open-standards/jouleclaw
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compliance: grade on water too, and retire the two magic floats
`EedReport::is_compliant()` was `self.pue < 1.5 && self.renewable_pct >= 50.0`:
two hardcoded floats with no provenance, no version, and no way to say which
instrument they encode — the exact shape `BandingScale` was added to replace,
sitting in the same crate, on the path a regulator would read.

It also silently ignored water. `EedReport` has collected `water_usage_liters`
all along, and the schemes that grade facilities grade on power **and** water,
so the check discarded an axis it already had in hand. The test that
demonstrates this is the reason for the deprecation rather than an argument for
it: a facility with PUE 1.10 and 2.0 L/kWh **passes `is_compliant()` while its
actual grade is F**.

Three pieces:

- `wue_milli_l_per_kwh()` derives Water Usage Effectiveness as an integer, and
  returns `None` rather than 0 when IT energy is zero. WUE is undefined there,
  and a 0 would read as *perfect* water efficiency for a facility that reported
  nothing — the flattering direction, which is the one to refuse.
- `CompositeRating` combines several metric ratings into one published grade
  under a **declared** rule. "Worst of" and "mean of" are both defensible and
  give different letters for the same facility, so the rule travels with the
  grade for the same reason a `Rating` carries its scale. It keeps its
  components, so a reader sees *which axis set the grade* — a facility rated D
  on water with an A on power is a materially different thing from one rated D
  on both, and a bare letter cannot tell them apart. `binding_component()` names
  the axis an operator has to improve to move the letter, and `covers()` reports
  whether a required axis was graded at all, because a grade that silently omits
  one is not the scheme's grade.
- `grade()` ties them together, taking the scales rather than embedding any.
  Which thresholds apply is the instrument's business, not this crate's — the
  same reason `BandingScale` still ships no canonical scale.

`is_compliant` is deprecated rather than deleted: it is public API, and the
deprecation note carries the reasoning to the call site, which a silent removal
could not. Pre-existing tests that exercise it keep working under a
module-level allow.

Duplicate metrics are refused: the same axis graded twice votes twice, which
under a worst-of rule is harmless and under any other rule is a silent weighting
nobody declared.

Found by the 2026-08-29 sweep, which flagged both that WUE was not rateable
end-to-end and that this function had survived the change meant to retire it.

Verified: 50 jouleclaw-compliance tests pass (7 new), no clippy warnings in the
crate — the four reported are pre-existing, in jouleclaw-core and
jouleclaw-energy.
2026-09-03 15:16:02 -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: grade on water too, and retire the two magic floats 2026-09-03 15:16:02 -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