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Agent Skill · 研究检索

verification-loop-construction(验证循环构建)

verification-loop-construction 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

verification-loop-construction 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为只读;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 62,819。

总安装 326周安装 14GitHub Stars 113下载 114核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:verification-loop-construction(验证循环构建)
来源仓库:https://github.com/datadrivenconstruction/ddc_skills_for_ai_agents_in_construction
仓库路径:skills/verification-loop-construction
安装命令:
npx skills add https://github.com/datadrivenconstruction/ddc_skills_for_ai_agents_in_construction --skill verification-loop-construction
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/datadrivenconstruction/ddc_skills_for_ai_agents_in_construction --skill verification-loop-construction

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

用于查找、检索和筛选相关信息,适合快速定位候选结果。适用于 Codex、Claude、Cursor 等宿主的环境,支持关键词和来源线索搜索。通过构造验证管道自动执行多阶段检查,输出整体状态和建议。安装前建议确认权限范围和命令执行风险。

verification-loop-construction 属于研究检索类 Skill,可作为该场景下的辅助能力补充。可能触发联网或文件读写,需评估维护状态后再使用。

来源仓库内路径:skills/verification-loop-construction

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/datadrivenconstruction/ddc_skills_for_ai_agent…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

verification-loop-construction 怎么安装?

在终端执行 npx skills add https://github.com/datadrivenconstruction/ddc_skills_for_ai_agents_in_const…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

verification-loop-construction 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

verification-loop-construction 需要什么权限?

权限级别是只读。该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

verification-loop-construction 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

verification-loop-construction 用的人多吗?

公开数据是累计安装 326 次,近一周安装 14 次,下载 114 次,GitHub 113 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

verification-loop-construction 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。
  • 标注为只读权限,试用阶段不容易误改本地文件。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 只想先试试效果、不希望它改动本地文件的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
verification-loop-construction

验证循环构建 · 本页

326113只读未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Verification Loop for Construction Automation

A systematic verification framework ensuring quality of construction automation outputs before delivery or deployment.

When to Use

Invoke this skill:

  • After generating cost estimates
  • After creating or updating schedules
  • After processing BIM/CAD data
  • After generating reports (daily, weekly, monthly)
  • After running data pipelines
  • Before submitting documents to clients
  • Before deploying automation workflows

Verification Phases

Phase 1: Data Integrity Check

def verify_data_integrity(output: dict) -> VerificationResult:
    """Check data completeness and consistency"""

    checks = []

    # Completeness check
    required_fields = get_required_fields(output['type'])
    missing = [f for f in required_fields if f not in output]
    checks.append({
        'name': 'Completeness',
        'status': 'PASS' if not missing else 'FAIL',
        'details': f'Missing fields: {missing}' if missing else 'All required fields present'
    })

    # Consistency check
    inconsistencies = find_inconsistencies(output)
    checks.append({
        'name': 'Consistency',
        'status': 'PASS' if not inconsistencies else 'WARN',
        'details': inconsistencies or 'No inconsistencies found'
    })

    # Referential integrity
    broken_refs = check_references(output)
    checks.append({
        'name': 'Referential Integrity',
        'status': 'PASS' if not broken_refs else 'FAIL',
        'details': f'Broken references: {broken_refs}' if broken_refs else 'All references valid'
    })

    return VerificationResult(checks)
Data Integrity Checklist
  • All required fields populated
  • No duplicate records
  • Foreign keys resolve correctly
  • Date formats consistent
  • Currency values formatted correctly
  • Units of measure standardized

Phase 2: Business Logic Verification

def verify_business_logic(output: dict) -> VerificationResult:
    """Verify construction-specific business rules"""

    checks = []

    # Cost estimate checks
    if output['type'] == 'cost_estimate':
        # Verify totals match line items
        calculated_total = sum(item['amount'] for item in output['line_items'])
        declared_total = output['total']
        variance = abs(calculated_total - declared_total)

        checks.append({
            'name': 'Total Accuracy',
            'status': 'PASS' if variance < 0.01 else 'FAIL',
            'details': f'Calculated: {calculated_total}, Declared: {declared_total}'
        })

        # Verify markup applied correctly
        for item in output['line_items']:
            expected_markup = item['base_cost'] * (1 + item['markup_rate'])
            if abs(item['amount'] - expected_markup) > 0.01:
                checks.append({
                    'name': f'Markup Check - {item["id"]}',
                    'status': 'FAIL',
                    'details': f'Expected: {expected_markup}, Got: {item["amount"]}'
                })

