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…

MITAuto-check passedTesting & QA

Install Qe Court

skills CLI
$ npx skills add proffesor-for-testing/agentic-qe --skill qe-court -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install proffesor-for-testing/agentic-qe qe-court --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/proffesor-for-testing/agentic-qe.git skills-src && mkdir -p .claude/skills && cp -r skills-src/assets/skills/qe-court .claude/skills/qe-court && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
qe-court
GitHub stars
495
Token cost
~3.2k tokens
SKILL.md length
1,368 words
Files
9 (incl. scripts)
Skills in repo
93
Repo updated
First seen
Licence
MIT

At a glance

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…

  • Works in 3 steps: ≥2 distinct vendors across the panel —… → Jury provider ∉ {writer, defense} — no… → All calls routed through ProviderManager…
  • You want more than one reviewers opinion on whether something is safe to ship: pre-merge gating
  • SKILL.md covers Purpose, When to convene the court, The court roster (composes… and Model routing (configurable —…, plus 9 more sections
  • Runs TypeScript scripts from its folder; calls codex

What it does

Qe Court is an agent skill from proffesor-for-testing/agentic-qe. 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…

Its SKILL.md is about 3.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 13 other files, including scripts (for example `config-schema.json`, `config.json` and `evals/fixtures/seeded-mutant-delivery/README.md`).

It sits in Testing & QA, covering Test generation and Feature launches and release readiness. The repository describes itself as: Agentic QE Fleet is an open-source AI-powered QA/QE platform designed for use with Coding Agents (works best with Claude Code) featuring specialized agents and skills to support… The licence is MIT.

When your agent uses it

  • You want more than one reviewers opinion on whether something is safe to ship: pre-merge gating
  • Release go/no-go
  • Catching a too-easy PASS
  • Any is this actually done? decision where a shallow approval is a risk

Example prompts

  • “is this actually done?”
  • “/qe-court”

Requirements

  • Node.js

Workflow steps

3 steps, taken from the first numbered list in SKILL.md.

  1. ≥2 distinct vendors across the panel — Claude / Cognitum / GPT-via-Codex — not just tiers.
  2. Jury provider ∉ {writer, defense} — no model grades its own or its writer's output.
  3. All calls routed through ProviderManager → ADR-123 budget cap + receipts.

What it can do on your machine

Read from SKILL.md and the folder at commit 1363bc7. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/ (TypeScript), which the agent can run.

    Shell commands in SKILL.md call:

    • codex

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Qe Court loads about 3.2k tokens when it runs. Until then it costs about 169 tokens; SKILL.md has 1,368 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~169
When it runs · the whole SKILL.md, loaded when a task matches
~3.2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from proffesor-for-testing/agentic-qe at commit 1363bc7, republished under its MIT licence (© proffesor-for-testing). 1,368 words, ~3,162 tokens.

Download SKILL.mdSave it as .claude/skills/qe-court/SKILL.md (or your agent's skills folder). This skill also uses 8 other files; get the full folder from GitHub.
name
qe-court
description
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.
trust_tier
3
validation.schema_path
schemas/output.json
validation.validator_path
scripts/validate-config.json
validation.eval_path
evals/qe-court.yaml
validation.status
passing
validation.passRate
1
validation.criticalPassRate
1
validation.lastValidated
2026-07-18

QE-Court: Adversarial Review as a Verdict

Purpose

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.

When to convene the court

  • Pre-merge gate on a risky PR or diff
  • Release go/no-go ("deployment readiness with a jury")
  • You got a PASS that felt too easy and want it stress-tested
  • A test suite claims coverage you don't trust (does it kill mutants?)
  • Any high-stakes "is this actually done?" call

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.

