bim-to-schedule-4d

bim-to-schedule-4d is a skill for Claude Code, Codex from datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction. It costs 28 tokens per session (1,612 once invoked), scanned A, original, MIT.

A construction planning tool connects BIM building elements with schedule activities. BIM, or Building Information Modeling, is a digital model of a building and its components.

In plain words
What is it for?
Use it to link model elements to dated activities and visualize the construction sequence over time in a 4D simulation.
Why use it?
It makes it easier to see which parts of a building are built, removed, or temporarily installed at each stage of the schedule.

Skill for Claude CodeCodex

Which agent this was written for is unclear — built for openclaw. Also seen: built for openclaw.

Good fit Use it to link model elements to dated activities and visualize the construction sequence over time in a 4D simulation.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/datadrivenconstruction/ddc_skills_for_ai_agents_in_construction/bim-to-schedule-4d
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction --skill bim-to-schedule-4d
Clone the repo
git clone --depth 1 https://github.com/datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for bim-to-schedule-4d

README.md
[![agentmods](https://agentmods.dev/badge/skills/datadrivenconstruction/ddc_skills_for_ai_agents_in_construction/bim-to-schedule-4d/github.svg)](https://agentmods.dev/skills/datadrivenconstruction/ddc_skills_for_ai_agents_in_construction/bim-to-schedule-4d)
Your own site
<a href="https://agentmods.dev/skills/datadrivenconstruction/ddc_skills_for_ai_agents_in_construction/bim-to-schedule-4d"><img src="https://agentmods.dev/badge/skills/datadrivenconstruction/ddc_skills_for_ai_agents_in_construction/bim-to-schedule-4d/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for bim-to-schedule-4d

Your own site · 80×15
<a href="https://agentmods.dev/skills/datadrivenconstruction/ddc_skills_for_ai_agents_in_construction/bim-to-schedule-4d"><img src="https://agentmods.dev/badge/skills/datadrivenconstruction/ddc_skills_for_ai_agents_in_construction/bim-to-schedule-4d.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 28 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,612 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00028 $0.01612
Opus 5 $0.00014 $0.00806
Sonnet 5 $0.00006 $0.00322
Haiku 4.5 $0.00003 $0.00161

Measured 9d ago against content hash 1b8d2362619c, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

bim-to-schedule-4d scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

1_DDC_Toolkit/Schedule-Integration/bim-to-schedule-4d/SKILL.md · 202 lines

How it starts

The opening of the file, as written. The whole thing — 202 lines — stays where its author put it; the contents beside it link to each section on GitHub.

BIM to Schedule 4D Integration

Technical Implementation

import pandas as pd
from datetime import date, timedelta
from typing import Dict, Any, List, Optional
from dataclasses import dataclass, field
from enum import Enum


class LinkStatus(Enum):
    LINKED = "linked"
    UNLINKED = "unlinked"
    PARTIAL = "partial"


@dataclass
class ScheduleActivity:
    activity_id: str
    activity_name: str
    start_date: date
    end_date: date
    duration_days: int
    wbs_code: str
    predecessors: List[str] = field(default_factory=list)


@dataclass
class BIMElement:
    element_id: str
    element_name: str
    category: str
    level: str
    zone: str
    volume: float = 0
    area: float = 0


@dataclass
class BIMScheduleLink:
    link_id: str
    activity_id: str
    element_ids: List[str]
    link_type: str  # install, remove, temporary
    status: LinkStatus


class BIMSchedule4D:
    def __init__(self, project_name: str):
        self.project_name = project_name
        self.activities: Dict[str, ScheduleActivity] = {}
        self.elements: Dict[str, BIMElement] = {}
        self.links: Dict[str, BIMScheduleLink] = {}
        self._link_counter = 0

