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iterate-kernel

iterate ecosystem shared kernel: schemas, the evidence->decision transcription, the decision-log audit chain and public validators. Verification reasoning stays in the engine; this layer transcribes.

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0.1.6
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iterate-kernel

The iterate ecosystem's shared semantic kernel: schemas, the evidence → decision transcription, the decision-log audit chain, and public validators.

What it is not. It carries no verification reasoning. Judging whether a claim is true belongs to the engine that produced the evidence; this package transcribes what that engine already decided, so that every shell in the ecosystem speaks the same language instead of each inventing its own.

Install

npm install iterate-kernel

Import per module, not through the barrel

import { decisionOutcomeFromEvidence } from "iterate-kernel/evidence-decision"
import { appendDecisionEntry } from "iterate-kernel/decision-log"
import { parseEvidencePack } from "iterate-kernel/parse"

Each module is its own subpath export. Importing the barrel (iterate-kernel) also pulls in schemas, which reads the JSON Schema files next to the package at load time — fine in a repository, but a runtime file read is a trap for anyone bundling to a single file. The subpaths avoid it, and they keep a consumer's dependency on this package as narrow as the APIs it actually uses.

The pieces

ModuleWhat it is for
evidence-pack / parsethe evidence pack shape, and parsing/validating one
evidence-decisionthe transcription: evidence (attribution level, circuit-breaker level, pass/fail/inconclusive) → a decision outcome and a human summary. It reads fields the engine already decided; it never infers.
decision-log-entry / decision-logthe append-only decision-log entry and the opID ↔ entry hash chain that makes it auditable. The entry carries the producer's own kind, its round, the dimension a decision served and a bounded payload — all optional, so chains written before them keep their bytes and their digests.
decision-log-transcribethe mapping from a decision record that the iterate ledgers already write ({timestamp, round, type, data} JSONL, produced independently in Python and TypeScript) onto a canonical draft. Rules live in fixtures/decision-record-transcription.ok-01.json so the second implementation is coded from the fixture, not from this package.
dimension-context / parsethe dimension-coverage transcription: a plan plus what the engine actually recorded → verified / unverified / unplanned, and one line to put in a summary. It validates id shape, never which ids exist — that list belongs to whoever configured the run.
run-plan / parsethe plan that dimension-context needs and refuses to invent: which dimensions a run intends to cover, in the caller's order, with the declared source. It carries a digest (rp_ + sha256 of the canonical form) so a ledger line can state which plan a run was held to, and a reader can notice the plan changed mid-run. Nothing here reads a config file — producing a plan is whoever configures the run's job, and that keeps the kernel from learning a consumer's file format.
invariant-report / parsewhat the invariant runner may state about its own checks, and the re-verification a failure asks for. It refuses a report that says pass while carrying a failed check, and it turns an error (a check that could not run) into no request: re-verifying the app would answer a question nobody measured.
convergencethe rules for what the loop does next, from stated inputs only. A tripped breaker, a spent round budget, and an errored check each halt; unlooked-or-unmeasured states verify, never converged. Both harnesses read one idea of "done" instead of growing two.
provider-registrationmetadata for a judgement producer — who offers which method, and what it requires. Registering an existing id is refused rather than silently overridden, and resolution never guesses.
errors / schemas / canonical-json / recipe-configKernelSchemaError, the JSON Schemas, canonical serialisation, recipe validation

A runnable example

This is the whole surface in one file, and it is the shape the API actually wants. Two details cost real time to discover, so they are written out here rather than left to the error messages:

  • the ledger path is a first argument, not a field. There is no default location, on purpose: a durable audit chain should not be created wherever a process happened to start.
  • entryId and createdAt are yours to supply (sequence and prevEntryHash are derived from the ledger and must not be sent). newDecisionEntryId() mints one in the required dl_<26 Crockford> form.
import { decisionOutcomeFromEvidence, decisionSummaryFromEvidence } from "iterate-kernel/evidence-decision"
import { appendDecisionLogEntry, newDecisionEntryId } from "iterate-kernel/decision-log"
import { parseEvidencePack, parseDimensionContextInput } from "iterate-kernel/parse"
import { dimensionContext, formatDimensionContext } from "iterate-kernel/dimension-context"
import { resolve } from "node:path"

const pack = parseEvidencePack(await readFile("evidence.json", "utf8").then(JSON.parse))
const outcome = decisionOutcomeFromEvidence(pack)

// the transcription — never an inference; it reads what the engine already decided
console.log(outcome, decisionSummaryFromEvidence(pack))

// the audit chain — refuses to append onto a tail it cannot re-hash
appendDecisionLogEntry(resolve("ledger.jsonl"), {
  entryId: newDecisionEntryId(),
  createdAt: new Date().toISOString(),
  operationId: pack.operationId,
  outcome,
  summary: decisionSummaryFromEvidence(pack),
})

// dimension coverage — `recorded` is what the engine logged, not what you hoped it would
const input = parseDimensionContextInput({
  planned: [{ id: "correctness" }, { id: "security" }, { id: "ui-ux" }],
  recorded: { security: { decisions: 3, operationIds: [pack.operationId] } },
})
// -> "1/3 dimensions verified, 2 unverified (correctness, ui-ux), 3 decisions"
console.log(formatDimensionContext(dimensionContext(input)))

parseDimensionContextInput returns the validated input; dimensionContext computes the context; formatDimensionContext renders the line. Anything recorded but never planned shows up as unplanned — a reporter that quietly dropped it would be the failure this exists to prevent.

Versioning

0.1.x is pre-stable. The schemas and the transcription rules are the contract every consumer depends on, so a change to either is a minor-version change at minimum, and the fixtures in fixtures/ are the executable statement of what the contract means.

The fixtures are the portable half of the contract

schemas/ and fixtures/ ship in the tarball — test/packaging.test.mjs packs locally and refuses a corpus that did not make it into the artifact. Each fixture states its own rules in its comment, written so a second implementation can be coded from the file without reading the TypeScript. That is the only way this contract reaches the consumers that cannot import it: iterate-harness is Python and glasspaned is Swift.

Those consumers do not read this package at runtime. They vendor a copy of the corpus pinned by sha256 — iterate-harness/tests/kernel_fixtures/, checked by its scripts/check_kernel_fixtures.py (--source kernel/fixtures inside the monorepo, registry mode in the split repo). Moving a fixture therefore means re-recording that pin in the same change, and the check fails in whichever direction the bytes disagree. A cross-implementation comparison that can be skipped silently is not a contract; it is a note nobody reads.

Consumers

A consumer's kernel is this package, pinned. There is no second copy of the source anywhere: the GlassPane Harness fork used to vendor kernel/src under packages/opencode/vendor/kernel with a probe that asked whether the canonical branch had moved, and that arrangement was retired in favour of the npm dependency — its script/kernel-pin.mjs now checks the installed version, the lockfile integrity hash, and the per-file sha256 of the shipped corpus against contracts/kernel-pin.json, and script/kernel-conformance.mjs runs the fixtures against the installed dist/.

The Python side still cannot import TypeScript, so it vendors the corpus (fixtures and schemas) and implements the rules itself from the fixture comment fields; that is what the paragraph above describes, and scripts/check_kernel_fixtures.py is what keeps the two copies byte-agreed.

Either way, run the fixtures: they are how you find out that the kernel you have is not the kernel you think you have.

FAQs

Package last updated on 12 Oct 2026

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