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Agent Skill · 研究检索

data-lineage-tracker(数据沿袭跟踪器)

用于辅助数据整理、表格处理、CSV/Excel 分析、指标计算和图表准备。它适合让 Agent 清洗字段、汇总数据、发现异常、生成统计口径或把分析结果转成可读说明。使用时需要确认数据来源、字段含义和时间范围,避免把样本数据当全量事实;涉及敏感数据、导出文件或批量写回时,应先确认权限和脱敏边界。

data-lineage-tracker 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 62,606。

总安装 329周安装 14GitHub Stars 111下载 115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:data-lineage-tracker(数据沿袭跟踪器)
来源仓库:https://github.com/datadrivenconstruction/ddc_skills_for_ai_agents_in_construction
仓库路径:skills/data-lineage-tracker
安装命令:
npx skills add https://github.com/datadrivenconstruction/ddc_skills_for_ai_agents_in_construction --skill data-lineage-tracker
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 data-lineage-tracker

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。

追踪建筑数据在系统中的流转路径与变换过程。提供审计轨迹以满足合规要求与问题溯源需求。帮助理解变更对下游系统的影响范围。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。需记录各环节的数据转换逻辑与来源信息。

data-lineage-tracker 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/data-lineage-tracker

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

data-lineage-tracker 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。

data-lineage-tracker 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。

data-lineage-tracker 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。

data-lineage-tracker 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。

data-lineage-tracker 用的人多吗?

公开数据是累计安装 329 次,近一周安装 14 次,下载 115 次,GitHub 111 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。

data-lineage-tracker 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
data-lineage-tracker

数据沿袭跟踪器 · 本页

329111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

Data Lineage Tracker for Construction

Overview

Track the origin, transformations, and flow of construction data through systems. Provides audit trails for compliance, helps debug data issues, and ensures data governance.

Business Case

Construction projects require data accountability:

  • Audit Compliance: Know where every number came from
  • Issue Resolution: Trace data problems to their source
  • Change Impact: Understand what downstream systems are affected
  • Regulatory Requirements: Maintain data provenance for legal/insurance

Technical Implementation

from dataclasses import dataclass, field
from typing import List, Dict, Any, Optional, Set
from datetime import datetime
from enum import Enum
import json
import hashlib
import uuid

class TransformationType(Enum):
    EXTRACT = "extract"
    TRANSFORM = "transform"
    LOAD = "load"
    AGGREGATE = "aggregate"
    JOIN = "join"
    FILTER = "filter"
    CALCULATE = "calculate"
    MANUAL_EDIT = "manual_edit"
    IMPORT = "import"
    EXPORT = "export"

@dataclass
class DataSource:
    id: str
    name: str
    system: str
    location: str
    owner: str
    created_at: datetime

@dataclass
class TransformationStep:
    id: str
    transformation_type: TransformationType
    description: str
    input_entities: List[str]
    output_entities: List[str]
    logic: str  # SQL, Python, or description
    performed_by: str  # user or system
    performed_at: datetime
    parameters: Dict[str, Any] = field(default_factory=dict)

@dataclass
class DataEntity:
    id: str
    name: str
    source_id: str
    entity_type: str  # table, file, field, record
    created_at: datetime
    version: int = 1
    checksum: Optional[str] = None
    parent_entities: List[str] = field(default_factory=list)
    metadata: Dict[str, Any] = field(default_factory=dict)

@dataclass
class LineageRecord:
    id: str
    entity_id: str
    transformation_id: str
    upstream_entities: List[str]
    downstream_entities: List[str]
    recorded_at: datetime

class ConstructionDataLineageTracker:
    """Track data lineage for construction data flows."""

