{"slug":"datadrivenconstruction-project-kpi-dashboard","name":"project-kpi-dashboard","description":"Create interactive KPI dashboards for construction projects. Track schedule, cost, quality, and safety metrics in real-time.","long_description":"---\nname: \"project-kpi-dashboard\"\ndescription: \"Create interactive KPI dashboards for construction projects. Track schedule, cost, quality, and safety metrics in real-time.\"\nhomepage: \"https://datadrivenconstruction.io\"\nmetadata: {\"openclaw\": {\"emoji\": \"📊\", \"os\": [\"darwin\", \"linux\", \"win32\"], \"homepage\": \"https://datadrivenconstruction.io\", \"requires\": {\"bins\": [\"python3\"]}}}\n---\n# Project KPI Dashboard\n\n## Business Case\n\n### Problem Statement\nProject stakeholders struggle with:\n- Scattered data across multiple systems\n- Delayed reporting on project health\n- No real-time visibility into KPIs\n- Inconsistent metric definitions\n\n### Solution\nCentralized KPI dashboard that aggregates data from multiple sources and presents key metrics with drill-down capabilities.\n\n### Business Value\n- **Real-time visibility** - Live project health status\n- **Data-driven decisions** - Actionable insights\n- **Stakeholder alignment** - Single source of truth\n- **Early warning** - Proactive issue detection\n\n## Technical Implementation\n\n```python\nimport pandas as pd\nfrom datetime import datetime, date, timedelta\nfrom typing import Dict, Any, List, Optional\nfrom dataclasses import dataclass, field\nfrom enum import Enum\n\n\nclass KPIStatus(Enum):\n    \"\"\"KPI health status.\"\"\"\n    ON_TRACK = \"on_track\"\n    AT_RISK = \"at_risk\"\n    CRITICAL = \"critical\"\n    UNKNOWN = \"unknown\"\n\n\nclass KPICategory(Enum):\n    \"\"\"KPI categories.\"\"\"\n    SCHEDULE = \"schedule\"\n    COST = \"cost\"\n    QUALITY = \"quality\"\n    SAFETY = \"safety\"\n    PRODUCTIVITY = \"productivity\"\n    SUSTAINABILITY = \"sustainability\"\n\n\n@dataclass\nclass KPIMetric:\n    \"\"\"Single KPI metric.\"\"\"\n    name: str\n    category: KPICategory\n    current_value: float\n    target_value: float\n    unit: str\n    status: KPIStatus\n    trend: str  # up, down, stable\n    last_updated: datetime\n    description: str = \"\"\n\n    @property\n    def variance(self) -> float:\n        \"\"\"Calculate variance from target.\"\"\"\n        if self.target_value == 0:\n            return 0\n        return ((self.current_value - self.target_value) / self.target_value) * 100\n\n    @property\n    def achievement(self) -> float:\n        \"\"\"Calculate achievement percentage.\"\"\"\n        if self.target_value == 0:\n            return 0\n        return (self.current_value / self.target_value) * 100\n\n\n@dataclass\nclass DashboardConfig:\n    \"\"\"Dashboard configuration.\"\"\"\n    project_name: str\n    project_code: str\n    start_date: date\n    end_date: date\n    budget: float\n    currency: str = \"USD\"\n    refresh_interval_minutes: int = 15\n\n\nclass ProjectKPIDashboard:\n    \"\"\"Construction project KPI dashboard.\"\"\"\n\n    # Standard thresholds for RAG status\n    THRESHOLDS = {\n        'schedule': {'green': 0.95, 'amber': 0.85},\n        'cost': {'green': 1.05, 'amber': 1.15},\n        'quality': {'green': 0.98, 'amber': 0.95},\n        'safety': {'green': 0, 'amber': 1}  # incident count\n    }\n\n    def __init__(self, config: DashboardConfig):\n        self.config = config\n        self.metrics: Dict[str, KPIMetric] = {}\n        self.history: List[Dict[str, Any]] = []\n\n    def add_metric(self, metric: KPIMetric):\n        \"\"\"Add or update a KPI metric.\"\"\"\n        self.metrics[metric.name] = metric\n        self._record_history(metric)\n\n    def _record_history(self, metric: KPIMetric):\n        \"\"\"Record metric history for trending.\"\"\"\n        self.history.append({\n            'name': metric.name,\n            'value': metric.current_value,\n            'timestamp': metric.last_updated,\n            'status': metric.status.value\n        })\n\n    def calculate_schedule_kpis(self,\n                                 planned_activities: int,\n                                 completed_activities: int,\n                                 planned_duration_days: int,\n                                 actual_duration_days: int) -> List[KPIMetric]:\n        \"\"\"Calculate schedule-related KPIs.\"\"\"\n\n        # Schedule Performance Index (SPI)\n        spi = completed_activities / planned_activities if planned_activities > 0 else 0\n        spi_status = self._get_status(spi, 'schedule')\n\n        # Schedule Variance\n        sv = completed_activities - planned_activities\n\n        # Percent Complete\n        pct_complete = (completed_activities / planned_activities * 100) if planned_activities > 0 else 0\n\n        metrics = [\n            KPIMetric(\n                name=\"Schedule Performance Index\",\n                category=KPICategory.SCHEDULE,\n                current_value=round(spi, 2),\n                target_value=1.0,\n                unit=\"ratio\",\n                status=spi_status,\n                trend=self._calculate_trend(\"Schedule Performance Index\"),\n                last_updated=datetime.now(),\n                description=\"SPI = Earned Value / Planned Value\"\n            ),\n            KPIMetric(\n                name=\"Percent Complete\",\n                category=KPICategory.SCHEDULE,\n                current_value=round(pct_complete, 1),\n                target_value=100,\n                unit=\"%\",\n                status=spi_status,\n                trend=self._calculate_trend(\"Percent Complete\"),\n                last_updated=datetime.now()\n            ),\n            KPIMetric(\n                name=\"Schedule Variance\",\n                category=KPICategory.SCHEDULE,\n                current_value=sv,\n                target_value=0,\n                unit=\"activities\",\n                status=spi_status,\n                trend=self._calculate_trend(\"Schedule Variance\"),\n                last_updated=datetime.now()\n            )\n        ]\n\n        for m in metrics:\n            self.add_metric(m)\n\n        return metrics\n\n    def calculate_cost_kpis(self,\n                            budgeted_cost: float,\n                            actual_cost: float,\n                            earned_value: float) -> List[KPIMetric]:\n        \"\"\"Calculate cost-related KPIs.