Verify
asgeirtj/system_prompts_leaks
Verify that a code change actually does what it's supposed to by exercising it end-to-end and observing behavior — drive the affected flow, not just tests or typecheck.
Verifier-in-the-loop CONSTRUCTION of quantum error-correcting codes with transversal non-Clifford gates (CCZ/T).
$ npx skills add Muuuun/luxas --skill qec-construct -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install Muuuun/luxas qec-construct --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/Muuuun/luxas.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/qec-construct .claude/skills/qec-construct && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "qec-construct" agent skill from https://github.com/Muuuun/luxas/tree/main/skills/qec-construct into .claude/skills/qec-construct/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "qec-construct", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/Muuuun/luxas/tree/main/skills/qec-constructType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add Muuuun/luxas --skill qec-construct -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install Muuuun/luxas qec-construct --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Muuuun/luxas.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/qec-construct .agents/skills/qec-construct && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "qec-construct" agent skill from https://github.com/Muuuun/luxas/tree/main/skills/qec-construct into .agents/skills/qec-construct/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "qec-construct", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add Muuuun/luxas --skill qec-construct -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install Muuuun/luxas qec-construct --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Muuuun/luxas.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/qec-construct .cursor/skills/qec-construct && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "qec-construct" agent skill from https://github.com/Muuuun/luxas/tree/main/skills/qec-construct into .cursor/skills/qec-construct/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "qec-construct", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/Muuuun/luxas.git --path skills/qec-construct--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add Muuuun/luxas --skill qec-construct -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install Muuuun/luxas qec-construct --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Muuuun/luxas.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/qec-construct .gemini/skills/qec-construct && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "qec-construct" agent skill from https://github.com/Muuuun/luxas/tree/main/skills/qec-construct into .gemini/skills/qec-construct/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "qec-construct", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install Muuuun/luxas qec-constructInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add Muuuun/luxas --skill qec-construct -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/Muuuun/luxas.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/qec-construct .github/skills/qec-construct && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "qec-construct" agent skill from https://github.com/Muuuun/luxas/tree/main/skills/qec-construct into .github/skills/qec-construct/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "qec-construct", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add Muuuun/luxas --skill qec-construct -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install Muuuun/luxas qec-construct --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Muuuun/luxas.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/qec-construct .opencode/skills/qec-construct && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "qec-construct" agent skill from https://github.com/Muuuun/luxas/tree/main/skills/qec-construct into .opencode/skills/qec-construct/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "qec-construct", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
qec-constructVerifier-in-the-loop CONSTRUCTION of quantum error-correcting codes with transversal non-Clifford gates (CCZ/T).
Qec Construct is an agent skill from Muuuun/luxas. Verifier-in-the-loop CONSTRUCTION of quantum error-correcting codes with transversal non-Clifford gates (CCZ/T). Applies whenever the project goal is a new or better code/construction — INCLUDING search-phrased goals ("find codes beating X"), where the construct-loop (propose algebraic rule → qverify → debug) is the REQUIRED mode, replacing blind random/grid sampling (empirically caps far below frontier). Gate certification is currently abelian/CCZ only, validated against the 11 Menon codes; CSS + distance checks…
Its SKILL.md is about 1.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 11 other files, including scripts (for example `scripts/kernel/ccz_subrank.py`, `scripts/kernel/cheap_screen.py` and `scripts/kernel/group.py`).
The repository describes itself as: An autonomous research colleague — from a question to a compiled manuscript, while you sleep. The licence is MIT.
2 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit 9f77cef. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Ships 7 files in scripts/ (Python), which the agent can run.
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Qec Construct loads about 1.6k tokens when it runs. Until then it costs about 173 tokens; SKILL.md has 736 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.
The full file from Muuuun/luxas at commit 9f77cef, republished under its MIT licence (© Muuuun). 736 words, ~1,579 tokens.
.claude/skills/qec-construct/SKILL.md (or your agent's skills folder). This skill also uses 8 other files; get the full folder from GitHub.Applies when RESEARCH.md's goal is a new or improved QEC code / code family / transversal-gate construction — construct, invent, design, discover, improve distance/FOM, and search-phrased variants ("find codes beating X") equally.
