Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/muuuun/luxas/qec-constructnpx skills add Muuuun/luxas --skill qec-constructgit clone --depth 1 https://github.com/Muuuun/luxasWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/muuuun/luxas/qec-construct)<a href="https://agentmods.dev/skills/muuuun/luxas/qec-construct"><img src="https://agentmods.dev/badge/skills/muuuun/luxas/qec-construct.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00148 | $0.01619 |
| Opus 5 | $0.00074 | $0.00809 |
| Sonnet 5 | $0.00030 | $0.00324 |
| Haiku 4.5 | $0.00015 | $0.00162 |
Grade A, and why
qec-construct scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 99 lines — stays where its author put it; the contents beside it link to each section on GitHub.
qec-construct — a QEC verifier-in-the-loop
Routing (brain: read this section, forward the rest)
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):
- Read this file BEFORE writing notes/plan.md.
- Every code-construction/code-search experiment spawn task MUST (a) include the
literal path
skills/qec-construct/SKILL.mdwith the instruction to read it in the Design phase and wrapscripts/qverifyas 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.
The one rule: CONSTRUCT, don't search
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.
The verifier: 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/qverify
What ships with it
8 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- scripts/kernel/ccz_subrank.py 19 KB runs code
- scripts/kernel/cheap_screen.py 7.3 KB runs code
- scripts/kernel/group.py 5.2 KB runs code
- scripts/kernel/tricycle_code.py 5.7 KB runs code
- scripts/kernel/tricycle_distance.py 22 KB runs code
- scripts/kernel/tricycle_stcp.py 14 KB runs code
- scripts/qverify 7.3 KB
- tests/smoke_test.py 4.2 KB runs code
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 5d ago First seen · 99 lines · 148 tokens per session scan A 896ef0ce6234
qec-construct is a skill published in the GitHub repository Muuuun/luxas (956 stars, last pushed today), licensed MIT. It adds 148 tokens to every session and 1,619 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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