\"\"\"\n\n        # Cost Performance Index (CPI)\n        cpi = earned_value / actual_cost if actual_cost > 0 else 0\n        cpi_status = self._get_status(cpi, 'cost', inverse=True)\n\n        # Cost Variance\n        cv = earned_value - actual_cost\n\n        # Budget utilization\n        budget_used = (actual_cost / budgeted_cost * 100) if budgeted_cost > 0 else 0\n\n        metrics = [\n            KPIMetric(\n                name=\"Cost Performance Index\",\n                category=KPICategory.COST,\n                current_value=round(cpi, 2),\n                target_value=1.0,\n                unit=\"ratio\",\n                status=cpi_status,\n                trend=self._calculate_trend(\"Cost Performance Index\"),\n                last_updated=datetime.now(),\n                description=\"CPI = Earned Value / Actual Cost\"\n            ),\n            KPIMetric(\n                name=\"Cost Variance\",\n                category=KPICategory.COST,\n                current_value=round(cv, 2),\n                target_value=0,\n                unit=self.config.currency,\n                status=cpi_status,\n                trend=self._calculate_trend(\"Cost Variance\"),\n                last_updated=datetime.now()\n            ),\n            KPIMetric(\n                name=\"Budget Utilization\",\n                category=KPICategory.COST,\n                current_value=round(budget_used, 1),\n                target_value=100,\n                unit=\"%\",\n                status=cpi_status,\n                trend=self._calculate_trend(\"Budget Utilization\"),\n                last_updated=datetime.now()\n            )\n        ]\n\n        for m in metrics:\n            self.add_metric(m)\n\n        return metrics\n\n    def calculate_quality_kpis(self,\n                               total_inspections: int,\n                               passed_inspections: int,\n                               rework_items: int,\n                               total_items: int) -> List[KPIMetric]:\n        \"\"\"Calculate quality-related KPIs.\"\"\"\n\n        # First Pass Yield\n        fpy = passed_inspections / total_inspections if total_inspections > 0 else 0\n        fpy_status = self._get_status(fpy, 'quality')\n\n        # Rework Rate\n        rework_rate = rework_items / total_items * 100 if total_items > 0 else 0\n\n        metrics = [\n            KPIMetric(\n                name=\"First Pass Yield\",\n                category=KPICategory.QUALITY,\n                current_value=round(fpy * 100, 1),\n                target_value=98,\n                unit=\"%\",\n                status=fpy_status,\n                trend=self._calculate_trend(\"First Pass Yield\"),\n                last_updated=datetime.now()\n            ),\n            KPIMetric(\n                name=\"Rework Rate\",\n                category=KPICategory.QUALITY,\n                current_value=round(rework_rate, 1),\n                target_value=2,\n                unit=\"%\",\n                status=fpy_status,\n                trend=self._calculate_trend(\"Rework Rate\"),\n                last_updated=datetime.now()\n            )\n        ]\n\n        for m in metrics:\n            self.add_metric(m)\n\n        return metrics\n\n    def calculate_safety_kpis(self,\n                              incidents: int,\n                              near_misses: int,\n                              worked_hours: float,\n                              safety_observations: int) -> List[KPIMetric]:\n        \"\"\"Calculate safety-related KPIs.\"\"\"\n\n        # TRIR (Total Recordable Incident Rate)\n        trir = (incidents * 200000) / worked_hours if worked_hours > 0 else 0\n        trir_status = KPIStatus.ON_TRACK if incidents == 0 else (\n            KPIStatus.AT_RISK if incidents <= 2 else KPIStatus.CRITICAL\n        )\n\n        # LTIR (Lost Time Incident Rate)\n        ltir = (incidents * 1000000) / worked_hours if worked_hours > 0 else 0\n\n        metrics = [\n            KPIMetric(\n                name=\"TRIR\",\n                category=KPICategory.SAFETY,\n                current_value=round(trir, 2),\n                target_value=0,\n                unit=\"per 200k hrs\",\n                status=trir_status,\n                trend=self._calculate_trend(\"TRIR\"),\n                last_updated=datetime.now(),\n                description=\"Total Recordable Incident Rate\"\n            ),\n            KPIMetric(\n                name=\"Safety Observations\",\n                category=KPICategory.SAFETY,\n                current_value=safety_observations,\n                target_value=50,\n                unit=\"count\",\n                status=KPIStatus.ON_TRACK if safety_observations >= 50 else KPIStatus.AT_RISK,\n                trend=self._calculate_trend(\"Safety Observations\"),\n                last_updated=datetime.now()\n            ),\n            KPIMetric(\n                name=\"Near Miss Reports\",\n                category=KPICategory.SAFETY,\n                current_value=near_misses,\n                target_value=10,\n                unit=\"count\",\n                status=KPIStatus.ON_TRACK,\n                trend=self._calculate_trend(\"Near Miss Reports\"),\n                last_updated=datetime.now()\n            )\n        ]\n\n        for m in metrics:\n            self.add_metric(m)\n\n        return metrics\n\n    def _get_status(self, value: float, category: str, inverse: bool = False) -> KPIStatus:\n        \"\"\"Determine RAG status based on thresholds.