    def __init__(self, project_id: str):
        self.project_id = project_id
        self.sources: Dict[str, DataSource] = {}
        self.entities: Dict[str, DataEntity] = {}
        self.transformations: Dict[str, TransformationStep] = {}
        self.lineage_records: List[LineageRecord] = []

    def register_source(self, name: str, system: str, location: str, owner: str) -> DataSource:
        """Register a new data source."""
        source = DataSource(
            id=f"SRC-{uuid.uuid4().hex[:8]}",
            name=name,
            system=system,
            location=location,
            owner=owner,
            created_at=datetime.now()
        )
        self.sources[source.id] = source
        return source

    def register_entity(self, name: str, source_id: str, entity_type: str,
                       parent_entities: List[str] = None,
                       metadata: Dict = None) -> DataEntity:
        """Register a data entity (table, file, field)."""
        entity = DataEntity(
            id=f"ENT-{uuid.uuid4().hex[:8]}",
            name=name,
            source_id=source_id,
            entity_type=entity_type,
            created_at=datetime.now(),
            parent_entities=parent_entities or [],
            metadata=metadata or {}
        )
        self.entities[entity.id] = entity
        return entity

    def calculate_checksum(self, data: Any) -> str:
        """Calculate checksum for data verification."""
        if isinstance(data, str):
            content = data
        else:
            content = json.dumps(data, sort_keys=True, default=str)
        return hashlib.sha256(content.encode()).hexdigest()[:16]

    def record_transformation(self,
                             transformation_type: TransformationType,
                             description: str,
                             input_entities: List[str],
                             output_entities: List[str],
                             logic: str,
                             performed_by: str,
                             parameters: Dict = None) -> TransformationStep:
        """Record a data transformation."""
        transformation = TransformationStep(
            id=f"TRF-{uuid.uuid4().hex[:8]}",
            transformation_type=transformation_type,
            description=description,
            input_entities=input_entities,
            output_entities=output_entities,
            logic=logic,
            performed_by=performed_by,
            performed_at=datetime.now(),
            parameters=parameters or {}
        )
        self.transformations[transformation.id] = transformation

        # Create lineage records
        for output_id in output_entities:
            record = LineageRecord(
                id=f"LIN-{uuid.uuid4().hex[:8]}",
                entity_id=output_id,
                transformation_id=transformation.id,
                upstream_entities=input_entities,
                downstream_entities=[],
                recorded_at=datetime.now()
            )
            self.lineage_records.append(record)

            # Update downstream references for input entities
            for input_id in input_entities:
                for existing_record in self.lineage_records:
                    if existing_record.entity_id == input_id:
                        existing_record.downstream_entities.append(output_id)

        return transformation

    def trace_upstream(self, entity_id: str, depth: int = None) -> List[Dict]:
        """Trace all upstream sources of an entity."""
        visited = set()
        lineage = []

        def trace(eid: str, current_depth: int):
            if eid in visited:
                return
            if depth is not None and current_depth > depth:
                return

            visited.add(eid)

            entity = self.entities.get(eid)
            if not entity:
                return

            # Find transformations that produced this entity
            for record in self.lineage_records:
                if record.entity_id == eid:
                    transformation = self.transformations.get(record.transformation_id)
                    if transformation:
                        lineage.append({
                            'entity': entity.name,
                            'entity_id': eid,
                            'depth': current_depth,
                            'transformation': transformation.description,
                            'transformation_type': transformation.transformation_type.value,
                            'performed_at': transformation.performed_at.isoformat(),
                            'performed_by': transformation.performed_by,
                            'upstream': record.upstream_entities
                        })

                        for upstream_id in record.upstream_entities:
                            trace(upstream_id, current_depth + 1)

        trace(entity_id, 0)
        return sorted(lineage, key=lambda x: x['depth'])

    def trace_downstream(self, entity_id: str, depth: int = None) -> List[Dict]:
        """Trace all downstream dependencies of an entity."""
        visited = set()
        dependencies = []

        def trace(eid: str, current_depth: int):
            if eid in visited:
                return
            if depth is not None and current_depth > depth:
                return

            visited.add(eid)

            entity = self.entities.get(eid)
            if not entity:
                return

