noir-optimisation SKILL.md skillA

noir-optimisation from sparq-org/sparq is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.

Install it, pinned
mdr add sparq-org/sparq/noir-optimisation@git:20260612.13b231c

Pins git:20260612.13b231c in mdr.lock. Pin the fingerprint instead.

Audit grade
A, 17 of 17 checks passed
Kind
SKILL.md skill
Repository
sparq-org/sparq
Path
.claude/skills/noir-optimisation/SKILL.md
Versions recorded
1
Latest version
git:20260612.13b231c, committed Jun 12, 2026
Size
68,319 bytes
Repository stars
13
License
MIT

Cost model and optimisation reference for Noir circuits on the UltraHonk / Aztec Barretenberg stack. Use when sizing constraint budgets, deciding whether to push work into an `unconstrained` Brillig hint with an in-circuit verifier, comparing Field-arith vs typed `u64` bit operations, reading `bb gates` / `nargo info` / `noir-profiler gates` output, or weighing ACIR-opcode against backend-gate regressions. Companion to `noir-circuit-patterns` — that skill covers SPARQL-primitive shapes; this…

Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.

What the file says

# Noir optimisation — cost model + decision rules

**This is a low-level library; always optimise for minimal gate
count.** Every call site pays the constraint cost on every proof.
Per-site savings of 5-15 gates compound across thousands of call
sites in downstream callers' circuits. Readability is secondary to
constraint count: when the two trade off, take the gates and add a
comment. The only exception is when two forms compile to the same
constraints (the optimiser CSE's identical sub-expressions); in that
case pick whichever reads better.

A reference for someone already writing Noir circuits in this
workspace. Optimisation in Noir is empirical: measure with **`bb gates`**
*before* declaring a win. The 2026-05-03 round-1 of `unconstrained_ops`
for IEEE 754 had us predict an ACIR-opcode + Width win for
`count_leading_zeros_u64_verified`; PR #37 measured **both regressing**
in both isolated and composed regimes, and the follow-up
bit-decomposition spike (`c0f433d`, reverted in `63d0b95`) regressed
twice as hard again. The 2026-05-10 `shr_sticky_u64` Field-arith spike
*looked* like a 17% win on `bb gates` until we discovered the relation
…

Read the whole file at its exact version.

How to install

The exact contents, by fingerprint
mdr add sparq-org/sparq/noir-optimisation@sha256:7af23bb4d8496927

The line at the top of this page pins the label git:20260612.13b231c, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.

Badge

mdr badge

[![mdr](https://markdownregistry.com/badge/art_l555n3yccpuhrelw.svg)](https://markdownregistry.com/a/art_l555n3yccpuhrelw)

4 badge image fetches in 30 days. What the badge shows.

Versions

The registry has recorded 1 version of this file, committed on Jun 12, 2026.

versioncommittedcommitsizeaudit
git:20260612.13b231c latest2026-06-12 13b231c 68,319 BA view

Audit of the latest version

A  17 of 17 checks passed. Fixed automatic checks with no AI involved, so the same checks give the same answer every run.
  • pass: Frontmatter block present
  • pass: Frontmatter declares a name
  • pass: Frontmatter declares a description
  • pass: Size between 200 bytes and 200 KB (68319 bytes)
  • pass: No zero-width or bidi control characters
  • pass: No instruction hidden inside an HTML comment
  • pass: No link to an exfiltration or paste host
  • pass: No credential-shaped string
  • pass: No instruction to send local credentials anywhere
  • pass: No text hidden with inline styles
  • pass: No prompt-injection phrasing
  • pass: No curl or wget piped into a shell
  • pass: No recursive delete of root, home or parent
  • pass: No instruction to read or print local credentials
  • pass: No base64 blob over 200 characters
  • pass: No link to a raw IP address
  • pass: No script tag

Source

GitHub

sparq-org/sparq · 13 stars · license MIT · pushed 2026-10-29 · branch main

API

GET https://markdownregistry.com/api/v1/artifacts/art_l555n3yccpuhrelw
GET https://markdownregistry.com/api/v1/resolve?ref=sparq-org/sparq/noir-optimisation
GET https://markdownregistry.com/api/v1/blob/7af23bb4d8496927e692ccd32cef48f83d78059ca3fb197e2f3781dfc06bed98

Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.

Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.

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