\"\"\"\n        thresholds = self.THRESHOLDS.get(category, {'green': 0.95, 'amber': 0.85})\n\n        if inverse:\n            if value >= thresholds['green']:\n                return KPIStatus.ON_TRACK\n            elif value >= thresholds['amber']:\n                return KPIStatus.AT_RISK\n            else:\n                return KPIStatus.CRITICAL\n        else:\n            if value >= thresholds['green']:\n                return KPIStatus.ON_TRACK\n            elif value >= thresholds['amber']:\n                return KPIStatus.AT_RISK\n            else:\n                return KPIStatus.CRITICAL\n\n    def _calculate_trend(self, metric_name: str) -> str:\n        \"\"\"Calculate trend based on historical data.\"\"\"\n        history = [h for h in self.history if h['name'] == metric_name]\n        if ","tagline":"Create interactive KPI dashboards for construction projects. Track schedule, cost, quality, and safety metrics in real-time.","category":"data-analysis","tags":["agent-skill"],"author":"datadrivenconstruction","verified":false,"attribution":{"status":"registry_indexed","statusLabel":"Registry indexed","shortLabel":"REGISTRY INDEXED","sourceLabel":"recursive skill source sync","sourceDetail":"datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction","creatorName":"datadrivenconstruction","creatorUrl":"https://github.com/datadrivenconstruction","sourceUrl":"https://github.com/datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction/tree/main/1_DDC_Toolkit/Analytics/project-kpi-dashboard","indexedBy":"OpenAgentSkill community index","claimUrl":"https://www.openagentskill.com/skills/datadrivenconstruction-project-kpi-dashboard#claim-this-skill","claimCta":"Claim this skill","trustNote":"This listing was indexed from public sources and is not marked official until a maintainer claim is approved.","publicNote":"Attribution links to the public repository or creator profile. Creators can claim the listing to update ownership signals."},"stats":{"stars":282,"forks":74,"verified_installs":0,"successful_runs":0,"total_outcomes":0,"rating":0,"review_count":0,"quality_score":40.41},"quality":{"score":71,"tier":"strong","label":"Strong","summary":"Solid option that is likely worth shortlisting for production workflows.","signals":[{"label":"GitHub stars","value":"282","tone":"neutral"},{"label":"Freshness","value":"Today","tone":"positive"},{"label":"Install ready","value":"Yes","tone":"positive"},{"label":"License","value":"MIT","tone":"neutral"}],"warnings":["SKILL.md excerpt is incomplete; full documentation may lack explicit setup and dependency installation steps."]},"trust":{"version":"trust-score-v5","score":66,"base_score":74,"outcome_confidence":0,"tier":"review","label":"Sandbox only","summary":"Useful candidate with missing or mixed trust signals. 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issue activity unavailable in current metadata"},{"id":"maintenance","label":"Recent maintenance","score":100,"weight":0.14,"status":"pass","detail":"Pushed today"},{"id":"license","label":"License clarity","score":86,"weight":0.09,"status":"pass","detail":"MIT"},{"id":"documentation","label":"README/SKILL.md completeness","score":76,"weight":0.14,"status":"info","detail":"Public metadata needs stronger README/SKILL.md context"},{"id":"dependency_risk","label":"Dependency/runtime risk","score":90,"weight":0.12,"status":"pass","detail":"no major dependency risk hints in public metadata"},{"id":"installability","label":"Install availability","score":92,"weight":0.1,"status":"pass","detail":"npx skills add datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction --skill project-kpi-dashboard"},{"id":"install_safety","label":"Install command safety","score":92,"weight":0.1,"status":"pass","detail":"standard package or runtime install path"},{"id":"permission_surface","label":"Permission surface","score":100,"weight":0.07,"status":"pass","detail":"no high-risk permission surface in public metadata"},{"id":"repository","label":"Repository evidence","score":86,"weight":0.04,"status":"pass","detail":"https://github.com/datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction/tree/main/1_DDC_Toolkit/Analytics/project-kpi-dashboard"},{"id":"review_status","label":"Review status","score":66,"weight":0.05,"status":"info","detail":"AI review data available"},{"id":"agent_outcomes","label":"Agent Proven outcomes","score":54,"weight":0.13,"status":"info","detail":"No agent outcome data yet"}],"checks":[{"status":"info","label":"GitHub adoption","detail":"282 GitHub stars"},{"status":"info","label":"Stars/forks activity","detail":"282 stars, 74 forks; 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full documentation may lack explicit setup and dependency installation steps."]},{"id":"agent_safety_gate","label":"Agent safety gate","status":"warn","score":68,"required_for_auto_install":true,"detail":"Usable candidate, but the agent should surface permission and audit notes before installation.","evidence":["Require human approval before installing into a real workspace.","SKILL.md excerpt is incomplete; full documentation may lack explicit setup and dependency installation steps."]