            # Find entities that use this entity
            for record in self.lineage_records:
                if eid in record.upstream_entities:
                    transformation = self.transformations.get(record.transformation_id)
                    if transformation:
                        dependencies.append({
                            'entity': self.entities[record.entity_id].name if record.entity_id in self.entities else record.entity_id,
                            'entity_id': record.entity_id,
                            'depth': current_depth,
                            'transformation': transformation.description,
                            'transformation_type': transformation.transformation_type.value
                        })

                        trace(record.entity_id, current_depth + 1)

        trace(entity_id, 0)
        return sorted(dependencies, key=lambda x: x['depth'])

    def get_entity_history(self, entity_id: str) -> List[Dict]:
        """Get complete history of changes to an entity."""
        history = []

        for record in self.lineage_records:
            if record.entity_id == entity_id:
                transformation = self.transformations.get(record.transformation_id)
                if transformation:
                    history.append({
                        'timestamp': transformation.performed_at.isoformat(),
                        'action': transformation.transformation_type.value,
                        'description': transformation.description,
                        'performed_by': transformation.performed_by,
                        'inputs': [
                            self.entities[eid].name if eid in self.entities else eid
                            for eid in record.upstream_entities
                        ]
                    })

        return sorted(history, key=lambda x: x['timestamp'])

    def impact_analysis(self, entity_id: str) -> Dict:
        """Analyze impact of changes to an entity."""
        downstream = self.trace_downstream(entity_id)

        impact = {
            'entity': self.entities[entity_id].name if entity_id in self.entities else entity_id,
            'total_affected': len(downstream),
            'affected_by_depth': {},
            'affected_entities': downstream
        }

        for dep in downstream:
            depth = dep['depth']
            impact['affected_by_depth'][depth] = impact['affected_by_depth'].get(depth, 0) + 1

        return impact

    def validate_lineage(self) -> List[str]:
        """Validate lineage for completeness and consistency."""
        issues = []

        # Check for orphan entities (no source or transformation)
        for eid, entity in self.entities.items():
            has_lineage = any(r.entity_id == eid for r in self.lineage_records)
            if not has_lineage and entity.entity_type != 'source':
                issues.append(f"Entity '{entity.name}' has no lineage record")

        # Check for broken references
        all_entity_ids = set(self.entities.keys())
        for record in self.lineage_records:
            for upstream_id in record.upstream_entities:
                if upstream_id not in all_entity_ids:
                    issues.append(f"Lineage references unknown entity: {upstream_id}")

        # Check for circular dependencies
        for eid in self.entities:
            upstream = set()
            to_check = [eid]
            while to_check:
                current = to_check.pop()
                if current in upstream:
                    issues.append(f"Circular dependency detected involving entity: {self.entities[eid].name}")
                    break
                upstream.add(current)
                for record in self.lineage_records:
                    if record.entity_id == current:
                        to_check.extend(record.upstream_entities)

        return issues

    def generate_lineage_graph(self, entity_id: str) -> str:
        """Generate Mermaid diagram of lineage."""
        lines = ["```mermaid", "graph LR"]

        upstream = self.trace_upstream(entity_id, depth=5)
        downstream = self.trace_downstream(entity_id, depth=5)

        # Add nodes
        added_nodes = set()
        for item in upstream + downstream:
            node_id = item['entity_id'].replace('-', '_')
            if node_id not in added_nodes:
                entity = self.entities.get(item['entity_id'])
                name = entity.name if entity else item['entity_id']
                lines.append(f"    {node_id}[{name}]")
                added_nodes.add(node_id)

        # Add target node
        target_node = entity_id.replace('-', '_')
        if target_node not in added_nodes:
            entity = self.entities.get(entity_id)
            name = entity.name if entity else entity_id
            lines.append(f"    {target_node}[{name}]:::target")

