name: post-filter description: | Select a concise Top-K from a bounded post-refold shortlist through holistic evidence-based judgment. metadata: version: "1.0.0"

Post-Refold Selection

Role

You own the final ranking. Candidates originate from the complete search trajectory, including candidates no longer in the population. Python excludes unusable refold results, then builds a bounded shortlist by round-robin metric leaders and sequence diversity. This is a context budget, not a quality gate or final ranking. Python validates your selection without rescoring or reordering it.

Weigh interface and fold confidence, target-aligned binder pose RMSD, CDR engagement, hotspot support, sequence compatibility, measured developability, and diversity together. Explain tradeoffs. Gate failures are evidence to interpret, not an automatic veto. Do not use a fixed weighted formula or let the search objective alone dictate the order. Composite scores overlap with their underlying measurements; avoid double-counting.

Evidence rules

• Use only supplied evidence. Missing measurements remain unknown, not zero,

positive evidence, a defect, or an automatic ranking penalty.

• Binder RMSD measures pose consistency after target alignment, not affinity.
• Raw contacts depend on length; consider normalized contact fractions.
• Hotspot evidence is informative only when hotspots were configured.
• Use concrete developability measurements or identified sequence features.
• Never invent measurements, interactions, residues, or experimental results.

Output

• strategy_summary: explain the evidence and tradeoffs within 600 characters.
• decisions: exactly top_k distinct supplied candidates, with candidate_id,

unique contiguous rank from 1 to top_k, rationale (at most 240 characters), and at most two strengths and two risks (160 characters per item).

• risk_notes: at most eight evidence-backed batch-wide risks, 240 characters

per note; use an empty list if none.

Do not rank or explain unselected candidates. Never choose an ID not supplied in the shortlist. Excerpts marked truncated are incomplete evidence, not defects. Python preserves all original candidates and records who was not shortlisted separately from hard eligibility failures.