},{"id":"readme_skillmd_completeness","label":"README/SKILL.md completeness","status":"warn","score":76,"required_for_auto_install":false,"detail":"Public metadata needs stronger README/SKILL.md context","evidence":["Usable metadata, review docs"]},{"id":"license_clarity","label":"License clarity","status":"pass","score":86,"required_for_auto_install":true,"detail":"MIT","evidence":["MIT"]},{"id":"recent_maintenance","label":"Recent maintenance","status":"pass","score":100,"required_for_auto_install":false,"detail":"Pushed today","evidence":["Pushed today"]},{"id":"permission_surface","label":"Permission surface","status":"pass","score":100,"required_for_auto_install":true,"detail":"no high-risk permission surface in public metadata","evidence":["Network access: medium"]},{"id":"alternatives","label":"Alternatives available","status":"info","score":55,"required_for_auto_install":false,"detail":"No close alternatives were found in the current shortlist.","evidence":[]}],"endpoints":{"web":"https://www.openagentskill.com/skills/datadrivenconstruction-project-kpi-dashboard/evals","api":"/api/agent/evals?slug=datadrivenconstruction-project-kpi-dashboard","text":"/api/agent/evals?slug=datadrivenconstruction-project-kpi-dashboard&format=text"}},"agent_readable_metadata":{"version":"openagentskill-agent-metadata-v2","skill":{"slug":"datadrivenconstruction-project-kpi-dashboard","name":"project-kpi-dashboard","description":"Create interactive KPI dashboards for construction projects. Track schedule, cost, quality, and safety metrics in real-time.","category":"data-analysis","url":"https://www.openagentskill.com/skills/datadrivenconstruction-project-kpi-dashboard","repository":"https://github.com/datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction/tree/main/1_DDC_Toolkit/Analytics/project-kpi-dashboard","github_repo":"datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction"},"suited_tasks":["Research agents workflows","Claude Code teams","builders willing to evaluate younger projects","Search sources","Extract claims","Synthesize findings","Navigate pages","Click and type safely"],"suited_agents":["Codex","Claude Code","Cursor","OpenAgentSkill CLI","CLI"],"install":{"command":"npx skills add datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction --skill project-kpi-dashboard","ready":true,"targets":[{"id":"openagentskill-cli","label":"CLI","kind":"command","value":"npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.2.1/openagentskill-0.2.1.tgz install datadrivenconstruction-project-kpi-dashboard"},{"id":"codex","label":"Codex","kind":"agent-prompt","value":"Install the \"project-kpi-dashboard\" agent skill from https://github.com/datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction/tree/main/1_DDC_Toolkit/Analytics/project-kpi-dashboard. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: Create interactive KPI dashboards for construction projects. Track schedule, cost, quality, and safety metrics in real-time. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"datadrivenconstruction-project-kpi-dashboard\",\"task\":\"Install project-kpi-dashboard\",\"agent\":\"codex\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes."},{"id":"claude-code","label":"Claude Code","kind":"agent-prompt","value":"Add \"project-kpi-dashboard\" as a Claude Code skill from https://github.com/datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction/tree/main/1_DDC_Toolkit/Analytics/project-kpi-dashboard. Inspect the skill instructions, place the reusable skill files in the appropriate local skills location for this project, and report the activation steps. Skill purpose: Create interactive KPI dashboards for construction projects. Track schedule, cost, quality, and safety metrics in real-time. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"datadrivenconstruction-project-kpi-dashboard\",\"task\":\"Install project-kpi-dashboard\",\"agent\":\"claude-code\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes."},{"id":"cursor","label":"Cursor","kind":"agent-prompt","value":"Turn \"project-kpi-dashboard\" from https://github.com/datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction/tree/main/1_DDC_Toolkit/Analytics/project-kpi-dashboard into a reusable Cursor project rule or agent instruction. Preserve the core workflow, adapt paths to this repo, and keep the rule scoped to tasks where it is relevant. Skill purpose: Create interactive KPI dashboards for construction projects. Track schedule, cost, quality, and safety metrics in real-time. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"datadrivenconstruction-project-kpi-dashboard\",\"task\":\"Install project-kpi-dashboard\",\"agent\":\"cursor\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes."}],"handoff_url":"https://www.openagentskill.com/api/skills/datadrivenconstruction-project-kpi-dashboard/install","manifest_url":"https://www.openagentskill.com/api/registry/manifest/datadrivenconstruction-project-kpi-dashboard"},"trust":{"score":74,"label":"Strong shortlist","version":"trust-score-v4","install_policy":"human_review_before_install","evidence":{"stars":"282 GitHub stars","repoActivity":"282 stars, 74 forks","lastPushed":"Pushed today","license":"MIT","repository":"https://github.com/datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction/tree/main/1_DDC_Toolkit/Analytics/project-kpi-dashboard","install":"npx skills add datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction --skill project-kpi-dashboard","installSafety":"standard package or runtime install path","permissionSurface":"no high-risk permission surface in public metadata","documentation":"Usable metadata, review docs","agentOutcomes":"No agent outcome data yet"},"outcome_evidence":{"total":0,"successes":0,"failures":0,"not_relevant":0,"success_rate":null,"recent_success_rate":null,"recent_failure_rate":null,"install_attempts":0,"install_success_rate":null,"risk_blocked":0,"setup_required":0,"avg_output_quality":null,"production_outcomes":0,"last_outcome_at":null,"label":"No agent outcome data yet"},"auto_install":{"allowed":false,"sandbox_required":true,"reason":"Human review or sandbox validation is required before automatic installation."