    # Schedule checks
    if output['type'] == 'schedule':
        # Verify dependencies
        for task in output['tasks']:
            for pred_id in task.get('predecessors', []):
                pred = find_task(output['tasks'], pred_id)
                if pred and pred['end_date'] > task['start_date']:
                    checks.append({
                        'name': f'Dependency Violation - {task["id"]}',
                        'status': 'FAIL',
                        'details': f'Task starts before predecessor {pred_id} ends'
                    })

        # Verify resource allocation
        resource_conflicts = find_resource_conflicts(output['tasks'])
        checks.append({
            'name': 'Resource Conflicts',
            'status': 'PASS' if not resource_conflicts else 'WARN',
            'details': resource_conflicts or 'No resource conflicts'
        })

    return VerificationResult(checks)
Business Logic Checklist

For Cost Estimates:

  • Line item totals = declared subtotals
  • Subtotals + markups = grand total
  • Tax calculations correct
  • Contingency applied consistently
  • Unit prices within expected ranges
  • Quantities match QTO

For Schedules:

  • Dependencies respected (no backwards links)
  • Critical path calculated correctly
  • No resource over-allocation
  • Milestones properly dated
  • Working days/calendar correct
  • Float values logical

For BIM Data:

  • Element counts match expected
  • Property values within ranges
  • Spatial relationships valid
  • Level associations correct
  • Classification codes valid

Phase 3: Format & Standards Compliance

def verify_standards_compliance(output: dict) -> VerificationResult:
    """Verify compliance with construction standards"""

    checks = []

    # CSI classification check
    if 'csi_codes' in output:
        invalid_codes = []
        for code in output['csi_codes']:
            if not validate_csi_code(code):
                invalid_codes.append(code)

        checks.append({
            'name': 'CSI Code Validation',
            'status': 'PASS' if not invalid_codes else 'WARN',
            'details': f'Invalid codes: {invalid_codes}' if invalid_codes else 'All codes valid'
        })

    # CWICR mapping check
    if output.get('cwicr_mapped'):
        unmapped = [item for item in output['items'] if not item.get('cwicr_id')]
        checks.append({
            'name': 'CWICR Mapping',
            'status': 'PASS' if not unmapped else 'WARN',
            'details': f'{len(unmapped)} items unmapped' if unmapped else 'All items mapped'
        })

    # Document format check
    if output['type'] == 'report':
        format_issues = validate_report_format(output)
        checks.append({
            'name': 'Report Format',
            'status': 'PASS' if not format_issues else 'WARN',
            'details': format_issues or 'Format compliant'
        })

    return VerificationResult(checks)
Standards Compliance Checklist
  • CSI MasterFormat codes valid (6-digit)
  • UniFormat codes valid (if used)
  • CWICR mappings present
  • ISO dates (YYYY-MM-DD)
  • Currency format consistent
  • Measurement units consistent (metric/imperial)

Phase 4: Output Quality Check

def verify_output_quality(output: dict) -> VerificationResult:
    """Check output quality and presentation"""

    checks = []

    # Formatting check
    if output['format'] == 'excel':
        checks.extend([
            {
                'name': 'Column Headers',
                'status': check_headers_present(output),
                'details': 'Headers in first row'
            },
            {
                'name': 'Number Formatting',
                'status': check_number_format(output),
                'details': 'Currencies and percentages formatted'
            },
            {
                'name': 'Print Area',
                'status': check_print_area(output),
                'details': 'Print area set for clean output'
            }
        ])

    if output['format'] == 'pdf':
        checks.extend([
            {
                'name': 'Page Layout',
                'status': check_page_layout(output),
                'details': 'Margins and orientation correct'
            },
            {
                'name': 'Images Rendered',
                'status': check_images(output),
                'details': 'All images/charts visible'
            },
            {
                'name': 'Fonts Embedded',
                'status': check_fonts(output),
                'details': 'Fonts embedded for portability'
            }
        ])

    # Data visualization check
    if 'charts' in output:
        for chart in output['charts']:
            checks.append({
                'name': f'Chart - {chart["title"]}',
                'status': validate_chart(chart),
                'details': 'Labels, legends, and data visible'
            })

    return VerificationResult(checks)
Output Quality Checklist
  • Headers/footers present
  • Page numbers correct
  • Company branding applied
  • Charts readable
  • Tables properly aligned
  • Links/references working

Phase 5: Cross-Reference Validation

def verify_cross_references(output: dict, sources: list) -> VerificationResult:
    """Validate output against source data"""

    checks = []

    for source in sources:
        # Compare key metrics
        metrics = extract_comparable_metrics(output, source)

        for metric_name, (output_val, source_val) in metrics.items():
            variance_pct = abs(output_val - source_val) / source_val * 100 if source_val else 0

            status = 'PASS'
            if variance_pct > 5:
                status = 'WARN'
            if variance_pct > 10:
                status = 'FAIL'

            checks.append({
                'name': f'{metric_name} vs {source["name"]}',
                'status': status,
                'details': f'Output: {output_val}, Source: {source_val}, Variance: {variance_pct:.1f}%'
            })

    return VerificationResult(checks)
Cross-Reference Checklist
  • QTO matches BIM model
  • Estimate matches specifications
  • Schedule aligns with estimate
  • Budget matches contract
  • Progress matches field data
  • Actuals match projections (within tolerance)

