#!/usr/bin/env python3 from datetime import date from pathlib import Path from skill_ir_paths import find_skill_ir from skill_report_metrics import calculate_scorecard from skill_report_sources import ( extract_title, load_json, load_yaml, package_entries, parse_frontmatter, parse_sections, summarize_logic, summarize_usage, ) from skill_report_world_class import world_class_readiness, world_class_roadmap_item SCRIPT_INTERFACE = "internal-module" SCRIPT_INTERFACE_REASON = "Imported by render_skill_overview.py to build the v2 report data model." REPORT_NAV_V2 = [ {"label": "技能概述", "label_en": "Overview", "href": "overview"}, {"label": "总览指标", "label_en": "Metrics", "href": "metrics"}, {"label": "能力画像", "label_en": "Profile", "href": "capability"}, {"label": "原理结构", "label_en": "Principle", "href": "principle"}, {"label": "契约边界", "label_en": "Contract", "href": "contract"}, {"label": "质量评估", "label_en": "Quality", "href": "quality"}, {"label": "风险治理", "label_en": "Risk", "href": "risk"}, {"label": "包体资产", "label_en": "Assets", "href": "assets"}, {"label": "迭代路线", "label_en": "Roadmap", "href": "roadmap"}, ] def context_payload(intent: dict) -> dict: context = intent.get("context", {}) if isinstance(intent, dict) else {} return context if isinstance(context, dict) else {} def as_text_list(value) -> list[str]: if not value: return [] if isinstance(value, list): return [str(item).strip() for item in value if str(item).strip()] return [str(value).strip()] def compact_unique(items: list[str], limit: int = 6) -> list[str]: seen = set() result = [] for item in items: normalized = str(item).strip() if not normalized or normalized.lower() in seen: continue seen.add(normalized.lower()) result.append(normalized) if len(result) >= limit: break return result def derive_strengths(skill_dir: Path, metadata: dict) -> list[str]: strengths = ["触发面保持精简，并锚定在 frontmatter description。"] if (skill_dir / "reports" / "skill-ir.json").exists() or (skill_dir / "skill-ir" / "examples").exists(): strengths.append("已生成 Skill IR，核心语义可先于平台打包被审查和迁移。") if (skill_dir / "reports" / "compiled_targets.json").exists(): strengths.append("已生成目标编译报告，可审查 IR 到 OpenAI、Claude、generic 等目标契约的映射。") if (skill_dir / "reports" / "output_quality_scorecard.json").exists(): strengths.append("已生成 Output Eval Lab scorecard，可比较 with-skill 与 baseline 输出质量。") if (skill_dir / "reports" / "output_execution_runs.json").exists(): strengths.append("已生成 Output Execution Runs，可区分记录样本、命令执行和模型执行证据。") if (skill_dir / "reports" / "output_review_adjudication.json").exists(): strengths.append("已生成 Output Review Adjudication，可记录盲评决策、一致率和待评审项。") if (skill_dir / "reports" / "conformance_matrix.json").exists(): strengths.append("已生成 Runtime Conformance Matrix，可审查目标端消费能力。") if (skill_dir / "reports" / "security_trust_report.json").exists(): strengths.append("已生成 Security Trust Report，可审查脚本、依赖、secret 和包完整性风险。") if (skill_dir / "reports" / "skill_atlas.json").exists(): strengths.append("已生成 Skill Atlas，可审查多 Skill 组合中的路由冲突、过期资产和 owner 缺口。") if (skill_dir / "reports" / "registry_audit.json").exists(): strengths.append("已生成 Registry Audit，可审查版本、owner、license、checksum 和目标兼容矩阵。") if (skill_dir / "reports" / "install_simulation.json").exists(): strengths.append("已生成 Install Simulation，可审查 zip 解压、入口加载、接口元数据和 adapter 可读性。") if (skill_dir / "reports" / "adoption_drift_report.json").exists(): strengths.append("已生成 Adoption Drift Report，可把本地使用反馈转为下一轮迭代信号。") if (skill_dir / "reports" / "review_waivers.json").exists(): strengths.append("已生成 Review Waivers 台账，可记录 reviewer 对 warning 风险的批准、理由和到期时间。") if (skill_dir / "reports" / "review_annotations.json").exists(): strengths.append("已生成 Review Annotations 台账，可把 reviewer 批注挂到 gate、文件和行号。") if (skill_dir / "reports" / "review-studio.json").exists(): strengths.append("已生成 Review Studio 2.0，可在一页中查看 blocker、warning、证据路径和发布闸门。") if (skill_dir / "agents" / "interface.yaml").exists(): strengths.append("已打包 agents/interface.yaml，便于后续做跨平台适配。") if (skill_dir / "references").exists() and any((skill_dir / "references").iterdir()): strengths.append("长指导被拆到 references 中，入口文件可以保持轻量。") if (skill_dir / "scripts").exists() and any((skill_dir / "scripts").iterdir()): strengths.append("确定性辅助逻辑放在 scripts 中，而不是藏在提示词里。") if (skill_dir / "evals").exists() and any((skill_dir / "evals").iterdir()): strengths.append("包内包含可随 Skill 迁移的质量门禁或触发检查。") if metadata.get("maturity_tier"): strengths.append(f"生命周期元数据清晰，成熟度层级为 `{metadata['maturity_tier']}`。") return strengths[:6] def scenario_items(description: str, usage_steps: list[str], metadata: dict) -> list[str]: scenarios = [] if "workflow" in description.lower() or "流程" in description: scenarios.append("把重复流程沉淀为可复用的 agent skill。") if "prompt" in description.lower() or "提示" in description: scenarios.append("把分散提示词、对话记录或操作规范整理为稳定能力。") if metadata.get("maturity_tier") in {"production", "library", "governed"}: scenarios.append("团队复用前，需要明确触发边界、质量证据和维护责任。") if usage_steps: scenarios.append(f"用户说出类似需求时：{usage_steps[0]}") scenarios.append("已有原始资料，但还没有清晰输入、输出和后续迭代路径。") return compact_unique(scenarios, limit=4) def trigger_contract(interface_data: dict, description: str) -> dict: compatibility = interface_data.get("compatibility", {}) activation = compatibility.get("activation", {}) execution = compatibility.get("execution", {}) return { "description": description, "activation": activation.get("mode", "manual"), "execution": execution.get("context", "inline"), "shell": execution.get("shell", "bash"), } def io_contract(intent: dict, package_map: list[dict], description: str) -> dict: context = context_payload(intent) inputs = as_text_list(context.get("real_inputs")) or [ "用户提供的工作流、提示词、文档、记录或散乱笔记", "期望沉淀的复用场景、排除项、约束和质量标准", ] outputs = as_text_list(context.get("primary_output")) or [ "可路由的 SKILL.md", "agents/interface.yaml 元数据", "必要的 references、scripts、evals、reports 证据", ] if package_map: outputs.append(f"结构化 Skill 目录，共 {len(package_map)} 类关键资产。") if description and not outputs: outputs.append(f"围绕该能力边界交付：{description}") return { "inputs": compact_unique(inputs, limit=5), "outputs": compact_unique(outputs, limit=5), } def principle_nodes(system_model: dict) -> list[dict]: boundary = system_model.get("boundary_map", {}) if isinstance(system_model, dict) else {} loops = system_model.get("feedback_loops", []) if isinstance(system_model, dict) else [] drift = system_model.get("drift_watch", []) if isinstance(system_model, dict) else [] leverage = system_model.get("leverage_points", []) if isinstance(system_model, dict) else [] return [ {"title": "意图澄清", "body": boundary.get("owned_job", "先确认真实任务、输入材料和交付结果。")}, {"title": "边界路由", "body": "用 frontmatter description 决定是否触发，并写明相邻非目标。"}, {"title": "资产分层", "body": "把入口、参考、脚本、评估和报告拆到各自目录，避免 SKILL.md 膨胀。"}, { "title": "证据回路", "body": loops[0].get("response") if loops else "通过评估、报告和复盘把真实使用反馈变成下一轮改进。", }, { "title": "漂移观察", "body": drift[0].get("countermeasure") if drift else "持续观察触发漂移、输出漂移和治理漂移。", }, { "title": "杠杆升级", "body": leverage[0].get("move") if leverage else "优先改边界、触发和一个最小自修复检查。", }, ] def roadmap_items(iteration: dict, readiness: dict | None = None) -> list[dict]: directions = iteration.get("directions", []) if isinstance(iteration, dict) else [] items = [] evidence_item = world_class_roadmap_item(readiness or {}) if evidence_item: items.append(evidence_item) for item in directions[:3]: items.append( { "title": item.get("title", "下一步"), "why": item.get("why", "提升复用稳定性。"), "actions": item.get("actions", [])[:3], "unlocks": item.get("unlocks", ""), } ) if len(items) >= 3: break if items: return items return [ { "title": "收紧触发", "why": "先让 Skill 在正确场景被调用，再扩展资产。", "actions": ["增加正例、反例和近邻用例。", "压缩 frontmatter description。"], "unlocks": "更稳定的路由边界。", } ] def artifact_design_highlights(profile: dict) -> list[str]: primary = profile.get("primary_artifact", {}) highlights = [] if primary.get("direction"): highlights.append(primary["direction"]) highlights.extend(profile.get("quality_gates", [])[:3]) return