        # Add edges
        for item in upstream:
            for upstream_id in item.get('upstream', []):
                from_node = upstream_id.replace('-', '_')
                to_node = item['entity_id'].replace('-', '_')
                lines.append(f"    {from_node} --> {to_node}")

        for item in downstream:
            from_node = entity_id.replace('-', '_')
            to_node = item['entity_id'].replace('-', '_')
            if to_node != from_node:
                lines.append(f"    {from_node} --> {to_node}")

        lines.append("    classDef target fill:#f96")
        lines.append("```")

        return "\n".join(lines)

    def export_lineage(self) -> Dict:
        """Export complete lineage data."""
        return {
            'project_id': self.project_id,
            'exported_at': datetime.now().isoformat(),
            'sources': {k: {
                'id': v.id,
                'name': v.name,
                'system': v.system,
                'location': v.location,
                'owner': v.owner
            } for k, v in self.sources.items()},
            'entities': {k: {
                'id': v.id,
                'name': v.name,
                'source_id': v.source_id,
                'entity_type': v.entity_type,
                'parent_entities': v.parent_entities
            } for k, v in self.entities.items()},
            'transformations': {k: {
                'id': v.id,
                'type': v.transformation_type.value,
                'description': v.description,
                'input_entities': v.input_entities,
                'output_entities': v.output_entities,
                'performed_by': v.performed_by,
                'performed_at': v.performed_at.isoformat()
            } for k, v in self.transformations.items()},
            'lineage_records': [{
                'id': r.id,
                'entity_id': r.entity_id,
                'transformation_id': r.transformation_id,
                'upstream_entities': r.upstream_entities
            } for r in self.lineage_records]
        }

    def generate_report(self) -> str:
        """Generate lineage report."""
        lines = [f"# Data Lineage Report: {self.project_id}", ""]
        lines.append(f"**Generated:** {datetime.now().strftime('%Y-%m-%d %H:%M')}")
        lines.append(f"**Sources:** {len(self.sources)}")
        lines.append(f"**Entities:** {len(self.entities)}")
        lines.append(f"**Transformations:** {len(self.transformations)}")
        lines.append("")

        # Sources
        lines.append("## Data Sources")
        for source in self.sources.values():
            lines.append(f"- **{source.name}** ({source.system})")
            lines.append(f"  - Location: {source.location}")
            lines.append(f"  - Owner: {source.owner}")
        lines.append("")

        # Validation
        issues = self.validate_lineage()
        if issues:
            lines.append("## Lineage Issues")
            for issue in issues:
                lines.append(f"- ⚠️ {issue}")
            lines.append("")

        # Transformation summary
        lines.append("## Transformation Summary")
        type_counts = {}
        for t in self.transformations.values():
            type_counts[t.transformation_type.value] = type_counts.get(t.transformation_type.value, 0) + 1
        for t_type, count in sorted(type_counts.items()):
            lines.append(f"- {t_type}: {count}")

        return "\n".join(lines)

Quick Start

# Initialize tracker
tracker = ConstructionDataLineageTracker("PROJECT-001")

# Register sources
procore = tracker.register_source("Procore", "SaaS", "cloud", "PM Team")
sage = tracker.register_source("Sage 300", "Database", "on-prem", "Finance")

# Register entities
budget = tracker.register_entity("Project Budget", procore.id, "table")
costs = tracker.register_entity("Job Costs", sage.id, "table")
report = tracker.register_entity("Cost Variance Report", procore.id, "file")

# Record transformation
tracker.record_transformation(
    transformation_type=TransformationType.JOIN,
    description="Join budget and actual costs for variance calculation",
    input_entities=[budget.id, costs.id],
    output_entities=[report.id],
    logic="SELECT b.*, c.actual, (b.budget - c.actual) as variance FROM budget b JOIN costs c ON b.cost_code = c.cost_code",
    performed_by="ETL Pipeline"
)

# Trace lineage
upstream = tracker.trace_upstream(report.id)
print("Upstream lineage:", upstream)

# Generate graph
print(tracker.generate_lineage_graph(report.id))

# Export for audit
lineage_data = tracker.export_lineage()

Resources

  • Data Governance: DAMA DMBOK lineage guidelines
  • Audit Requirements: SOX, ISO compliance

平台分布

Codex

33.7%
按下载量换算39

Claude

29.49%
按下载量换算34

Cursor

19.2%
按下载量换算22

Gemini CLI

9.52%
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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