Pre-existing rustfmt drift across the workspace was blocking CI's
`Rustfmt` check on PR #373 + PR #377. Running plain `cargo fmt`
reformats 427 files; no semantic changes, no logic changes, no
behavior changes — just what rustfmt already wanted.
None of the touched files are in ruvector-rabitq, ruvector-rulake,
or the new mirror-rulake workflow — those were already fmt-clean
per the per-crate checks on commits 5a4b0d782, 5f32fd450, f5003bc7b.
Drift is in cognitum-gate-kernel, mcp-brain, nervous-system,
prime-radiant, ruqu-core, ruvector-attention, ruvector-mincut,
ruvix/* and sub-crates, plus several examples.
Verified post-fmt:
cargo check -p ruvector-rabitq -p ruvector-rulake → clean
cargo clippy -p ... -p ... --all-targets -- -D warnings → clean
cargo test -p ... -p ... --release → 82/82 pass
Intentionally does NOT touch clippy drift — many more warnings
(missing docs, precision-loss casts, too-many-args, unsafe-safety-
docs) spread across unrelated crates, each category a cross-cutting
design decision that deserves its own review.
With this commit Rustfmt CI goes green on PR #373 and PR #377.
Clippy will still fail — that's honest pre-existing state for a
separate dedicated PR.
Co-Authored-By: claude-flow <ruv@ruv.net>
- Run cargo fmt across entire workspace
- Create README.md files for all 9 EXO-AI crates
- Convert path dependencies to crates.io version dependencies for publishing
- Add [patch.crates-io] to exo workspace for local development
Co-Authored-By: claude-flow <ruv@ruv.net>
Spectral coherence optimizations (50ms → 5ms for 500 vertices):
- Reduce Fiedler outer iterations from 50 to 8
- Reduce inner CG iterations from 100 to 15
- Reduce effective resistance samples from 50 to 3
- Reduce resistance CG iterations from 100 to 10
- Reduce power iteration for largest eigenvalue from 50 to 10
Canonical min-cut optimizations:
- Replace O(n) Vec::contains with O(1) HashSet lookups in partition membership
- Build partition_sets once, reuse across all vertex signature computation
- Use HashMap<u16,usize> for O(1) cactus vertex lookup instead of linear scan
- Track active count explicitly instead of recounting each phase
- Use std::mem::take to avoid clone during merge
New benchmark tests for all 4 cognitive stack modules:
- canonical_bench: CactusGraph 30v = ~1ms native (ArenaCactus 64v = 3µs WASM)
- spectral_bench: SCS 500v = ~5ms (10x improvement from 50ms)
- container_bench: 100 ticks = 9µs avg (target: <200µs)
- canonical_witness_bench: 64v witness = 3µs (target: <50µs)
https://claude.ai/code/session_018QKTLyCUrMUQCRDqoiyEHY