The court roster (composes existing skills/agents — do NOT reimplement critics)

RoleWhoJob
Defensewriter model (summarizer)States the case-FOR-ship from the evidence. Never grades.
Prosecutionqe-devils-advocate, brutal-honesty-review, sherlock-review, qe-security-scanner, qe-mutation-tester, codex exec reviewEach files CHARGES against the delivery, with its own probe set, blind to the others until filing.
Blind refutersrc/verification/adversarial-verifyTries to KILL weak charges (default-refuted-if-uncertain).
Jurytwo-gate LLM-judge (ADR-119), cross-modelWeighs surviving charges → verdict + (optional) score.
Deeper reviewerhigher effort/model tier of any prosecutorThe overturn round.
Judgeyou (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; see qcsd-development-swarm.)

Model routing (configurable — this is the point of the court)

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.

StepDefault provider / tierWhy
Defenseclaude-code (default) or cognitum-low (may equal writer)Cheap; states the case, never grades. Must differ in vendor from the jury
Prosecutor — devils-advocatecognitum-midGap/assumption hunting
Prosecutor — brutal-honestyclaude-code (Opus/Sonnet)Rigor lens, different family from jury
Prosecutor — sherlockcognitum-highDeductive/root-cause needs a strong model
Prosecutor — security-scannerSAST tool + cognitum-midDeterminism where possible
Prosecutor — mutationmutation tool + local/boosterTest-adequacy is mechanical
Prosecutor — codex-reviewcodex (ChatGPT sub)Cross-vendor GPT brain — true writer≠juror; ≈$0
Jury (two-gate judge)cognitum-high or Opus, provider ≠ writerMust not grade its own family's output
Deeper reviewerhighest tier / best-of-N @ higher effortEscalation 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):

  1. ≥2 distinct vendors across the panel — Claude / Cognitum / GPT-via-Codex — not just tiers.
  2. Jury provider ∉ {writer, defense} — no model grades its own or its writer's output. Vendor is compared coarsely: cognitum-low and cognitum-high are the same vendor, so pairing them across defense and jury is a violation, not a diverse panel.
  3. All calls routed through 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.

The protocol

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 states (three-valued — never a bare pass/fail)

VerdictMeaningTrigger
SHIPSurvived the overturn roundNo fatal charge survived K deeper rounds
REMANDFixable charges — back to authorNon-fatal charges survived; delivery is close
BLOCKA fatal charge survived≥1 fatal charge reproduced and not refuted

Self-learning — the court feeds the flywheel (ADR-124 M0.B)

A verdict is not the end; it is training signal. After each court run:

  1. Sign the court record → a flywheel receipt. Use the ADR-118 signer (src/learning/qe-flywheel/receipt.ts createSigner / platform-signer.ts, persisted via receipt-store.ts). The verdict + surviving charges are the body.
  2. Each reproduced, surviving charge → a 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).
  3. An overturned SHIP is the highest-value signal there is — persist {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.
  4. Retrieval-augment the next panel: seed each prosecutor's probe set with the HNSW-nearest prior charges for similar deliveries (qe_pattern_embeddings).

All writes are appends to existing stores — never destructive to memory.db.

Show full SKILL.md (536 more words)Show less

Improvement over time (ADR-124 M0.C)

  • Probe-set promotion: track each probe's historical mutant-kill rate; promote high-kill probes, retire dead ones (stored under a qe-court/probes namespace).
  • DoE-gated scoring: emit a numeric score ONLY if its rubric passes the ADR-122 ANOVA screen (it must actually discriminate). Otherwise report the verdict class + charges, no number — never a noise "91/100".
  • Learnable overturn depth K: start K=2; learn per-domain the depth at which new charges stop appearing (the empirical loop-until-dry tail).

Anti-collusion invariants (enforce these or it isn't a court)

  1. Writer ≠ any juror. 2. Prosecutors file blind. 3. Overturn is asymmetric (SHIP must survive escalation; BLOCK needs one surviving fatal charge). 4. No un-validated scores.

How to run it (today)

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:

  1. Read config.json for the panel + routing + overturnDepth, then validate the panel before seating it — this step is not optional:

    ts
    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.

  2. 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.