    def import_schedule(self, schedule_data: List[Dict[str, Any]]):
        for act in schedule_data:
            activity = ScheduleActivity(
                activity_id=act['id'],
                activity_name=act['name'],
                start_date=act['start'],
                end_date=act['end'],
                duration_days=(act['end'] - act['start']).days,
                wbs_code=act.get('wbs', ''),
                predecessors=act.get('predecessors', [])
            )
            self.activities[activity.activity_id] = activity

    def import_elements(self, element_data: List[Dict[str, Any]]):
        for elem in element_data:
            element = BIMElement(
                element_id=elem['id'],
                element_name=elem['name'],
                category=elem['category'],
                level=elem.get('level', ''),
                zone=elem.get('zone', ''),
                volume=elem.get('volume', 0),
                area=elem.get('area', 0)
            )
            self.elements[element.element_id] = element

    def create_link(self, activity_id: str, element_ids: List[str],
                   link_type: str = "install") -> BIMScheduleLink:
        if activity_id not in self.activities:
            return None

        self._link_counter += 1
        link_id = f"LNK-{self._link_counter:05d}"

        # Verify elements exist
        valid_elements = [eid for eid in element_ids if eid in self.elements]

        status = LinkStatus.LINKED if valid_elements else LinkStatus.UNLINKED
        if valid_elements and len(valid_elements) < len(element_ids):
            status = LinkStatus.PARTIAL

        link = BIMScheduleLink(
            link_id=link_id,
            activity_id=activity_id,
            element_ids=valid_elements,
            link_type=link_type,
            status=status
        )
        self.links[link_id] = link
        return link

    def auto_link_by_level(self, level: str, activity_id: str):
        """Auto-link all elements on a level to an activity."""
        level_elements = [e.element_id for e in self.elements.values()
                        if e.level == level]
        if level_elements:
            return self.create_link(activity_id, level_elements)
        return None

    def get_elements_for_date(self, target_date: date) -> List[BIMElement]:
        """Get elements that should be visible on a specific date."""
        visible_elements = []
        for link in self.links.values():
            activity = self.activities.get(link.activity_id)
            if activity and activity.start_date <= target_date <= activity.end_date:
                for elem_id in link.element_ids:
                    if elem_id in self.elements:
                        visible_elements.append(self.elements[elem_id])
        return visible_elements

    def get_unlinked_elements(self) -> List[BIMElement]:
        linked_ids = set()
        for link in self.links.values():
            linked_ids.update(link.element_ids)
        return [e for e in self.elements.values() if e.element_id not in linked_ids]

    def get_unlinked_activities(self) -> List[ScheduleActivity]:
        linked_activities = {link.activity_id for link in self.links.values()}
        return [a for a in self.activities.values() if a.activity_id not in linked_activities]

    def get_link_summary(self) -> Dict[str, Any]:
        total_elements = len(self.elements)
        linked_elements = len(set(
            eid for link in self.links.values() for eid in link.element_ids
        ))

        return {
            'total_activities': len(self.activities),
            'total_elements': total_elements,
            'linked_elements': linked_elements,
            'unlinked_elements': total_elements - linked_elements,
            'total_links': len(self.links),
            'link_coverage': round(linked_elements / total_elements * 100, 1) if total_elements > 0 else 0
        }

    def export_links(self, output_path: str):
        data = []
        for link in self.links.values():
            activity = self.activities.get(link.activity_id)
            data.append({
                'Link ID': link.link_id,
                'Activity': activity.activity_name if activity else '',
                'Start': activity.start_date if activity else None,
                'End': activity.end_date if activity else None,
                'Elements': len(link.element_ids),
                'Type': link.link_type,
                'Status': link.status.value
            })
        pd.DataFrame(data).to_excel(output_path, index=False)

Read the full file on GitHub · 202 lines

Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 9d ago First seen · 202 lines · 28 tokens per session scan A 1b8d2362619c

Subscribe to this mod's changes

bim-to-schedule-4d is a skill published in the GitHub repository datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction (310 stars, last pushed 21d ago), licensed MIT. It adds 28 tokens to every session and 1,612 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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