open-standards/jouleclaw
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compliance: publish the EU draft PUE bands as a sourced data pack, not as code
`BandingScale` deliberately ships no canonical scale: which thresholds are
correct for a metric is a policy question a library has no standing to settle,
and baking one in would repeat the mistake the type was written to retire —
`is_compliant`'s `pue < 1.5 && renewable_pct >= 50.0`, two magic floats with no
provenance, no version, and no way to say which instrument they encoded.

So the EU draft's PUE bands are published as **data**, in `jouleclaw/scales/v1/`,
with their sources beside them. `BandingScale` already derives `Deserialize`, so
a pack loads with `serde_json::from_str` and this adds no crate code at all —
which is the point.

Each pack is exactly a `BandingScale`, accompanied by a provenance file
recording where the numbers came from, the status of that source, what the pack
omits, and the reuse terms. A pack with no provenance file is not publishable
here; a threshold whose origin is unstated is the thing the directory exists to
replace.

Three things the provenance says plainly:

- **The instrument is a DRAFT** — registered 2026-03-26, revised 2026-07-02, not
  adopted and not in the Official Journal, with first labels expected
  2027-08-15. A grade produced from it is not a regulatory determination.
- **WUE is deliberately absent.** The instrument sets the grade from PUE *and*
  WUE, and only the PUE bands were read from it. Inventing WUE boundaries to
  complete the set would be exactly the failure this design prevents: a
  threshold with no provenance, presented as though it had one. A test asserts
  that a composite built from this pack reports `covers(&["pue","wue"]) ==
  false`, so a half-graded facility cannot read as graded.
- **The instrument permits calculation and estimates**, not only measurement, so
  a PUE fed to this scale may be self-declared. The scale bands whatever number
  it is given and says nothing about how that number was acquired.

The scale id is a version and is never edited in place. Ratings cite their
`scale_id` and `comparable_with` refuses to rank across scales, which only works
if an id means one fixed set of boundaries forever — so a changed instrument is
a new id, never an edit that would silently re-band grades already issued.

The pack is tested, not merely committed: it is `include_str!`-ed, deserialized,
validated and banded, and the test pins that its last boundary is **1900** —
this file's own example fixture uses 2000, and only one of the two is sourced.

Verified: 52 jouleclaw-compliance tests pass (2 new).

Co-Authored-By: Claude Opus 5 <[email protected]>
2026-09-06 06:24:25 -04:00
..
conformance/v1 jouleclaw SPEC.md: normative §§8-12 for waves 12-21 2026-06-02 10:42:25 -04:00
jouleclaw-rs compliance: publish the EU draft PUE bands as a sourced data pack, not as code 2026-09-06 06:24:25 -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
README.md family: wire JouleClaw, Sandbox, and Joule Code as JCP consumers 2026-06-10 11:19:00 -04:00
ROADMAP.md docs: strip vanity metrics from README + ROADMAP 2026-06-02 07:30:50 -04:00
SPEC.md jouleclaw: wave-25 — contract CLI + signed verdict-receipt + source fetcher + revise loop 2026-06-03 04:12:27 -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