highlights[:4] def prompt_quality_highlights(profile: dict) -> list[str]: highlights = [] primary = profile.get("primary_task_family", {}) complexity = profile.get("complexity", {}) if primary.get("label"): highlights.append(f"Primary prompt task family: {primary['label']}.") if complexity.get("band"): highlights.append(f"Complexity: {complexity['band']} — {complexity.get('reason', '')}") for item in profile.get("quality_matrix", [])[:2]: highlights.append(f"{item.get('label', 'Quality')}: {item.get('score', 'n/a')}/100.") return highlights[:4] def system_model_highlights(model: dict) -> list[str]: highlights = [] stability = model.get("stability", {}) if stability: highlights.append(f"Stability: {stability.get('band', 'unknown')} ({stability.get('score', 'n/a')}/100).") boundary = model.get("boundary_map", {}) if boundary.get("owned_job"): highlights.append(f"Owned job: {boundary['owned_job']}") for point in model.get("leverage_points", [])[:2]: if point.get("point"): highlights.append(f"Leverage: {point['point']} — {point.get('move', '')}") return highlights[:4] def capability_profile(manifest: dict, interface_data: dict, prompt_quality: dict) -> dict: maturity = manifest.get("maturity_tier", "scaffold") task_family = prompt_quality.get("primary_task_family", {}).get("label", "Skill workflow") execution = interface_data.get("compatibility", {}).get("execution", {}) adapter_targets = interface_data.get("compatibility", {}).get("adapter_targets", []) certainty = 72 if execution.get("context", "inline") == "inline" else 58 knowledge = 80 if prompt_quality.get("complexity", {}).get("band") in {"expert", "complex"} else 62 return { "archetype": manifest.get("skill_archetype", maturity), "task_family": task_family, "maturity": maturity, "trigger_strength": "手动触发 + description 路由", "reuse_scope": "跨平台" if len(adapter_targets) >= 2 else "本地复用", "matrix": {"execution_certainty": certainty, "knowledge_density": knowledge}, } def risk_governance(output_risk: dict, system_model: dict, scorecard: dict) -> dict: risk_names = [ ("误触发风险", "trigger_score"), ("输出漂移风险", "evidence_score"), ("证据不足风险", "evidence_score"), ("包体膨胀风险", "maintainability_score"), ("跨平台迁移风险", "portability_score"), ] risks = [] for index, (name, metric_key) in enumerate(risk_names): score = scorecard.get(metric_key, {}).get("score", 50) probability = max(1, min(3, 4 - round(score / 34))) impact = 3 if index in {0, 2, 4} else 2 risks.append( { "name": name, "impact": impact, "probability": probability, "signal": scorecard.get(metric_key, {}).get("reasons", ["证据不足"])[0], "response": "先补证据和边界，再增加包体复杂度。", } ) human_boundary = system_model.get("boundary_map", {}).get("human_judgment_boundary", []) return { "risks": risks, "risk_families": output_risk.get("risk_families", []), "human_judgment_boundary": human_boundary, } def quality_review( strengths: list[str], scorecard: dict, artifact_design: dict, prompt_quality: dict, system_model: dict, ) -> dict: gaps = [] for key, payload in scorecard.items(): if payload.get("score", 0) < 70: gaps.append(f"{payload.get('label', key)}需要补强：{payload.get('reasons', ['证据不足'])[0]}") return { "strengths": strengths, "gaps": gaps or ["当前关键证据较完整，优先保持轻量。"], "recommendations": [ "先改触发边界，再扩展工作流。", "只把重复且稳定的步骤沉淀为脚本。", "每次升级后重新生成报告并检查分数原因。", ], "artifact_design": { "design_system": artifact_design.get("design_system", "content-led editorial"), "highlights": artifact_design_highlights(artifact_design), }, "prompt_quality": { "overall_quality_score": prompt_quality.get("overall_quality_score", "n/a"), "highlights": prompt_quality_highlights(prompt_quality), }, "system_model": { "stability": system_model.get("stability", {}), "highlights": system_model_highlights(system_model), }, } def package_assets(package_map: list[dict]) -> dict: files = sum(item.get("file_count", 0) for item in package_map if item.get("kind") == "file") folders = [item for item in