new-invariant
Testing & QualityImplement a new invariant for jolt-eval
How to use this skill
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This skill handles all the boilerplate: creating the invariant struct + input type, implementing the Invariant trait, registering it in the JoltInvariants enum, creating a fuzz target (if applicable), and running sync_targets.sh.
<Execution_Policy>
- The user must provide an invariant name (lowercase with underscores, e.g.
sumcheck_binding). - Ask the user what property is being checked and what the input type should look like before writing code.
- Follow existing patterns exactly — study the split_eq_bind and soundness invariants as models.
- Always run clippy and the auto-generated tests before reporting success. </Execution_Policy>
Phase 1: Gather Requirements
- Validate the argument
{{ARGUMENTS}}: must be a valid Rust identifier (lowercase alphanumeric + underscores). Reject otherwise. - Ask the user:
- What property does this invariant check? (becomes the
description()) - What does the input look like? (fields, types, ranges)
- What synthesis targets should it support? (
Test,Fuzz,RedTeam) - Does it need non-trivial setup? (e.g. preprocessing, compilation — default to
Setup = ())
- What property does this invariant check? (becomes the
Phase 2: Explore Context
- Read
jolt-eval/src/invariant/mod.rsto understand the currentJoltInvariantsenum anddispatch!macro. - Read an existing invariant for reference:
- Simple:
jolt-eval/src/invariant/split_eq_bind.rs - Complex (with setup, enrich_input):
jolt-eval/src/invariant/soundness.rs
- Simple:
- If the invariant tests jolt-prover-legacy functionality, explore the relevant jolt-prover-legacy modules to understand the types and APIs involved.
Phase 3: Implement
Create the invariant file at jolt-eval/src/invariant/<invariant_name>.rs with:
Input Type
#[derive(Debug, Clone, serde::Serialize, serde::Deserialize, schemars::JsonSchema)]
pub struct <Name>Input {
// fields
}
impl<'a> Arbitrary<'a> for <Name>Input {
fn arbitrary(u: &mut Unstructured<'a>) -> arbitrary::Result<Self> {
// Generate random inputs with reasonable bounds
}
}
Key requirements for the input type:
- Must derive
Debug,Clone,Serialize,Deserialize,JsonSchema - Must implement
Arbitrarymanually (for fuzzing) - Use bounded ranges in
Arbitraryimpl (e.g.u.int_in_range(2..=16)?) to keep inputs meaningful
Invariant Struct
#[jolt_eval_macros::invariant(Test, Fuzz, RedTeam)] // adjust targets as needed
#[derive(Default)]
pub struct <Name>Invariant;
impl Invariant for <Name>Invariant {
type Setup = (); // or a custom setup type
type Input = <Name>Input;
fn name(&self) -> &str { "<invariant_name>" }
fn description(&self) -> String { "...".into() }
fn setup(&self) -> Self::Setup { /* ... */ }
fn check(&self, setup: &Self::Setup, input: Self::Input) -> Result<(), CheckError> {
// 1. Validate input — return Err(CheckError::InvalidInput(...)) for degenerate cases
// 2. Run the property check
// 3. Return Ok(()) if the invariant holds
// 4. Return Err(CheckError::Violation(...)) if violated
}
fn seed_corpus(&self) -> Vec<Self::Input> {
// Include: minimal case, typical case, edge case (large values, boundary conditions)
}
}
Guidelines for check()
- Use
CheckError::InvalidInputfor degenerate inputs that should be skipped (not counted as violations) - Use
CheckError::Violation(InvariantViolation::with_details(...))for actual violations — include diagnostic info - Compare against a known-correct reference implementation when testing optimized code
Phase 4: Register
Edit jolt-eval/src/invariant/mod.rs:
- Add
pub mod <invariant_name>;to the module declarations at the top. - Add a variant to
JoltInvariants:<VariantName>(<invariant_name>::<Name>Invariant), - Add the variant to
JoltInvariants::all():
UseSelf::<VariantName>(<invariant_name>::<Name>Invariant),<Name>Invariant::default()if the struct has fields. - Add the variant to the
dispatch!macro:JoltInvariants::<VariantName>($inv) => $body,
Phase 5: Create Fuzz Target (if targets include Fuzz)
Create jolt-eval/fuzz/fuzz_targets/<invariant_name>.rs:
#![no_main]
use jolt_eval::invariant::<invariant_name>::<Name>Invariant;
jolt_eval::fuzz_invariant!(<Name>Invariant::default());
Then run ./jolt-eval/sync_targets.sh to update fuzz/Cargo.toml.
Phase 6: Validate
Run these commands (all must pass):
# Format
cargo fmt -q
# Lint
cargo clippy -p jolt-eval -q --all-targets -- -D warnings
# Run auto-generated tests (seed_corpus + random_inputs)
cargo nextest run -p jolt-eval --cargo-quiet invariant::<invariant_name>
# If fuzz target was created, verify it compiles
cd jolt-eval/fuzz && cargo check 2>&1 | head -20
If any step fails, fix the issue and re-run.
Task: Implement a new invariant for jolt-eval. {{ARGUMENTS}}