},"best_for":["data-analysis","agent-skill"],"known_risks":["SKILL.md excerpt is incomplete; full documentation may lack explicit setup and dependency installation steps.","Quality score needs review"]},"agent_proven":{"version":"agent-proven-v1","score":0,"tier":"unproven","label":"Needs first agent run","summary":"No agent outcome reports yet. Use Resolve, run one narrow sandbox task, then report the result.","metrics":{"totalOutcomes":0,"successfulOutcomes":0,"failedOutcomes":0,"installAttempts":0,"installSuccessRate":null,"successRate":null,"recentSuccessRate":null,"recentFailureRate":null,"riskBlocked":0,"setupRequired":0,"notRelevant":0,"avgOutputQuality":null,"avgTimeToUsefulMs":null,"productionOutcomes":0,"humanReviewRequired":0,"uniqueAgents":0,"lastOutcomeAt":null},"signals":[],"penalties":["No real agent outcome evidence yet"]},"audit":{"score":80,"risk_level":"needs_review","risk_label":"Needs review","warnings":["SKILL.md excerpt is incomplete; full documentation may lack explicit setup and dependency installation steps.","The skill uses pandas and may require additional Python packages beyond python3; dependency management is not specified.","Quality score needs review"]},"safety_gate":{"tier":"reviewed","label":"Reviewed with permission notes","auto_install_policy":"review","auto_install_allowed":false,"human_review_required":true,"blocked":false,"recommended_action":"Require human approval before installing into a real workspace."},"quality":{"score":71,"label":"Strong"},"supply":{"track":"Data, BI, and analytics","scenario":"Data analysis","maintenance":"Pushed today","risk":"Needs review"},"alternative_skills":[],"do_not_use_when":["teams that need a vendor-supported SLA","production agents without a repository review","SKILL.md excerpt is incomplete; full documentation may lack explicit setup and dependency installation steps.","No OpenAgentSkill engagement data yet","The skill uses pandas and may require additional Python packages beyond python3; dependency management is not specified.","Quality score needs review","Production credentials, payments, or irreversible account changes without explicit human review","Sensitive private data before reviewing repository code, license, and permission surface"],"agent_contract":{"task_input":"Use project-kpi-dashboard in an agent workflow","recommended_action":"Require human approval before installing into a real workspace.","install_policy":"review","minimum_review_before_use":["Trust: 74/100 Strong shortlist","Audit: 80/100 Needs review","Safety: 68/100 Review before install","Review repository, license, install command, and permission surface before production use."],"expected_agent_output":{"selected_skill":"datadrivenconstruction-project-kpi-dashboard (project-kpi-dashboard)","install_command":"npx skills add datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction --skill project-kpi-dashboard","risk_summary":"Needs review; Reviewed with permission notes; Review before production","verification_result":"Report the smallest successful task, files touched, warnings, and any missing setup."}},"outcome_feedback":{"endpoint":"https://www.openagentskill.com/api/agent/outcome","method":"POST","requires_resolve_event_id":true,"event_id_source":"Use install_receipt.outcome_feedback.event_id or feedback.event_id returned by /api/agent/resolve for the current task.","expected_outcomes":["success","failed","not_relevant","blocked_by_risk","setup_required"],"payload_template":{"event_id":"<install_receipt.outcome_feedback.event_id or feedback.event_id from /api/agent/resolve>","skill_slug":"datadrivenconstruction-project-kpi-dashboard","task":"Use project-kpi-dashboard in an agent workflow","agent":"codex","outcome":"success","install_used":true,"risk_blocked":false,"setup_required":false,"task_success":true,"output_quality":4,"error_type":null,"human_review_required":false,"workspace":"sandbox","time_to_useful_ms":120000,"notes":"Report the smallest successful task, setup friction, files touched, and risk notes."}},"endpoints":{"web":"https://www.openagentskill.com/skills/datadrivenconstruction-project-kpi-dashboard","api":"https://www.openagentskill.com/api/agent/skills/datadrivenconstruction-project-kpi-dashboard","audit":"https://www.openagentskill.com/skills/datadrivenconstruction-project-kpi-dashboard/audit","eval":"https://www.openagentskill.com/api/agent/evals?slug=datadrivenconstruction-project-kpi-dashboard&task=Use%20project-kpi-dashboard%20in%20an%20agent%20workflow&max_risk=medium","resolve":"https://www.openagentskill.com/api/agent/resolve?task=Use%20project-kpi-dashboard%20in%20an%20agent%20workflow&agent=codex&max_risk=medium","receipt":"https://www.openagentskill.com/api/agent/receipt?task=Use%20project-kpi-dashboard%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text","install":"https://www.openagentskill.com/api/skills/datadrivenconstruction-project-kpi-dashboard/install","manifest":"https://www.openagentskill.com/api/registry/manifest/datadrivenconstruction-project-kpi-dashboard"}},"machine_metadata":{"version":"openagentskill-agent-metadata-v2","skill":{"slug":"datadrivenconstruction-project-kpi-dashboard","name":"project-kpi-dashboard","description":"Create