optimize-littleman-solutions

Audits and optimizes existing ICFPC littleman .man solutions to reduce footprint, ticks, and score.

1|Updated Jul 30, 2026
One-click install
npx skills add https://github.com/d-experts/public-icfpc-2026 --skill optimize-littleman-solutions-d-experts
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: optimize-littleman-solutions
Source: https://github.com/d-experts/public-icfpc-2026/tree/main/member-06/.agents/skills/optimize-littleman-solutions
Command: npx skills add https://github.com/d-experts/public-icfpc-2026 --skill optimize-littleman-solutions-d-experts

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve? It re-audits already-solved ICFPC 2026 littleman problems and systematically shrinks their footprint, average ticks, and overall score without breaking correctness on any public test case. ## Core Features & Use Cases - Solution Auditing: Runs a read-only audit script over all problems//.man files, measuring side, average ticks, and score via the lman CLI to establish trustworthy baselines. - Improvement Prioritization: Ranks optimization opportunities using scoring mode (footprint vs footprint-tick), leaderboard gaps from lman rank, and next-side tick break-even ceilings. - Hypothesis-Driven Optimization: Guides creation of separately named candidate .man files, staged verification with lman check/run/test, and NOTES.md updates only when score genuinely improves. - Use Case: Given a solved problem like triangle with an 8x8 solution, audit all candidates, identify that reducing side by one still wins even with more ticks, build a smaller candidate, and verify all public tests pass before recording the new best. ## Quick Start Use the optimize-littleman-solutions skill to audit all solved problems and optimize the one with the most improvement headroom.

Frequently Asked Questions about optimize-littleman-solutions

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I optimize an existing littleman .man solution?▼

Run the audit script to measure all candidates with lman test, pick the lowest-score all-pass baseline, then form a hypothesis about shrinking the bounding box or reducing ticks. Create a separately named candidate file and verify it with lman check, run, and test before adopting it.

How is the littleman score calculated for optimization?▼

Score equals side squared times average ticks for footprint-tick problems. Reducing side by one wins if average ticks stay below score divided by (side-1) squared, which the audit script reports as the next-side tick ceiling.

Can I overwrite the original best .man file when optimizing?▼

No, the original best .man file must never be overwritten directly. Candidates are created as separate files in the same problems/<slug>/ directory with distinguishing names, and NOTES.md is updated only when a candidate genuinely improves the score.

Does the audit script modify my solution files?▼

No, audit-solutions.mjs is read-only. It enumerates problems/*/*.man files and runs lman test --json for each, outputting a human-readable table or JSON with pass counts, footprint, ticks, and score.

What should I do if no optimization candidate improves the score?▼

Keep the baseline and record failed hypotheses in NOTES.md only when they provide evidence of a lower bound. Delete merely broken candidates and report what was tried and what blocked improvement.