package_map if item.get("kind") == "folder"] distribution = [{"label": item["path"], "value": max(1, item.get("file_count", 1))} for item in package_map] return { "entries": package_map, "file_count": files + sum(item.get("file_count", 0) for item in folders), "folder_count": len(folders), "distribution": distribution, } def build_report_model(skill_dir: Path) -> dict: skill_dir = skill_dir.resolve() skill_text = (skill_dir / "SKILL.md").read_text(encoding="utf-8") frontmatter, body = parse_frontmatter(skill_text) sections = parse_sections(body) interface_data = load_yaml(skill_dir / "agents" / "interface.yaml") manifest = load_json(skill_dir / "manifest.json") intent = load_json(skill_dir / "reports" / "intent-confidence.json") artifact_design = load_json(skill_dir / "reports" / "artifact-design-profile.json") prompt_quality = load_json(skill_dir / "reports" / "prompt-quality-profile.json") system_model = load_json(skill_dir / "reports" / "system-model.json") output_risk = load_json(skill_dir / "reports" / "output-risk-profile.json") output_quality = load_json(skill_dir / "reports" / "output_quality_scorecard.json") output_execution = load_json(skill_dir / "reports" / "output_execution_runs.json") output_blind_review = load_json(skill_dir / "reports" / "output_blind_review_pack.json") output_review_kit = load_json(skill_dir / "reports" / "output_review_kit.json") output_review_adjudication = load_json(skill_dir / "reports" / "output_review_adjudication.json") benchmark_reproducibility = load_json(skill_dir / "reports" / "benchmark_reproducibility.json") conformance = load_json(skill_dir / "reports" / "conformance_matrix.json") runtime_permissions = load_json(skill_dir / "reports" / "runtime_permission_probes.json") trust_report = load_json(skill_dir / "reports" / "security_trust_report.json") skill_atlas = load_json(skill_dir / "reports" / "skill_atlas.json") registry_audit = load_json(skill_dir / "reports" / "registry_audit.json") package_verification = load_json(skill_dir / "reports" / "package_verification.json") install_simulation = load_json(skill_dir / "reports" / "install_simulation.json") upgrade_check = load_json(skill_dir / "reports" / "upgrade_check.json") adoption_drift = load_json(skill_dir / "reports" / "adoption_drift_report.json") review_waivers = load_json(skill_dir / "reports" / "review_waivers.json") review_annotations = load_json(skill_dir / "reports" / "review_annotations.json") world_class_evidence = load_json(skill_dir / "reports" / "world_class_evidence_plan.json") world_class_evidence_ledger = load_json(skill_dir / "reports" / "world_class_evidence_ledger.json") compiled_targets = load_json(skill_dir / "reports" / "compiled_targets.json") reference_synthesis = load_json(skill_dir / "reports" / "reference-synthesis.json") iteration = load_json(skill_dir / "reports" / "iteration-directions.json") name = frontmatter.get("name", skill_dir.name) skill_ir, skill_ir_path = find_skill_ir(skill_dir, name) description = frontmatter.get("description", "No description found.") title = extract_title(body, name.replace("-", " ").title()) display_name = interface_data.get("interface", {}).get("display_name", title) default_prompt = interface_data.get("interface", {}).get("default_prompt", "") logic_steps = summarize_logic(sections) usage_steps = summarize_usage(sections, default_prompt, description) package_map = package_entries(skill_dir) scorecard = calculate_scorecard(skill_dir) strengths = derive_strengths(skill_dir, manifest) trigger = trigger_contract(interface_data, description) io = io_contract(intent, package_map, description) principles = principle_nodes(system_model) readiness = world_class_readiness(world_class_evidence_ledger) roadmap = roadmap_items(iteration, readiness) metadata = { "canonical_format": interface_data.get("compatibility", {}).get("canonical_format", "agent-skills"), "targets": interface_data.get("compatibility", {}).get("adapter_targets", []), "maturity_tier": manifest.get("maturity_tier", "scaffold"), "skill_archetype": manifest.get("skill_archetype", manifest.get("maturity_tier", "scaffold")), "updated_at": manifest.get("updated_at", str(date.today())), } deliverables = [ "SKILL.md", "agents/interface.yaml", skill_ir_path or "reports/skill-ir.json", "reports/compiled_targets.md", "reports/output_quality_scorecard.md", "reports/conformance_matrix.md", "reports/security_trust_report.md", "reports/skill_atlas.html", "reports/registry_audit.md", "reports/package_verification.md", "reports/install_simulation.md", "reports/upgrade_check.md", "reports/adoption_drift_report.md", "reports/review_waivers.md", "reports/review_annotations.md", "reports/review-studio.html", "reports/skill-interpretation.html", "reports/skill-overview.html", ] if (skill_dir / "reports" / "runtime_permission_probes.md").exists(): insert_after = deliverables.index("reports/security_trust_report.md") + 1 deliverables.insert(insert_after, "reports/runtime_permission_probes.md") if (skill_dir / "reports" / "output_blind_review_pack.md").exists(): insert_after = deliverables.index("reports/output_quality_scorecard.md") + 1 deliverables.insert(insert_after, "reports/output_blind_review_pack.md") if (skill_dir / "reports" / "output_execution_runs.md").exists(): insert_after = deliverables.index("reports/output_quality_scorecard.md") + 1 deliverables.insert(insert_after, "reports/output_execution_runs.md") if (skill_dir / "reports" / "output_blind_answer_key.json").exists(): insert_after = deliverables.index("reports/output_blind_review_pack.md") + 1 if "reports/output_blind_review_pack.md" in deliverables else deliverables.index("reports/output_quality_scorecard.md") + 1 deliverables.insert(insert_after, "reports/output_blind_answer_key.json") if (skill_dir / "reports" / "output_review_kit.md").exists(): insert_after = deliverables.index("reports/output_blind_review_pack.md") + 1 if "reports/output_blind_review_pack.md" in deliverables else deliverables.index("reports/output_quality_scorecard.md") + 1 deliverables.insert(insert_after, "reports/output_review_kit.md") if (skill_dir / "reports" / "output_review_adjudication.md").exists(): insert_after = deliverables.index("reports/output_review_kit.md") + 1 if "reports/output_review_kit.md" in deliverables else deliverables.index("reports/output_quality_scorecard.md") + 1 deliverables.insert(insert_after, "reports/output_review_adjudication.md") if (skill_dir / "reports" / "benchmark_reproducibility.md").exists(): insert_after = deliverables.index("reports/output_review_adjudication.md") + 1 if "reports/output_review_adjudication.md" in deliverables else deliverables.index("reports/output_quality_scorecard.md") + 1 deliverables.insert(insert_after, "reports/benchmark_reproducibility.md") if (skill_dir / "reports" / "world_class_evidence_plan.md").exists(): insert_after = deliverables.index("reports/review_waivers.md") + 1 deliverables.insert(insert_after, "reports/world_class_evidence_plan.md") if (skill_dir / "reports" / "world_class_evidence_ledger.md").exists(): insert_after = ( deliverables.index("reports/world_class_evidence_plan.md") + 1 if "reports/world_class_evidence_plan.md" in deliverables else deliverables.index("reports/review_waivers.md") + 1 ) deliverables.insert(insert_after, "reports/world_class_evidence_ledger.md") skill_summary = { "name": name, "title": title, "display_name": display_name, "description": description, "maturity": metadata["maturity_tier"], "updated_at": metadata["updated_at"], "core_value": "把一次性经验沉淀为可复用、可评估、可迁移的 Skill 包体。", "audience": "Skill 作者、复用团队和后续 reviewer。", "deliverables": deliverables, "flow": ["输入材料", "Skill 包体", "可复用能力"], } contract = { "trigger": trigger, "inputs": io["inputs"], "outputs": io["outputs"], "should_trigger": scenario_items(description, usage_steps, manifest)[:3], "should_not_trigger": [ "只需要一次性回答、没有复用价值的临时请求。", "要求直接执行相邻任务，而不是沉淀或使用这个 Skill。", "缺少必要事实且用户不允许澄清的场景。", ], "boundary_cards": [ {"label": "Owned", "body": description}, {"label": "Adjacent", "body": "相邻任务需要先确认是否应转为独立 Skill。"