interactive KPI dashboards for construction projects. Track schedule, cost, quality, and safety metrics in real-time.","category":"data-analysis","url":"https://www.openagentskill.com/skills/datadrivenconstruction-project-kpi-dashboard","repository":"https://github.com/datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction/tree/main/1_DDC_Toolkit/Analytics/project-kpi-dashboard","github_repo":"datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction"},"suited_tasks":["Research agents workflows","Claude Code teams","builders willing to evaluate younger projects","Search sources","Extract claims","Synthesize findings","Navigate pages","Click and type safely"],"suited_agents":["Codex","Claude Code","Cursor","OpenAgentSkill CLI","CLI"],"install":{"command":"npx skills add datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction --skill project-kpi-dashboard","ready":true,"targets":[{"id":"openagentskill-cli","label":"CLI","kind":"command","value":"npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.2.1/openagentskill-0.2.1.tgz install datadrivenconstruction-project-kpi-dashboard"},{"id":"codex","label":"Codex","kind":"agent-prompt","value":"Install the \"project-kpi-dashboard\" agent skill from https://github.com/datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction/tree/main/1_DDC_Toolkit/Analytics/project-kpi-dashboard. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: Create interactive KPI dashboards for construction projects. Track schedule, cost, quality, and safety metrics in real-time. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"datadrivenconstruction-project-kpi-dashboard\",\"task\":\"Install project-kpi-dashboard\",\"agent\":\"codex\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes."},{"id":"claude-code","label":"Claude Code","kind":"agent-prompt","value":"Add \"project-kpi-dashboard\" as a Claude Code skill from https://github.com/datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction/tree/main/1_DDC_Toolkit/Analytics/project-kpi-dashboard. Inspect the skill instructions, place the reusable skill files in the appropriate local skills location for this project, and report the activation steps. Skill purpose: Create interactive KPI dashboards for construction projects. Track schedule, cost, quality, and safety metrics in real-time. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"datadrivenconstruction-project-kpi-dashboard\",\"task\":\"Install project-kpi-dashboard\",\"agent\":\"claude-code\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes."},{"id":"cursor","label":"Cursor","kind":"agent-prompt","value":"Turn \"project-kpi-dashboard\" from https://github.com/datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction/tree/main/1_DDC_Toolkit/Analytics/project-kpi-dashboard into a reusable Cursor project rule or agent instruction. Preserve the core workflow, adapt paths to this repo, and keep the rule scoped to tasks where it is relevant. Skill purpose: Create interactive KPI dashboards for construction projects. Track schedule, cost, quality, and safety metrics in real-time. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"datadrivenconstruction-project-kpi-dashboard\",\"task\":\"Install project-kpi-dashboard\",\"agent\":\"cursor\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes."}],"handoff_url":"https://www.openagentskill.com/api/skills/datadrivenconstruction-project-kpi-dashboard/install","manifest_url":"https://www.openagentskill.com/api/registry/manifest/datadrivenconstruction-project-kpi-dashboard"},"trust":{"score":74,"label":"Strong shortlist","version":"trust-score-v4","install_policy":"human_review_before_install","evidence":{"stars":"282 GitHub stars","repoActivity":"282 stars, 74 forks","lastPushed":"Pushed today","license":"MIT","repository":"https://github.com/datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction/tree/main/1_DDC_Toolkit/Analytics/project-kpi-dashboard","install":"npx skills add datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction --skill project-kpi-dashboard","installSafety":"standard package or runtime install path","permissionSurface":"no high-risk permission surface in public metadata","documentation":"Usable metadata, review docs","agentOutcomes":"No agent outcome data yet"},"outcome_evidence":{"total":0,"successes":0,"failures":0,"not_relevant":0,"success_rate":null,"recent_success_rate":null,"recent_failure_rate":null,"install_attempts":0,"install_success_rate":null,"risk_blocked":0,"setup_required":0,"avg_output_quality":null,"production_outcomes":0,"last_outcome_at":null,"label":"No agent outcome data yet"},"auto_install":{"allowed":false,"sandbox_required":true,"reason":"Human review or sandbox validation is required before automatic installation."