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Get Started Free →datadrivenconstruction/critical-path-analyzer
Analyze project critical path from schedule data. Identify critical activities, calculate float, and assess schedule risk.
Passed 21 of 22 test cases with the skill, and 20 of 22 without it.
1 fixed20 passed either way1 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
A test case the skill fixed. Same model, same prompt, with and without the skill.
Our current construction project consists of Task A (5d, cost $10k), Task B (8d, pred: A, cost $20k), Task C (4d, pred: B, cost $15k), Task D (2d, pred: C, cost $8k), Task E (7d, pred: D, cost $30k), Task F (15d, pred: E, cost $50k), and Task G (20d, pred: F, cost $40k). We need to compress the schedule. Perform an analysis to identify compression opportunities on the critical path, listing candidate tasks, available crash days, and estimated cost per day saved so we can decide how to accelerate completion.
| Checked | Without skill | With skill |
|---|---|---|
| Identifies Task F maximum crash days as 3 | Missed | Passed |
| Calculates Task F crash cost per day as 8333.33 | Missed | Passed |
The instructions your model reads when the skill loads.
Analyze construction schedules using Critical Path Method (CPM). Identify critical activities, calculate total and free float, simulate what-if scenarios, and find opportunities to compress schedule.
"Understanding the critical path is essential for effective schedule management" — DDC Community
┌─────────────────────────────────────────────────────────────────┐
│ CRITICAL PATH METHOD │
├─────────────────────────────────────────────────────────────────┤
│ │
│ Activity A (5d) ──→ Activity C (10d) ──→ Activity E (3d) │
│ ↓ ↑ │
│ Activity B (8d) ──────────→ Activity D (6d) ───┘ │
│ │
│ Critical Path: A → C → E (18 days) │
│ Float on B→D: 4 days │
│ │
└─────────────────────────────────────────────────────────────────┘
from dataclasses import dataclass, field
from typing import List, Dict, Optional, Set, Tuple
from datetime import datetime, timedelta
from collections import defaultdict
import heapq
@dataclass
class Activity:
id: str
name: str
duration: int # days
predecessors: List[str] = field(default_factory=list)
test cases passed, vs 20 / 22 without
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