Does NOT apply to magic-state cultivation, lattice surgery, decoder, or imaging projects: the gate check is abelian/CCZ-only and those are out of scope regardless of wiring.
Brain's only two obligations (do not run the loop yourself):
skills/qec-construct/SKILL.md with the instruction to read it in
the Design phase and wrap scripts/qverify as a tool, and (b) frame the
experiment as a construct-loop (propose a parametrized ALGEBRAIC construction →
qverify → debug the failure), never as random/grid sampling over supports —
sampling is the mode that capped at FOM ~10.4 vs frontier 45.5.Broad/random/hill-climb search over code supports is a known dead end for this problem (empirically caps far below the frontier; the good codes are rare isolated optima). Your job is to propose a parametrized ALGEBRAIC construction — a group + a generating rule for the supports + (for a new gate) the cup-product / Leibniz conditions — and debug it against the sound verifier, not to sample points and hope.
If you find yourself enumerating random supports, stop: that is the wrong mode.
scripts/qverify (this is your Lean)Call it at high frequency. Input a construction spec (JSON), get a SOUND verdict — including which condition failed, so you can fix it.
echo '{"family":"abelian","group_shape":[3,4,5],
"supp_a":[[0,1,3],[0,3,0],[2,1,3],[2,3,1]],
"supp_b":[[1,1,4],[1,2,2],[2,1,1],[2,2,4]],
"supp_c":[[0,0,4],[2,0,1]],
"frontier_fom":14.4}' | scripts/qverifyWhat it checks, cheapest first:
FOM_upper = k*UB^3/n. If FOM_upper < frontier the code provably can't beat it → reject (never rejects a real winner, since UB ≥ d_Z). Otherwise → promote.partition_a/b/c) — STCP/Leibniz conditions hold? logical CCZ non-trivial? K_CCZ (extractable gates). Abelian path is validated against all 11 published Menon codes."exact":true — sound exact distance via ILP-to-optimality. Only this certifies distance. Run it only on promoted candidates.qverify it (cheap). If css or gate fails → read which condition failed → fix the construction (this is the Menon-style derivation-debug; e.g. the naive cup-product conditions force d=2 — find the offset/structure that escapes it).FOM_upper up while keeping the gate valid."exact":true to certify.A code counts as a new frontier code ONLY if a single qverify run shows:
css_valid ✓, gate.preserves_codespace/stcp_conditions_hold ✓, K_CCZ ≥ 1,
and distance_exact.status == "optimal" with fom_exact strictly above the
frontier. Estimated / biased-sampled / timed-out distances never certify a win.
If you report a win on anything less, it is a hallucination, not a result.
The abelian families are heavily optimized (you will mostly re-find Menon). The
upside is the under-explored non-abelian region ("family":"general",
"group":{"kind":"dihedral","n":..} or {"kind":"perm","generators":[..]}).
The CSS + distance + cheap-screen verifiers ARE general and sound for non-abelian.
But two honest caveats: (1) the non-abelian CCZ gate check is NOT yet implemented
in qverify — so a non-abelian code is CSS/distance-verified but cannot be
gate-CERTIFIED here yet; implementing a group-agnostic direct-circuit
coboundary-invariance check (validated against verify_stcp before ship) is the
open next step. (2) Non-abelian is a high-risk region, not virgin territory:
Tiew2026 already derived non-abelian weight-4 cup-product gate conditions, yet
experts (Tiew, Menon) converged on abelian for deep reasons — the cup product is
graded-commutative (abelian-aligned), and abelian gives Fourier/character analysis,
analytic distance bounds, and hardware locality. Betting on non-abelian bets that
their choice was driven by "harder to analyze" (which this skill's verifiers
bypass) rather than "structurally worse" (which they don't).
This skill gives you a sound, cheap, debuggable verifier and the construct-don't- search discipline. It does not guarantee a better code — proposing the right construction is still the hard part. But it is the machine that lets a construction loop actually converge instead of hallucinating, and it attacks the two real walls: no cheap classical proxy exists for quantum distance (so the screen measures the quantum quantity directly, cheaply, soundly), and the gate-validity that used to be guessed is now checked exactly.
© Muuuun, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 8 other files (scripts) in skills/qec-construct of Muuuun/luxas.