},"best_for":["data-analysis","agent-skill"],"known_risks":["SKILL.md excerpt is incomplete; full documentation may lack explicit setup and dependency installation steps.","Quality score needs review"]},"agent_proven":{"version":"agent-proven-v1","score":0,"tier":"unproven","label":"Needs first agent run","summary":"No agent outcome reports yet. Use Resolve, run one narrow sandbox task, then report the result.","metrics":{"totalOutcomes":0,"successfulOutcomes":0,"failedOutcomes":0,"installAttempts":0,"installSuccessRate":null,"successRate":null,"recentSuccessRate":null,"recentFailureRate":null,"riskBlocked":0,"setupRequired":0,"notRelevant":0,"avgOutputQuality":null,"avgTimeToUsefulMs":null,"productionOutcomes":0,"humanReviewRequired":0,"uniqueAgents":0,"lastOutcomeAt":null},"signals":[],"penalties":["No real agent outcome evidence yet"]},"audit":{"score":80,"risk_level":"needs_review","risk_label":"Needs review","warnings":["SKILL.md excerpt is incomplete; full documentation may lack explicit setup and dependency installation steps.","The skill uses pandas and may require additional Python packages beyond python3; dependency management is not specified.","Quality score needs review"]},"safety_gate":{"tier":"reviewed","label":"Reviewed with permission notes","auto_install_policy":"review","auto_install_allowed":false,"human_review_required":true,"blocked":false,"recommended_action":"Require human approval before installing into a real workspace."},"quality":{"score":71,"label":"Strong"},"supply":{"track":"Data, BI, and analytics","scenario":"Data analysis","maintenance":"Pushed today","risk":"Needs review"},"alternative_skills":[],"do_not_use_when":["teams that need a vendor-supported SLA","production agents without a repository review","SKILL.md excerpt is incomplete; full documentation may lack explicit setup and dependency installation steps.","No OpenAgentSkill engagement data yet","The skill uses pandas and may require additional Python packages beyond python3; dependency management is not specified.","Quality score needs review","Production credentials, payments, or irreversible account changes without explicit human review","Sensitive private data before reviewing repository code, license, and permission surface"],"agent_contract":{"task_input":"Use project-kpi-dashboard in an agent workflow","recommended_action":"Require human approval before installing into a real workspace.","install_policy":"review","minimum_review_before_use":["Trust: 74/100 Strong shortlist","Audit: 80/100 Needs review","Safety: 68/100 Review before install","Review repository, license, install command, and permission surface before production use."],"expected_agent_output":{"selected_skill":"datadrivenconstruction-project-kpi-dashboard (project-kpi-dashboard)","install_command":"npx skills add datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction --skill project-kpi-dashboard","risk_summary":"Needs review; Reviewed with permission notes; Review before production","verification_result":"Report the smallest successful task, files touched, warnings, and any missing setup."}},"outcome_feedback":{"endpoint":"https://www.openagentskill.com/api/agent/outcome","method":"POST","requires_resolve_event_id":true,"event_id_source":"Use install_receipt.outcome_feedback.event_id or feedback.event_id returned by /api/agent/resolve for the current task.","expected_outcomes":["success","failed","not_relevant","blocked_by_risk","setup_required"],"payload_template":{"event_id":"<install_receipt.outcome_feedback.event_id or feedback.event_id from /api/agent/resolve>","skill_slug":"datadrivenconstruction-project-kpi-dashboard","task":"Use project-kpi-dashboard in an agent workflow","agent":"codex","outcome":"success","install_used":true,"risk_blocked":false,"setup_required":false,"task_success":true,"output_quality":4,"error_type":null,"human_review_required":false,"workspace":"sandbox","time_to_useful_ms":120000,"notes":"Report the smallest successful task, setup friction, files touched, and risk notes."}},"endpoints":{"web":"https://www.openagentskill.com/skills/datadrivenconstruction-project-kpi-dashboard","api":"https://www.openagentskill.com/api/agent/skills/datadrivenconstruction-project-kpi-dashboard","audit":"https://www.openagentskill.com/skills/datadrivenconstruction-project-kpi-dashboard/audit","eval":"https://www.openagentskill.com/api/agent/evals?slug=datadrivenconstruction-project-kpi-dashboard&task=Use%20project-kpi-dashboard%20in%20an%20agent%20workflow&max_risk=medium","resolve":"https://www.openagentskill.com/api/agent/resolve?task=Use%20project-kpi-dashboard%20in%20an%20agent%20workflow&agent=codex&max_risk=medium","receipt":"https://www.openagentskill.com/api/agent/receipt?task=Use%20project-kpi-dashboard%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text","install":"https://www.openagentskill.com/api/skills/datadrivenconstruction-project-kpi-dashboard/install","manifest":"https://www.openagentskill.com/api/registry/manifest/datadrivenconstruction-project-kpi-dashboard"}},"supply_profile":{"track":{"slug":"data","label":"Data, BI, and analytics","shortLabel":"Data","description":"CSV, SQL, notebooks, dashboards, data pipelines, BI, ETL, and spreadsheet analysis."},"scenario":{"label":"Data analysis","description":"I need my agent to analyze CSV data, produce insights, and explain trends.","useCases":[{"slug":"research-agents","title":"Research agents"},{"slug":"browser-automation","title":"Browser automation"},{"slug":"workflow-automation","title":"Workflow automation"}]},"applicableAgents":["Claude Code","CLI","Codex","Cursor"],"install":{"ready":true,"command":"npx skills add datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction --skill project-kpi-dashboard","primaryTarget":"CLI","targetCount":4},"githubQuality":{"stars":282,"starsLabel":"282","forks":74,"license":"MIT","qualityScore":71,"trustScore":74,"auditScore":80},"maintenance":{"status":"fresh","label":"Pushed today","daysSincePush":0,"lastPushedAt":"2026-08-22T07:59:22+00:00"},"risk":{"level":"needs_review","label":"Needs review","requiresReview":true,"notes":["SKILL.md excerpt is incomplete; full documentation may lack explicit setup and dependency installation steps.","The skill uses pandas and may require additional Python packages