Use when running comprehensive WCAG accessibility audits with axe-core + pa11y + Lighthouse, generating context-aware remediation, or testing video accessibility. Supports 3-tier browser cascade with graceful degradation.
日本語の概要は準備中です。原文の説明を表示しています。
Adversarial review court — a delivery (diff, PR, test suite, or artifact) is prosecuted by independent AI reviewers from different vendors, each with its own probe set, then a SHIP verdict must SURVIVE escalating deeper reviewers before it stands. Use when you want more than one reviewer's opinion on whether something is safe to ship: pre-merge gating, release go/no-go, catching a too-easy PASS, or any 'is this actually done?' decision where a shallow approval is a risk. Produces a signed court record with a three-valued verdict (SHIP / REMAND / BLOCK) and a human as final judge. Learns over time: reproduced charges and overturned SHIPs feed the QE flywheel.
日本語の概要は準備中です。原文の説明を表示しています。
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One reviewer — even a strong one — is one Einstein squinting at the chalkboard.
QE-Court convenes independent adversaries from different vendors, with different
roles and different probe sets, makes them attack the delivery, and then forces
any SHIP verdict to survive an escalating deeper review before it stands. You
stay in the loop as the final judge. Implements ADR-124; composes ADR-117..122.
The one rule that makes it a court and not a rubber stamp: a passing grade is
the claim under attack, not the finish line. A shallow 91/100 SHIP that a
deeper reviewer can overturn is a bug in the review, not a delivery that shipped.
For a quick single-lens review, use /sherlock-review, /brutal-honesty-review,
or /code-review instead — the court is for when one opinion isn't enough.
| Role | Who | Job |
|---|---|---|
| Defense | writer model (summarizer) | States the case-FOR-ship from the evidence. Never grades. |
| Prosecution | qe-devils-advocate, brutal-honesty-review, sherlock-review, qe-security-scanner, qe-mutation-tester, codex exec review | Each files CHARGES against the delivery, with its own probe set, blind to the others until filing. |
| Blind refuter | src/verification/adversarial-verify | Tries to KILL weak charges (default-refuted-if-uncertain). |
| Jury | two-gate LLM-judge (ADR-119), cross-model | Weighs surviving charges → verdict + (optional) score. |
| Deeper reviewer | higher effort/model tier of any prosecutor | The overturn round. |
| Judge | you (the human) | Sees the strongest case for AND against; rules. |
⚠️ Do NOT run the reduced 3-dimension QCSD workflow as the court engine. It can falsely rate SHIP by skipping the security / mutation / defect lanes. Spawn the specialized
qe-*prosecutors above, or you reproduce the exact false-SHIP the court exists to catch. (ADR-124; seeqcsd-development-swarm.)
The court's guarantees come from who reviews, not just how. Routing is
user-configurable in config.json under routing; the defaults below enforce
the invariants. Every model call goes through AQE's provider layer (ADR-123), so
budget caps and cost receipts apply automatically.
| Step | Default provider / tier | Why |
|---|---|---|
| Defense | claude-code (default) or cognitum-low (may equal writer) | Cheap; states the case, never grades. Must differ in vendor from the jury |
| Prosecutor — devils-advocate | cognitum-mid | Gap/assumption hunting |
| Prosecutor — brutal-honesty | claude-code (Opus/Sonnet) | Rigor lens, different family from jury |
| Prosecutor — sherlock | cognitum-high | Deductive/root-cause needs a strong model |
| Prosecutor — security-scanner | SAST tool + cognitum-mid | Determinism where possible |
| Prosecutor — mutation | mutation tool + local/booster | Test-adequacy is mechanical |
| Prosecutor — codex-review | codex (ChatGPT sub) | Cross-vendor GPT brain — true writer≠juror; ≈$0 |
| Jury (two-gate judge) | cognitum-high or Opus, provider ≠ writer | Must not grade its own family's output |
| Deeper reviewer | highest tier / best-of-N @ higher effort | Escalation must be stronger than the base panel |
Provider menu (mix freely in routing): claude-code (Claude subscription),
cognitum-{low,mid,high} (Cognitum's own multi-model tiers — one option, it routes
internally), openrouter (use when you want many distinct models across vendors
for breadth), codex (GPT via ChatGPT subscription), claude/openai/gemini
(metered APIs), ollama (local). Cognitum and OpenRouter are separate options:
Cognitum already resolves multiple models behind its tiers; OpenRouter is the lever
when you explicitly want to name several different models.
Enforced invariants (defaults; do not weaken without reason):
cognitum-low and cognitum-high are the same
vendor, so pairing them across defense and jury is a violation, not a diverse panel.ProviderManager → ADR-123 budget cap + receipts.Invariants 1–2 are machine-checked by validateCourtConfig() in referee.ts, which
the court MUST call before seating a panel (see How to run it). The options block
below binds directly to that check — minDistinctVendors and writerIsNeverJuror are
read, not decorative.
DELIVERY (diff / PR / test-suite / artifact)
│ 1. DEFENSE — writer model states the case for shipping, from evidence only.
│ 2. PROSECUTION (parallel, blind) — N specialized reviewers, DIFFERENT vendors,
│ each generates its OWN probe set and files CHARGES (finding + reproduction).
│ 3. KILL ROUND — blind refuters attack each charge; weak/unreproducible ones dropped.
│ 4. JURY — two-gate judge, cross-model, writer≠juror. 3-valued verdict.
│ A numeric score is emitted ONLY if its rubric passed the ADR-122 ANOVA screen.