Open the folder on GitHubat commit 9f77cef
Qec Construct next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Qec Construct this skillMuuuun/luxas | 1.2k | — | ~1.6k | Automated safety check: Pass | MIT | |
| Verifyasgeirtj/system_prompts_leaks | 69k | — | ~3k | Automated safety check: Pass | CC0-1.0 | |
| Code Reviewdotnet/maui | 23k | — | ~8.2k | Automated safety check: Pass | MIT | |
| Code Reviewflutter/flutter | 179k | — | ~1.4k | Automated safety check: Pass | BSD-3-Clause | |
| Minimal Code DisciplineYeachan-Heo/oh-my-claudecode | 40k | — | ~746 | Automated safety check: Pass | MIT | |
| Simplify CodeNousResearch/hermes-agent | 252k | — | ~3.7k | Automated safety check: Pass | MIT |
asgeirtj/system_prompts_leaks
Verify that a code change actually does what it's supposed to by exercising it end-to-end and observing behavior — drive the affected flow, not just tests or typecheck.
dotnet/maui
Deep code review of PR or materialized candidate-patch changes for correctness, safety, and MAUI conventions.
flutter/flutter
Performs a comprehensive, multi-step code review of pull requests or local code changes, using iterative refinement (generation, critique, synthesis) to ensure high-quality, actionable feedback.
Yeachan-Heo/oh-my-claudecode
A YAGNI-style checklist for planning and writing code changes: skip what is not needed, reuse what exists and ship the shortest correct diff.
NousResearch/hermes-agent
Parallel 4-agent cleanup of recent code changes. An agent skill from NousResearch/hermes-agent.
shareAI-lab/learn-claude-code
Reviews code against a five-part checklist covering security, correctness, performance, maintainability and testing, and reports findings in a fixed format.
Muuuun/luxas
Hybrid figure pipeline (Nano Banana raster + rembg background removal + TikZ vector assembly).
Muuuun/luxas
Write domain-authentic review articles that synthesize rather than stack.
Muuuun/luxas
Venue-specific formatting requirements for academic journals and conferences across all disciplines.
Muuuun/luxas
Narrative discipline for research reports — article-type templates (empirical / feasibility / comparison / policy-zh) and the feedback revision protocol that keeps outline, prose, and figures…
Muuuun/luxas
Cross-project research memory. An agent skill from Muuuun/luxas.
Muuuun/luxas
Unified academic paper search, citation chains, paper download (arXiv LaTeX/PDF, Sci-Hub), figure extraction from papers, LaTeX source reading, BibTeX fetching, web search, and browser automation…
Verifier-in-the-loop CONSTRUCTION of quantum error-correcting codes with transversal non-Clifford gates (CCZ/T). Qec Construct is an agent skill from Muuuun/luxas. Verifier-in-the-loop CONSTRUCTION of quantum error-correcting codes with transversal non-Clifford gates (CCZ/T).
Run `npx skills add Muuuun/luxas --skill qec-construct -a claude-code`. Or copy the skill folder (skills/qec-construct in Muuuun/luxas) into .claude/skills/qec-construct in your project. Claude Code loads it when a task matches its description.
Run `npx skills add Muuuun/luxas --skill qec-construct -a codex`. Or copy the skill folder (skills/qec-construct in Muuuun/luxas) into .agents/skills/qec-construct in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Muuuun/luxas --skill qec-construct -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/qec-construct, .gemini/skills/qec-construct, .github/skills/qec-construct and .opencode/skills/qec-construct in your project.
Going by SKILL.md and its folder, Qec Construct needs Python for the scripts in its folder. Our summary lists: Python 3.
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
Qec Construct is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 1.6k tokens (SKILL.md is roughly 6.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Qec Construct: Verify (asgeirtj/system_prompts_leaks, 69k stars), Code Review (dotnet/maui, 23k stars), Code Review (flutter/flutter, 179k stars) and Minimal Code Discipline (Yeachan-Heo/oh-my-claudecode, 40k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Muuuun (a GitHub user) maintains it in Muuuun/luxas, which has 1,169 GitHub stars. The repository holds 9 skills in this directory. The repository was last updated on September 6, 2026.
Source: Muuuun/luxas on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.