beyond python3; dependency management is not specified.","Quality score needs review","Needs review"]},"coverageTags":["Data","Data analysis","data-analysis","agent-skill"]},"audit":{"audit_score":80,"risk_level":"needs_review","risk_label":"Needs review","quality_score":71,"trust_score":74,"maintenance_score":100,"security_score":83,"install_score":92,"warnings":["SKILL.md excerpt is incomplete; full documentation may lack explicit setup and dependency installation steps.","The skill uses pandas and may require additional Python packages beyond python3; dependency management is not specified.","Quality score needs review"]},"quality_signals":{"model":"v2","star_score":17.16,"usage_score":0,"review_score":5.25,"metadata_score":3,"freshness_score":15},"platforms":["Claude Code"],"use_cases":[{"slug":"research-agents","title":"Research agents","url":"https://www.openagentskill.com/use-cases/research-agents"},{"slug":"browser-automation","title":"Browser automation","url":"https://www.openagentskill.com/use-cases/browser-automation"},{"slug":"workflow-automation","title":"Workflow automation","url":"https://www.openagentskill.com/use-cases/workflow-automation"},{"slug":"data-analysis","title":"Data analysis","url":"https://www.openagentskill.com/use-cases/data-analysis"}],"stacks":[{"slug":"research-report-agent","title":"Research report agent","url":"https://www.openagentskill.com/collections/research-report-agent"},{"slug":"browser-qa-agent","title":"Browser QA agent","url":"https://www.openagentskill.com/collections/browser-qa-agent"},{"slug":"frontend-product-ui","title":"Frontend and UI","url":"https://www.openagentskill.com/collections/frontend-product-ui"}],"install":"npx skills add datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction --skill project-kpi-dashboard","install_targets":[{"id":"openagentskill-cli","label":"CLI","title":"OpenAgentSkill CLI","kind":"command","value":"npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.2.1/openagentskill-0.2.1.tgz install datadrivenconstruction-project-kpi-dashboard","description":"Resolve policy, run the source installer safely, and report a verified install receipt.","copyLabel":"Copy command"},{"id":"codex","label":"Codex","title":"Codex install prompt","kind":"agent-prompt","value":"Install the \"project-kpi-dashboard\" agent skill from https://github.com/datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction/tree/main/1_DDC_Toolkit/Analytics/project-kpi-dashboard. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: Create interactive KPI dashboards for construction projects. Track schedule, cost, quality, and safety metrics in real-time. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"datadrivenconstruction-project-kpi-dashboard\",\"task\":\"Install project-kpi-dashboard\",\"agent\":\"codex\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.","description":"Give Codex a repo-aware install prompt when the skill is not available through a local CLI.","copyLabel":"Copy prompt"},{"id":"claude-code","label":"Claude Code","title":"Claude Code skill prompt","kind":"agent-prompt","value":"Add \"project-kpi-dashboard\" as a Claude Code skill from https://github.com/datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction/tree/main/1_DDC_Toolkit/Analytics/project-kpi-dashboard. Inspect the skill instructions, place the reusable skill files in the appropriate local skills location for this project, and report the activation steps. Skill purpose: Create interactive KPI dashboards for construction projects. Track schedule, cost, quality, and safety metrics in real-time. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"datadrivenconstruction-project-kpi-dashboard\",\"task\":\"Install project-kpi-dashboard\",\"agent\":\"claude-code\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.","description":"Use this prompt to ask Claude Code to add the skill and explain the local activation steps.","copyLabel":"Copy prompt"},{"id":"cursor","label":"Cursor","title":"Cursor rule prompt","kind":"agent-prompt","value":"Turn \"project-kpi-dashboard\" from https://github.com/datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction/tree/main/1_DDC_Toolkit/Analytics/project-kpi-dashboard into a reusable Cursor project rule or agent instruction. Preserve the core workflow, adapt paths to this repo, and keep the rule scoped to tasks where it is relevant. Skill purpose: Create interactive KPI dashboards for construction projects. Track schedule, cost, quality, and safety metrics in real-time. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"datadrivenconstruction-project-kpi-dashboard\",\"task\":\"Install project-kpi-dashboard\",\"agent\":\"cursor\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.","description":"Use this when installing as Cursor project rules or reusable agent instructions.","copyLabel":"Copy prompt"}],"repository":"https://github.com/datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction/tree/main/1_DDC_Toolkit/Analytics/project-kpi-dashboard","github_repo":"datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction","version":"1.0.0","license":"MIT","urls":{"web":"https://www.openagentskill.com/skills/datadrivenconstruction-project-kpi-dashboard","repository":"https://github.com/datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction/tree/main/1_DDC_Toolkit/Analytics/project-kpi-dashboard","api":"/api/agent/skills/datadrivenconstruction-project-kpi-dashboard","install_api":"/api/skills/datadrivenconstruction-project-kpi-dashboard/install"},"meta":{"created_at":"2026-08-22T10:35:46.88082+00:00","updated_at":"2026-08-22T10:35:46.88082+00:00","agent_friendly":true}}