Verification Report Format

After running all phases, produce a verification report:

═══════════════════════════════════════════════════════════════
                    VERIFICATION REPORT
═══════════════════════════════════════════════════════════════

Output Type:    Cost Estimate
Project:        Downtown Office Tower
Generated:      2026-01-24 14:30:00
Verified By:    DDC Verification Loop v1.0

───────────────────────────────────────────────────────────────
PHASE 1: DATA INTEGRITY
───────────────────────────────────────────────────────────────
✓ Completeness      PASS    All required fields present
✓ Consistency       PASS    No inconsistencies found
✓ Referential       PASS    All references valid

───────────────────────────────────────────────────────────────
PHASE 2: BUSINESS LOGIC
───────────────────────────────────────────────────────────────
✓ Total Accuracy    PASS    Calculated: $1,523,456.78, Declared: $1,523,456.78
✓ Markup Check      PASS    All markups applied correctly
⚠ Range Check       WARN    3 items outside typical ranges

───────────────────────────────────────────────────────────────
PHASE 3: STANDARDS COMPLIANCE
───────────────────────────────────────────────────────────────
✓ CSI Codes         PASS    All codes valid
✓ CWICR Mapping     PASS    156/156 items mapped
✓ Unit Standards    PASS    All units metric

───────────────────────────────────────────────────────────────
PHASE 4: OUTPUT QUALITY
───────────────────────────────────────────────────────────────
✓ Excel Format      PASS    Headers, formatting correct
✓ Charts            PASS    All visualizations rendered
✓ Print Ready       PASS    Print area configured

───────────────────────────────────────────────────────────────
PHASE 5: CROSS-REFERENCE
───────────────────────────────────────────────────────────────
✓ vs BIM QTO        PASS    Variance: 0.2%
✓ vs Historical     PASS    Within expected range
⚠ vs Budget         WARN    5.3% over budget baseline

═══════════════════════════════════════════════════════════════
                         SUMMARY
═══════════════════════════════════════════════════════════════

Total Checks:       18
Passed:             16
Warnings:           2
Failed:             0

OVERALL STATUS:     ✓ READY FOR DELIVERY

Recommendations:
1. Review items outside typical ranges (see Appendix A)
2. Discuss budget variance with PM before submission

═══════════════════════════════════════════════════════════════

Automated Verification Pipeline

class ConstructionVerificationPipeline:
    """Automated verification for construction outputs"""

    def __init__(self, output_type: str):
        self.output_type = output_type
        self.phases = self._get_phases_for_type(output_type)

    def verify(self, output: dict, sources: list = None) -> VerificationReport:
        results = []

        for phase in self.phases:
            phase_result = phase.execute(output, sources)
            results.append(phase_result)

            # Stop on critical failure
            if phase_result.has_critical_failure():
                break

        return VerificationReport(
            output_type=self.output_type,
            phases=results,
            overall_status=self._calculate_overall_status(results)
        )

    def _calculate_overall_status(self, results: list) -> str:
        if any(r.has_failures() for r in results):
            return 'NOT READY - FIX REQUIRED'
        if any(r.has_warnings() for r in results):
            return 'READY WITH WARNINGS'
        return 'READY FOR DELIVERY'

# Usage
pipeline = ConstructionVerificationPipeline('cost_estimate')
report = pipeline.verify(estimate_output, sources=[bim_model, specifications])
print(report.to_markdown())

Integration with DDC Workflows

This verification skill integrates with other DDC skills:

  1. Post-Estimation: Run after cost-estimation-* skills
  2. Post-QTO: Run after qto-report skill
  3. Post-Scheduling: Run after gantt-chart or 4d-simulation skills
  4. Post-Pipeline: Run after etl-pipeline skill

Continuous Verification Mode

For long automation sessions, run verification at checkpoints:

Recommended checkpoints:
- After processing each BIM model
- After generating each major section of estimate
- After completing each phase of schedule
- Before any external data submission

Command: /verify-construction

Quality is not negotiable in construction. Verify before you deliver.

平台分布

Codex

33.49%
按下载量换算38

Claude

30.71%
按下载量换算35

Cursor

19.59%
按下载量换算22

Gemini CLI

9.96%
按下载量换算11

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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