobs rather than run in the session, every structure-prediction run in Part A (complex re-predictions, monomer refolds, co-folds, the controls included) goes out as a batch job the way the session submits its other GPU work; Part B, the superpositions and the write-up stay in the session.

Principles

1. Independence. A check only adds evidence if the design loop did not optimise against it. Prefer predictors, seeds and physics terms outside your objective; say which checks are and are not independent.
2. Same pipeline for controls and designs. Every validation protocol is first run on positive and negative controls; report their numbers beside the designs'. A pipeline that cannot separate a known binder from a scrambled sequence is not evidence.
3. Not run ≠ passed. Anything you did not check is listed as not checked, with the reason.
4. Pass/fail only where the literature gives a threshold; otherwise report values against references. There is no validated computational developability gauntlet for miniproteins (antibody rules such as TAP do not transfer); show descriptors, compare to reference proteins if available, do not invent cut-offs.
5. Reject in the open. Candidates dropped on this evidence are part of the deliverable, with the reason.