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.
npx skills add xuansenpa1/skillrevise --skill power-flow-datagit clone --depth 1 https://github.com/xuansenpa1/skillreviseWrote 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.
[](https://agentmods.dev/skills/xuansenpa1/skillrevise/power-flow-data)<a href="https://agentmods.dev/skills/xuansenpa1/skillrevise/power-flow-data"><img src="https://agentmods.dev/badge/skills/xuansenpa1/skillrevise/power-flow-data/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.
<a href="https://agentmods.dev/skills/xuansenpa1/skillrevise/power-flow-data"><img src="https://agentmods.dev/badge/skills/xuansenpa1/skillrevise/power-flow-data.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00027 | $0.01134 |
| Opus 5 | $0.00014 | $0.00567 |
| Sonnet 5 | $0.00005 | $0.00227 |
| Haiku 4.5 | $0.00003 | $0.00113 |
Grade A, and why
power-flow-data 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.
This is a copy
100% identical to power-flow-data — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 152 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Power Flow Data Guide
Network data follows the MATPOWER format, a standard for power system test cases. The data comes from the PGLib-OPF benchmark library (github.com/power-grid-lib/pglib-opf).
⚠️ Important: Handling Large Network Files
Network JSON files can be very large (100K+ lines for realistic grids). Never read line-by-line with sed, head, or similar tools — this wastes time and context.
Always use Python's JSON parser directly:
import json
# This is fast even for multi-MB files
with open('network.json') as f:
data = json.load(f)
# Quick summary (do this first!)
print(f"Buses: {len(data['bus'])}")
print(f"Generators: {len(data['gen'])}")
print(f"Branches: {len(data['branch'])}")
print(f"Total load: {sum(b[2] for b in data['bus']):.1f} MW")
Quick file size check (if needed):
wc -l network.json # Line count
du -h network.json # File size
Network Topology Concepts
Bus Types
Power system buses are classified by what is specified vs. solved:
| Type | Code | Specified | Solved | Description |
|---|---|---|---|---|
| Slack | 3 | V, θ=0 | P, Q | Reference bus, balances power |
| PV | 2 | P, V | Q, θ | Generator bus with voltage control |
| PQ | 1 | P, Q | V, θ | Load bus |
Per-Unit System
All electrical quantities normalized to base values:
baseMVA = 100 # Typical base power
# Conversions
P_pu = P_MW / baseMVA
Q_pu = Q_MVAr / baseMVA
S_pu = S_MVA / baseMVA
Loading Network Data
import json
import numpy as np
def load_network(filepath):
"""Load network data from JSON."""
with open(filepath) as f:
data = json.load(f)
return {
'baseMVA': data['baseMVA'],
'bus': np.array(data['bus']),
'gen': np.array(data['gen']),
'branch': np.array(data['branch']),
'gencost': np.array(data['gencost']),
'reserve_capacity': np.array(data['reserve_capacity']), # MW per generator
'reserve_requirement': data['reserve_requirement'] # MW total
}
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.
- 9d ago First seen · 152 lines · 27 tokens per session scan A 7c6544423d41
power-flow-data is a skill published in the GitHub repository xuansenpa1/skillrevise (55 stars, last pushed 4d ago), licensed MIT. It adds 27 tokens to every session and 1,134 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to power-flow-data, differing in 0 lines, and is treated as a copy.
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