  3. Collect charges → run the blind-refuter kill round (adversarial-verify).

  4. Jury (two-gate judge) → verdict. If SHIP, run the overturn loop to overturnDepth.

  5. Emit the signed court record; persist learning per the section above.

  6. Present the strongest case FOR and AGAINST to the human judge.

Output: the court record

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."

Trust tier

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.

  • Reference implementation of ADR-124; hosted sibling is /v1/qe/verdict (Cognitum, planned).
  • Prosecutors: /brutal-honesty-review, /sherlock-review, qe-devils-advocate agent, codex exec review.
  • Verification core: src/verification/adversarial-verify. Signer: src/learning/qe-flywheel/receipt.ts.
  • Jury/rigor: ADR-117 (frozen anchor), ADR-119 (two-gate judge), ADR-121 (provenance), ADR-122 (DoE).
  • Contrast: /code-review, /pr-review (single-lens); qcsd-cicd-swarm (phase gate, not adversarial court).

© proffesor-for-testing, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 8 other files (scripts) in assets/skills/qe-court of proffesor-for-testing/agentic-qe.

  • SKILL.md
  • config-schema.json
  • config.json
  • evals/fixtures/seeded-mutant-delivery/README.md
  • evals/fixtures/seeded-mutant-delivery/budget.test.ts
  • evals/fixtures/seeded-mutant-delivery/budget.ts
  • evals/qe-court.yaml
  • schemas/output.json
  • scripts/validate-config.json

Open the folder on GitHubat commit 1363bc7

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Risk Based Testingpetrkindlmann/qa-skills170—~5.3kAutomated safety check: PassMIT
Quality Engineering Zephyr Coverage AnalysisHoangNguyen0403/agent-skills-standard572—~589Automated safety check: PassMIT
Test Casesagutinbaigo28/financial-agent-api1281 repos~1.8kAutomated safety check: PassMIT

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Questions about Qe Court

What does Qe Court do?

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…. Qe Court is an agent skill from proffesor-for-testing/agentic-qe. 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.

When should I use Qe Court?

Qe Court fits situations like: you want more than one reviewers opinion on whether something is safe to ship: pre-merge gating; release go/no-go; catching a too-easy PASS; any is this actually done? decision where a shallow approval is a risk.

How do I install Qe Court in Claude Code?

Run `npx skills add proffesor-for-testing/agentic-qe --skill qe-court -a claude-code`. Or copy the skill folder (assets/skills/qe-court in proffesor-for-testing/agentic-qe) into .claude/skills/qe-court in your project. Claude Code loads it when a task matches its description.

How do I install Qe Court in Codex?

Run `npx skills add proffesor-for-testing/agentic-qe --skill qe-court -a codex`. Or copy the skill folder (assets/skills/qe-court in proffesor-for-testing/agentic-qe) into .agents/skills/qe-court in your project. Codex loads it when a task matches its description.

Can I use Qe Court in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add proffesor-for-testing/agentic-qe --skill qe-court -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/qe-court, .gemini/skills/qe-court, .github/skills/qe-court and .opencode/skills/qe-court in your project.

What does Qe Court need to run?

Going by SKILL.md and its folder, Qe Court needs TypeScript for the scripts in its folder and the command-line tools its instructions call (codex). Our summary lists: Node.js.

Does Qe Court access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Qe Court safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Qe Court use?

Qe Court is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Qe Court use?

About 3.2k tokens (SKILL.md is roughly 13k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Qe Court?

Skills that share tags, products or a category with Qe Court: Test Planning (petrkindlmann/qa-skills, 170 stars), QA Metrics (petrkindlmann/qa-skills, 170 stars), Risk Based Testing (petrkindlmann/qa-skills, 170 stars) and Quality Engineering Zephyr Coverage Analysis (HoangNguyen0403/agent-skills-standard, 572 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Qe Court?

proffesor-for-testing (a GitHub user) maintains it in proffesor-for-testing/agentic-qe, which has 495 GitHub stars. The repository holds 93 skills in this directory. The repository was last updated on October 9, 2026.

Source: proffesor-for-testing/agentic-qe on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.