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noir-optimize-acir

Optimizes Noir programs by measuring ACIR circuit size and opcode counts through benchmarking and recompilation.

Install

mkdir -p .claude/skills/noir-optimize-acir && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/3059" && unzip -o skill.zip -d .claude/skills/noir-optimize-acir && rm skill.zip

Installs to .claude/skills/noir-optimize-acir

Activation

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Workflow for measuring and optimizing the ACIR circuit size of a constrained Noir program. Use when asked to optimize a Noir program's gate count or circuit size.
162 chars✓ has a “when” trigger
Intermediate

Key capabilities

  • Measure ACIR circuit gate count
  • Benchmark proving time
  • Analyze ACIR opcodes
  • Optimize circuit size
  • Export library function circuits

How it works

It uses nargo to compile programs and the bb CLI to measure gate counts, allowing for iterative optimization based on circuit size metrics.

Inputs & outputs

You give it
Noir source code
You get back
Circuit size and opcode metrics

When to use noir-optimize-acir

  • Measure circuit gate count
  • Optimize noir program
  • Benchmark proving time
  • Analyze ACIR opcodes

About this skill

ACIR Optimization Loop

This workflow targets ACIR circuit size for constrained Noir programs. It does not apply to unconstrained (Brillig) functions — Brillig runs on a conventional VM where standard profiling and algorithmic improvements apply instead, and bb gates won't reflect Brillig performance.

Measuring Circuit Size

Binary projects

Compile the program and measure gate count with:

nargo compile && bb gates -b ./target/<package>.json

Library projects

Libraries cannot be compiled with nargo compile. Instead, mark the functions you want to measure with #[export] and use nargo export:

nargo export && bb gates -b ./export/<function_name>.json

Artifacts are written to the export/ directory and named after the exported function (not the package).


If bb is not available, ask the user for their backend's equivalent command. Other backends should have a similar CLI interface.

The output contains two fields:

  • circuit_size: the actual gate count after backend compilation. This determines proving time, which is generally the bottleneck.
  • acir_opcodes: number of ACIR operations. This affects execution time (witness generation). A change can reduce opcodes without affecting circuit size or vice versa — both matter, but prioritize circuit_size when they conflict.

Always record a baseline of both metrics before making changes.

Optimization Loop

  1. Baseline: compile and record circuit_size.
  2. Apply one change at a time.
  3. Recompile and measure: compare circuit_size to the baseline.
  4. Revert if worse: if circuit_size increased or stayed the same, undo the change. Not every "optimization" helps — the compiler may already handle it, or the overhead of the new approach may outweigh the savings.
  5. Repeat from step 2 with the next candidate change.

What to Try

Candidate optimizations roughly ordered by impact:

  • Hint and verify: replace expensive in-circuit computation with an unconstrained hint and constrained verification. This is the highest-impact optimization for most programs.
  • Reduce what you hint: if you're hinting intermediate values (selectors, masks, indices), see if you can hint only the final result and verify it directly.
  • Hoist assertions out of branches: replace if c { assert_eq(x, a) } else { assert_eq(x, b) } with assert_eq(x, if c { a } else { b }).
  • Simplify comparisons: inequality checks (<, <=) cost more than equality (==). But don't introduce extra state to avoid them — measure first.

What Not to Try

  • Don't hint division or modular arithmetic: the compiler already injects unconstrained helpers for these.
  • Don't hand-roll conditional selects: if/else expressions compile to the same circuit as c * (a - b) + b.
  • Don't replace <= with flag tracking without measuring: adding mutable state across loop iterations can produce more gates than a simple comparison.

When not to use it

  • Unconstrained Brillig functions
  • Non-Noir programs

Prerequisites

nargobb CLI

Limitations

  • Does not apply to unconstrained functions
  • Requires bb CLI availability

How it compares

It provides a quantitative feedback loop for circuit optimization rather than relying on manual estimation.

Compared to similar skills

noir-optimize-acir side by side with the closest alternatives in the catalog.

SkillInstallsUpdatedSafetyDifficulty
noir-optimize-acir (this skill)13moReviewIntermediate
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angular1004moReviewAdvanced
cpp-pro184moNo flagsAdvanced

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