open-standards/jouleclaw
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Transaction Science 130123f648
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standards workspaces build + test / macOS energy backends (pull_request) Successful in 10m2s
standards workspaces build + test / jouledesk-rs (jouledesk/jouledesk-rs, jouledesk-rs, macos) (pull_request) Successful in 3m49s
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standards workspaces build + test / jouleclaw-rs (-nodebug, jouleclaw/jouleclaw-rs, -p jouleclaw-energy --features rapl,nvml, jouleclaw-rs, linux-arm64, -C target-feature=+fp16) (pull_request) Successful in 7m35s
jouleclaw-omni: declare 23 modules that were compiled by nothing
Twenty-five source files in this crate were named by no `mod` line, so they
were not in the build at all: ~19,000 lines that nothing type-checked, tested
or linted. `scripts/check-orphan-sources.py` pinned them as a baseline so the
count could only fall, and this is that fall: 25 -> 1.

Declaring them costs almost nothing, which is the surprise. Twenty-three
compile clean, and the two that do not are blocked by facts outside the code:

  video_decode.rs wants `ffmpeg_next`, which is not a dependency
  (`extern crate ffmpeg_next` -> E0463). That is a system library and a
  licensing choice, so it stays undeclared, and the baseline now holds it
  alone, with the reason written beside it.

  fusion.rs has every one of its `use` lines behind
  `#[cfg(feature = "metal")]` while the items that need those types do not, so
  a default build loses the imports and keeps the code: 31 unresolved types.
  It only ever compiled with that feature on. The module is now gated the same
  way, as `gpu_ops` and the sana_wm draft already are.

sana_wm_gpu_dispatchers_draft.rs is gated likewise: it imports
`crate::hal::metal`, which is `#[cfg(feature = "metal")]`.

Measured on the build host, with --keep-going so an early error cannot hide
what is behind it: `cargo check` 0 errors, `cargo clippy --all-targets` 0
errors, 44 tests pass, the whole jouleclaw workspace still checks, and the
orphan guard passes on the new baseline, its planted-orphan self-test included.

⚠️ Separately, and not from this change: `--features metal` does not compile on
main at all -- 3063 errors, concentrated in files that were already declared
(hunyuan3d.rs 300, audiogen.rs 269, trellis.rs 213). Measured on origin/main
before this change, so it is pre-existing. No CI job builds that feature.

Co-Authored-By: Claude Opus 5 <[email protected]>
2026-10-18 07:19:24 -04:00
..
conformance/v1 jouleclaw SPEC.md: normative §§8-12 for waves 12-21 2026-06-02 10:42:25 -04:00
jouleclaw-rs jouleclaw-omni: declare 23 modules that were compiled by nothing 2026-10-18 07:19:24 -04:00
scales compliance: publish the EU draft PUE bands as a sourced data pack, not as code 2026-09-06 06:24:25 -04:00
vocab jouleclaw: wave-24 — contract + handoff + mission + value report 2026-06-03 02:35:34 -04:00
LICENSE jouleclaw: standard skeleton + Phase 1 foundation crates 2026-05-26 09:55:11 -04:00
LICENSE-SPEC licences: ship the Apache-2.0 text the code already declares 2026-10-09 17:22:32 -04:00
README.md licences: ship the Apache-2.0 text the code already declares 2026-10-09 17:22:32 -04:00
ROADMAP.md docs: strip vanity metrics from README + ROADMAP 2026-06-02 07:30:50 -04:00
SPEC.md jouleclaw-energy: a process reads itself only once the reading thread has left its core 2026-10-12 20:50:52 -04:00

JouleClaw — Energy-Optimized AI Runtime

The substrate for AI that costs Joules, not tokens.

Capability per Joule, not capability per parameter.

What JouleClaw is

JouleClaw is a pure-Rust, omni-modal AI runtime + harness + agentic layer governed by Transaction Science as an open standard (5th in the open-standards quartet, alongside OpenPay, Smart Byte, EOC, and WAI).

Every operation JouleClaw performs walks an explicit energy-tiered cascade, top to bottom, stopping at the first stage that closes the query:

Tier Name Cost class What runs here
L0 Cache picojoules Content-addressed cache hits
L1 Lawful nanojoules Deterministic, pre-compiled primitive (text/code only)
L2 Embed sub-millijoules Matryoshka embeddings + nearest-neighbor + hybrid search
L3 Model joules Local SSM / ternary / multimodal / diffusion / etc.
L4 Wire tens of joules Remote frontier RPC (escape hatch only)

L1 (Lawful) is only meaningful for text and code modalities. For image, audio, video and 3D generation, the cascade collapses to L0 / L2 / L3 / L4 — the energy savings come from caching plus dispatch to the cheapest model that meets the quality bar.

Why JouleClaw exists

The mainstream "agentic AI" ecosystem treats inference as the entry point. Every state shift, every tool call, every routing decision runs through a 70-billion-parameter stochastic engine, burning kilojoules to do work that deterministic compute or a hot cache could resolve for microjoules.

JouleClaw inverts the default. Inference is the last resort, not the first. Frozen model weights are less trustworthy than current world state; fresh, provenance-stamped retrieval beats synthesis from training cuts. Every operation is metered in microjoules where the hardware permits it, and in millijoules where it doesn't — the spec is honest about the floor on every platform.

The thermodynamic circuit breaker is the safety mechanism. Set an energy budget; when measured consumption exceeds the budget, the breaker trips and the operation halts. Hallucination loops cannot survive an honest joule ledger.

What's here

Path Contents
SPEC.md JouleClaw v1 spec — cascade tiers, energy contract, receipt
CHARTER.md Stewardship pattern (shared across open-standards)
jouleclaw-rs/ Apache-2.0 Rust reference implementation
spec/ Tier specifications, energy provenance, receipt format
conformance/v1/ Signed wire vectors for cross-implementation verification

Reference implementation

jouleclaw-rs/ is the Apache-2.0 reference implementation in Rust. It runs on Apple Silicon (M3/M4/M5 with UMA + Metal 4 Tensor APIs), AMD Strix Halo / Ryzen AI Max, Intel Lunar Lake, NVIDIA Jetson, and discrete NVIDIA / AMD GPUs.

It is omni-modal: text, code, vision, audio, video, image diffusion, 3D Gaussian splatting, and cross-modal fusion all dispatch through the same energy-tiered cascade.

The MCP tool surface is a JCP consumer: jouleclaw-jcp wraps any jouleclaw-mcp metered tool so every dispatch is decided by the JCP runtime against a signed, metered Grant before a byte reaches the tool — the tool's identity is the content-addressed resource, the call's energy estimate is debited from the grant's joule budget, and every decision (allow and deny alike) seals as a JCR-1 receipt. An injected instruction can name an ungranted tool; it cannot make the gate dispatch it.

Status

v0.1.0 reference implementation in active development. The spec is draft status. Cross-implementation conformance vectors will land with v1.0.0.

License