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PR Jangler adversarial fix-plan validator. Use when the orchestrator dispatches AdversarialCheck on a per-PR fix-plan, or when the user runs 'prj-validate-adversarial' for manual debug.
기본적으로 소스를 먼저 확인하는 Prompt가 선택됩니다. 직접 명령으로 전환하거나 로컬 사본을 다운로드할 수도 있습니다.
설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
직접 명령은 검토 Prompt를 거치지 않습니다. 실행하기 전에 소스를 확인하세요.
npx skills add https://github.com/delorenj/pr-jangler --skill prj-validate-adversarial명령은 한 줄로 유지됩니다. 복사하기 전에 가로로 스크롤해 전체 내용을 확인하세요.
로컬 사본을 원하시나요? SkillsMP에서 현재 제공할 수 있는 파일을 다운로드하세요.
SOC 직업 분류 기준
SKILL.md 표시 중
| name | prj-validate-adversarial |
| description | PR Jangler adversarial fix-plan validator. Use when the orchestrator dispatches AdversarialCheck on a per-PR fix-plan, or when the user runs 'prj-validate-adversarial' for manual debug. |
This skill is the worst-case guard rail of the PR Jangler module. One invocation reviews a single per-PR fix-plan from a structurally separate context: it loads prs/{n}/fix-plan.md, prs/{n}/verification.md, and prs/{n}/review.md, runs the full project regression suite against the fix branch, then evaluates a six-item adversarial checklist with reject as the default verdict. A pass advances the PR to FixImpl; a reject sends it back to FixPlan with structured concerns appended; two consecutive rejects on the same plan, or any new regression in the full test suite, escalate to PleaseAdvise.
Act as a skeptical adversarial reviewer. You did NOT plan this fix. You do NOT carry the planner's framing. Treat suspicion as default mental mode and require evidence, not plausibility.
scripts/run.py) resolve from the skill root.{project-root}/... resolves from the project working directory.[modules.prj] in {project-root}/_bmad/config.toml.prj-orchestrator's state_io module (imported via sys.path); this skill never touches state.json directly.Load configuration from {project-root}/_bmad/config.toml (the [modules.prj] block). Required key: prj_repo. Optional: (auto-detected from the repo otherwise). If is missing, exit early with status and a clear run-log entry.
prj_test_runnerprj_repomisconfiguredExecute the validation:
python3 scripts/run.py --pr <N>
Flags:
--pr <N> (required) PR number whose fix-plan to validate--dry-run skip regression suite and state writes; emit the would-be verdict skeleton--verbose emit progress to stderr--project-root <path> override autodetectSee python3 scripts/run.py --help for full detail.
The actual six-item adversarial reasoning is an LLM task, not a script task. The flow is:
scripts/run.py gathers inputs: it reads the per-PR cache documents, runs the regression suite via scripts/regression_run.py, and assembles a context bundle.regression_run.py reports any regressions (a previously-passing test now failing on the fix branch), the script short-circuits to verdict: reject with item: regressions, passes: false and writes adversarial.md directly. This is the hard structural gate. The LLM is NOT consulted; structural gates always win.assets/prompt-adversarial.md and the gathered context, and produces a JSON response covering all six checklist items.scripts/run.py --finalize <response-path> (or pipes via stdin), which scripts/checklist_io.py validates and scripts/adversarial_io.py persists.Three Python modules, single concerns. The LLM activation context exists so the orchestrator's Skill-tool dispatch resolves cleanly when AdversarialCheck fires.
| Concern | Lives in |
|---|---|
| Shared state I/O (atomic load, validate, save, runlog) | state_io (imported from prj-orchestrator/scripts) |
| Regression-suite execution and gating | scripts/regression_run.py |
| Adversarial-response structural validation | scripts/checklist_io.py |
| Verdict persistence, retry counter, state transitions | scripts/adversarial_io.py |
| Orchestration: config, gather, dispatch, runlog | scripts/run.py |
| Adversarial reasoning prompt (LLM-facing) | assets/prompt-adversarial.md |
The adversarial prompt is intentionally stored as a separate asset and not inlined here. This enforces structural separation from prj-plan-fix: the planner's framing never leaks into the validator, and the prompt is auditable as a versioned artifact.
checklist_io.py rejects any response missing or misnaming an item.
test_validity — does the failing test demonstrate the alleged bug, or merely the proposed fix's own logic?scope — does the diff change anything beyond fixing the bug?side_effects — does the fix touch shared utilities, public APIs, or configs?regressions — full project test suite must show zero new failures on the fix branch. STRUCTURAL HARD GATE; auto-reject on any new failure.ac_alignment — does the fix align with the PR's stated acceptance criteria, not just the requesting comment?worst_case_probe — what breaks if we do NOT apply the fix? Is the bug actually load-bearing?Each item must produce {passes: bool, finding: str}. A single passes: false is grounds for reject. See assets/prompt-adversarial.md for the full adversarial prompt and pass criteria.
Reads from:
{project-root}/_bmad/config.toml (config: prj_repo, prj_test_runner){project-root}/_bmad-output/pr-workflow/state.json (current phase + retry counter){project-root}/_bmad-output/pr-workflow/prs/{n}/fix-plan.md{project-root}/_bmad-output/pr-workflow/prs/{n}/verification.md{project-root}/_bmad-output/pr-workflow/prs/{n}/review.mdWrites to:
{project-root}/_bmad-output/pr-workflow/state.json (via state_io.save_state, atomic) — phase transition + adversarial_reject_count bookkeeping{project-root}/_bmad-output/pr-workflow/prs/{n}/adversarial.md — full verdict report with checklist findings and regression summary{project-root}/_bmad-output/pr-workflow/logs/{YYYY-MM-DD}.jsonl (append-only run-log)| Verdict | Next phase | Side effects |
|---|---|---|
pass | FixImpl | next_action = {skill: "prj-implement-fix"}; adversarial_reject_count reset to 0 |
reject (first attempt on this plan) | FixPlan | next_action = {skill: "prj-plan-fix"}; adversarial_reject_count incremented; concerns appended to fix-plan context for the redo |
reject (second consecutive) | PleaseAdvise | Same as escalate |
escalate | PleaseAdvise | next_action = null; adversarial_reject_count reset to 0 |
The two-reject-then-escalate rule is enforced in adversarial_io.py, not left to the LLM. This prevents an infinite replan loop on a fundamentally flawed plan.
regression_run.py; the LLM cannot override it.prj-plan-fix. This skill runs in a separate invocation context. The adversarial prompt is written from a skeptical persona and lives in assets/prompt-adversarial.md. It does NOT inherit the planner's framing.state_io.save_state. Direct writes to state.json are forbidden.After install, smoke-test by validating the response-structure path with no real PR (no fix-plan needed):
python3 scripts/checklist_io.py --check '{"verdict": "pass", "findings": []}'
Expected: exit code 2 with a status: "invalid" JSON entry describing the missing checklist items.
Run unit tests (no subprocess shell-outs to the real test runner; all external calls mocked):
python3 -m unittest discover scripts/tests