open-standards/jouleclaw
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jouleclaw-compose: attribute a claim to its most authoritative citation
`compose_verified_answer` built each segment's `ClaimAttribution` from

    ds.cited_item_ids.iter().filter_map(resolve).next()

under a comment reading "Source URI from the most authoritative cited item".
`.next()` is the first cited id that happens to resolve, in whatever order the
ids were listed — a stated selection criterion the code did not perform.

Authority tier 1 is `AuthorityTier::Primary` and 4 is `Community`, so the most
authoritative cited item is the **minimum** tier. A segment citing a forum post
before a peer-reviewed source was therefore attributed to the forum post, and
the whole attribution rides on that one choice: `retrieval_source_uri`,
`retrieval_timestamp` and `retrieval_axes` all come from it. Selection is now
`min_by_key` on the tier, with ties broken on `item_id` so the result is
reproducible rather than a function of citation order.

A second problem sat in the same expression. `filter_map` drops a cited id that
matches no retrieved item **silently**, so a segment whose citations all dangle
came out with the ids still attached and an all-`None` attribution, with
nothing anywhere stating why. A reader sees citations and no source. Dangling
citations are now counted and reported as a caveat, using the mechanism the
function already uses for dropped segments. This is the honest shape of the
problem the sweep called "citation laundering": the citations are not read back
as provenance, and the gap was invisible.

Three tests, each pinning one property, every one of them discriminating on
*order* rather than on a single arrangement:

- the same two items, tier 1 and tier 4, cited both ways round, must attribute
  to the tier-1 source both times;
- two items of **equal** authority, cited both ways round, must resolve the
  same way — the tie-break is the only thing that makes this true, and it is
  the only test that catches its removal;
- a segment with one real and one dangling citation reports the dangling one
  and still attributes from the real one; a segment where every citation
  dangles has no attribution at all, which is when saying so matters most.

The sweep's own description of this finding was wrong in its specifics —
`cited_item_ids` is read in three places, and there is no `jouleclaw-diagnose`
crate — but reading the code to check surfaced the real defect beside it.

Co-Authored-By: Claude Opus 5 <[email protected]>
2026-10-19 20:41:38 -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-compose: attribute a claim to its most authoritative citation 2026-10-19 20:41:38 -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-graph: a node in flight survives the process, and an interrupted one is held rather than silently run again 2026-10-19 02:56:06 -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