}, {"label": "Excluded", "body": "不替代人工事实核查，也不静默扩大职责。"}, ], } synthesis = reference_synthesis.get("synthesis", {}).get("borrow_now", [])[:3] q_review = quality_review(strengths, scorecard, artifact_design, prompt_quality, system_model) report_contract = { "schema_version": "2.0", "html_report": "reports/skill-overview.html", "language": "zh-CN", "default_language": "zh-CN", "languages": ["zh-CN", "en"], "layout": "kami-white-audit-v2", "nav_labels": [item["label"] for item in REPORT_NAV_V2], "nav_labels_en": [item["label_en"] for item in REPORT_NAV_V2], } model = { "skill_summary": skill_summary, "scorecard": scorecard, "capability_profile": capability_profile(manifest, interface_data, prompt_quality), "principle_model": {"nodes": principles, "layers": ["入口层", "参考层", "脚本层", "评估层", "报告层"]}, "contract_boundary": contract, "quality_review": q_review, "risk_governance": risk_governance(output_risk, system_model, scorecard), "world_class_readiness": readiness, "package_assets": package_assets(package_map), "iteration_roadmap": {"items": roadmap}, "report_contract": report_contract, # Backward-compatible fields consumed by existing review tooling. "name": name, "title": title, "display_name": display_name, "description": description, "logic_steps": logic_steps, "usage_steps": usage_steps, "package_map": package_map, "strengths": strengths, "scenarios": scenario_items(description, usage_steps, manifest), "trigger_contract": trigger, "io_contract": io, "principles": principles, "roadmap": roadmap, "cards": [], "introduction": [ "这份报告用于快速理解新生成 Skill 的定位、原理、触发边界和交付内容。", "先确认重复任务、真实输入形态和可交付输出，再决定是否继续加 references、scripts 或 evals。", "如果需求仍然模糊，优先回到 intent dialogue 收紧边界，再扩展包体结构。", ], "benchmark_highlights": [], "skill_ir": { "schema_version": skill_ir.get("schema_version", ""), "source_path": skill_ir_path, "target_count": len(skill_ir.get("targets", [])), "trigger_samples": len(skill_ir.get("trigger_surface", {}).get("should_trigger", [])), "output_eval_cases": len(skill_ir.get("eval_plan", {}).get("output", [])), }, "compiled_targets": { "ok": compiled_targets.get("ok", False), "schema_version": compiled_targets.get("schema_version", ""), "summary": compiled_targets.get("summary", {}), "targets": [ { "target": item.get("target", ""), "status": item.get("status", ""), "adapter_mode": item.get("target_transform", {}).get("adapter_mode", ""), "degradation_strategy": item.get("target_transform", {}).get("degradation_strategy", ""), "native_surface": item.get("target_native_contract", {}).get("native_surface", ""), "permission_enforcement": item.get("target_native_contract", {}).get("permissions", {}).get("enforcement", ""), "generated_files": item.get("target_transform", {}).get("generated_files", []), "unsupported_features": item.get("unsupported_features", []), "warnings": item.get("warnings", []), } for item in compiled_targets.get("targets", []) if isinstance(item, dict) ], "failures": compiled_targets.get("failures", []), "warnings": compiled_targets.get("warnings", []), }, "output_quality": output_quality.get("summary", {}), "output_execution": { "ok": output_execution.get("ok", False), "summary": output_execution.get("summary", {}), "runner": output_execution.get("runner", {}), "failures": output_execution.get("failures", []), }, "output_blind_review": { "summary": output_blind_review.get("summary", {}), "seed": output_blind_review.get("seed", ""), "pair_count": output_blind_review.get("summary", {}).get("pair_count", 