│ 5. OVERTURN ROUND — if verdict == SHIP, escalate ONE deeper reviewer. Loop-until-dry:
│ SHIP only STANDS if K consecutive deeper rounds find nothing new. Surviving fatal → flip.
│ 6. SIGNED COURT RECORD — provenance-tier surviving charges (ADR-121), sign (ADR-118).
▼ HUMAN JUDGE (you) — rules SHIP / REMAND / BLOCK on the strongest case both ways.
| Verdict | Meaning | Trigger |
|---|---|---|
| SHIP | Survived the overturn round | No fatal charge survived K deeper rounds |
| REMAND | Fixable charges — back to author | Non-fatal charges survived; delivery is close |
| BLOCK | A fatal charge survived | ≥1 fatal charge reproduced and not refuted |
A verdict is not the end; it is training signal. After each court run:
src/learning/qe-flywheel/receipt.ts createSigner / platform-signer.ts,
persisted via receipt-store.ts). The verdict + surviving charges are the body.qe_pattern (ADR-110) at provenance
tier oracle:test-exec (ADR-121 — it reproduced, so it is oracle-grade).
Killed/refuted charges are NOT stored as positives (noise control).{shallow: SHIP, true: BLOCK|REMAND, charge} as a discriminator training pair
for the frozen anchor (ADR-117) and two-gate judge (ADR-119). This is what makes
the court harder to fool over time.qe_pattern_embeddings).All writes are appends to existing stores — never destructive to memory.db.
qe-court/probes namespace).QE-Court is an orchestration skill: the driving agent convenes the court by
composing existing agents/skills — there is no monolithic binary yet (a thin
aqe court CLI wrapper is planned as ADR-124 Phase 1; the hosted /v1/qe/verdict
is Phase 2). To run a court now:
Read config.json for the panel + routing + overturnDepth, then validate
the panel before seating it — this step is not optional:
import { validateCourtConfig } from 'agentic-qe/skills/qe-court/referee';
const violations = validateCourtConfig(config); // [] == valid
if (violations.length) throw new Error(`Cannot convene: ${violations.join(', ')}`);
A non-empty result means the panel cannot render a trustworthy verdict (colluding jury, too few vendors, no jury at all). ABORT the court and tell the user which invariant failed — do not proceed with a degraded panel and do not silently re-route around it. A court that convenes an invalid panel produces exactly the false SHIP it exists to catch.
Spawn the prosecutors in one message, in parallel (Task/Agent,
run_in_background: true), each with its routed provider; run
codex exec review for the cross-vendor lens via Bash.
Collect charges → run the blind-refuter kill round (adversarial-verify).
Jury (two-gate judge) → verdict. If SHIP, run the overturn loop to overturnDepth.
Emit the signed court record; persist learning per the section above.
Present the strongest case FOR and AGAINST to the human judge.
Markdown: the delivery under review, the Defense case, each prosecutor's surviving charges (provenance-tiered, with the vendor that filed them), the kill-round casualties, the jury verdict, the overturn transcript, and the signed verdict block. Durable, attestable evidence — the "jury waiting for everything you ship."
Tier 3 (verified). The court's falsifiable invariants are enforced by the
published agentic-qe/skills/qe-court/referee entrypoint and covered by a
consumer-runnable aqe-court-referee self-test <oracle> suite that the acceptance eval
(evals/qe-court.yaml, command-eval mode) runs through the aqe eval CLI —
15/15 green as of 2026-07-29. That suite now validates the shipped config.json
itself, so a routing edit that seats a colluding panel fails in CI rather than in
a user's court (issue #576). The keystone oracle: a seeded mutant a shallow panel
rated SHIP is overturned to BLOCK when the overturn round is active, and MUST
regress to SHIP at overturnDepth: 0 — proving the mechanic carries its weight.
Run it yourself: aqe eval run --skill qe-court --model cognitum-low.
/v1/qe/verdict (Cognitum, planned)./brutal-honesty-review, /sherlock-review, qe-devils-advocate agent, codex exec review.src/verification/adversarial-verify. Signer: src/learning/qe-flywheel/receipt.ts./code-review, /pr-review (single-lens); qcsd-cicd-swarm (phase gate, not adversarial court).まだレビューはありません。使ってみた感想をお寄せください。
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Use when running comprehensive WCAG accessibility audits with axe-core + pa11y + Lighthouse, generating context-aware remediation, or testing video accessibility. Supports 3-tier browser cascade with graceful degradation.
日本語の概要は準備中です。原文の説明を表示しています。
WCAG 2.2 compliance testing, screen reader validation, and inclusive design verification. Use when ensuring legal compliance (ADA, Section 508), testing for disabilities, or building accessible applications for 1 billion disabled users globally.
日本語の概要は準備中です。原文の説明を表示しています。
Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.
日本語の概要は準備中です。原文の説明を表示しています。
Create and train AI learning plugins with AgentDB's 9 reinforcement learning algorithms. Includes Decision Transformer, Q-Learning, SARSA, Actor-Critic, and more. Use when building self-learning agents, implementing RL, or optimizing agent behavior through experience.
日本語の概要は準備中です。原文の説明を表示しています。
Implement persistent memory patterns for AI agents using AgentDB. Includes session memory, long-term storage, pattern learning, and context management. Use when building stateful agents, chat systems, or intelligent assistants.
日本語の概要は準備中です。原文の説明を表示しています。
Optimize AgentDB performance with quantization (4-32x memory reduction), HNSW indexing (150x faster search), caching, and batch operations. Use when optimizing memory usage, improving search speed, or scaling to millions of vectors.
日本語の概要は準備中です。原文の説明を表示しています。