0), "answer_key_separate": output_blind_review.get("summary", {}).get("answer_key_separate", False), }, "output_review_kit": { "ok": output_review_kit.get("ok", False), "summary": output_review_kit.get("summary", {}), "artifacts": output_review_kit.get("artifacts", {}), "failures": output_review_kit.get("failures", []), }, "output_review_adjudication": { "ok": output_review_adjudication.get("ok", False), "summary": output_review_adjudication.get("summary", {}), "reviewer": output_review_adjudication.get("reviewer", ""), "reviewed_at": output_review_adjudication.get("reviewed_at", ""), "failures": output_review_adjudication.get("failures", []), }, "benchmark_reproducibility": { "ok": benchmark_reproducibility.get("ok", False), "summary": benchmark_reproducibility.get("summary", {}), "commit": benchmark_reproducibility.get("commit", ""), "missing_artifacts": benchmark_reproducibility.get("missing_artifacts", []), "limitations": benchmark_reproducibility.get("limitations", []), }, "runtime_conformance": conformance.get("summary", {}), "runtime_permissions": { "ok": runtime_permissions.get("ok", False), "summary": runtime_permissions.get("summary", {}), "expected_capabilities": runtime_permissions.get("expected_capabilities", []), "targets": [ { "target": item.get("target", ""), "status": item.get("status", ""), "assurance": item.get("assurance", ""), "native_enforcement": item.get("native_enforcement"), "metadata_fallback_explicit": item.get("metadata_fallback_explicit", False), "residual_risks": item.get("residual_risks", []), } for item in runtime_permissions.get("targets", []) if isinstance(item, dict) ], "failures": runtime_permissions.get("failures", []), }, "trust_security": trust_report.get("summary", {}), "skill_atlas": skill_atlas.get("summary", {}), "registry_distribution": { "ok": registry_audit.get("ok", False), "package": registry_audit.get("package", {}), "failures": registry_audit.get("failures", []), "warnings": registry_audit.get("warnings", []), }, "package_verification": { "ok": package_verification.get("ok", False), "summary": package_verification.get("summary", {}), "failures": package_verification.get("failures", []), "warnings": package_verification.get("warnings", []), }, "install_simulation": { "ok": install_simulation.get("ok", False), "summary": install_simulation.get("summary", {}), "failures": install_simulation.get("failures", []), "warnings": install_simulation.get("warnings", []), }, "upgrade_check": { "ok": upgrade_check.get("ok", False), "summary": upgrade_check.get("summary", {}), "upgrade_diff": upgrade_check.get("upgrade_diff", {}), "release_notes": upgrade_check.get("release_notes", []), "failures": upgrade_check.get("failures", []), "warnings": upgrade_check.get("warnings", []), }, "adoption_drift": { "ok": adoption_drift.get("ok", False), "summary": adoption_drift.get("summary", {}), "next_iteration_candidates": adoption_drift.get("next_iteration_candidates", []), "privacy_contract": adoption_drift.get("privacy_contract", {}), "failures": adoption_drift.get("failures", []), }, "review_waivers": { "ok": review_waivers.get("ok", False), "summary": review_waivers.get("summary", {}), "policy": review_waivers.get("policy", {}), "failures": review_waivers.get("failures", []), "warnings": review_waivers.get("warnings", []), }, "review_annotations": { "ok": review_annotations.get("ok", False), "summary": review_annotations.get("summary", {}), "annotations": review_annotations.get("annotations", [])[:8], "failures": review_annotations.get("failures", []), }, "world_class_evidence_plan": { "ok": world_class_evidence.get("ok", False), "summary": world_class_evidence.get("summary", {}), "tasks": world_class_evidence.get("tasks", [])[:8], "source_audit": world_class_evidence.get("source_audit", {}), }, "world_class_evidence_ledger": { "ok": world_class_evidence_ledger.get("ok", False), "summary": world_class_evidence_ledger.get("summary", {}), "entries": world_class_evidence_ledger.get("entries", [])[:8], "source_plan": world_class_evidence_ledger.get("source_plan", {}), }, "synthesis_highlights": synthesis, "artifact_design": q_review["artifact_design"], "prompt_quality": q_review["prompt_quality"], "system_model": q_review["system_model"], "metadata": metadata, } return model