Agent skill

Dc Power Flow

by benchflow-ai in benchflow-ai/skillsbench

DC power flow analysis for power systems. An agent skill from benchflow-ai/skillsbench.

Apache-2.0Auto-check passed

Install Dc Power Flow

skills CLI

$ npx skills add benchflow-ai/skillsbench --skill dc-power-flow -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI

$ gh skill install benchflow-ai/skillsbench dc-power-flow --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy

$ git clone --depth 1 https://github.com/benchflow-ai/skillsbench.git skills-src && mkdir -p .claude/skills && cp -r skills-src/tasks/energy-market-pricing/environment/skills/dc-power-flow .claude/skills/dc-power-flow && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Paste into Claude Code

Install the "dc-power-flow" agent skill from https://github.com/benchflow-ai/skillsbench/tree/main/tasks/energy-market-pricing/environment/skills/dc-power-flow into .claude/skills/dc-power-flow/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dc-power-flow", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/benchflow-ai/skillsbench/tree/main/tasks/energy-market-pricing/environment/skills/dc-power-flow

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add benchflow-ai/skillsbench --skill dc-power-flow -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install benchflow-ai/skillsbench dc-power-flow --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/benchflow-ai/skillsbench.git skills-src && mkdir -p .agents/skills && cp -r skills-src/tasks/energy-market-pricing/environment/skills/dc-power-flow .agents/skills/dc-power-flow && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "dc-power-flow" agent skill from https://github.com/benchflow-ai/skillsbench/tree/main/tasks/energy-market-pricing/environment/skills/dc-power-flow into .agents/skills/dc-power-flow/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dc-power-flow", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add benchflow-ai/skillsbench --skill dc-power-flow -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install benchflow-ai/skillsbench dc-power-flow --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/benchflow-ai/skillsbench.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/tasks/energy-market-pricing/environment/skills/dc-power-flow .cursor/skills/dc-power-flow && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "dc-power-flow" agent skill from https://github.com/benchflow-ai/skillsbench/tree/main/tasks/energy-market-pricing/environment/skills/dc-power-flow into .cursor/skills/dc-power-flow/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dc-power-flow", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/benchflow-ai/skillsbench.git --path tasks/energy-market-pricing/environment/skills/dc-power-flow

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add benchflow-ai/skillsbench --skill dc-power-flow -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install benchflow-ai/skillsbench dc-power-flow --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/benchflow-ai/skillsbench.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/tasks/energy-market-pricing/environment/skills/dc-power-flow .gemini/skills/dc-power-flow && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "dc-power-flow" agent skill from https://github.com/benchflow-ai/skillsbench/tree/main/tasks/energy-market-pricing/environment/skills/dc-power-flow into .gemini/skills/dc-power-flow/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dc-power-flow", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install benchflow-ai/skillsbench dc-power-flow

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add benchflow-ai/skillsbench --skill dc-power-flow -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/benchflow-ai/skillsbench.git skills-src && mkdir -p .github/skills && cp -r skills-src/tasks/energy-market-pricing/environment/skills/dc-power-flow .github/skills/dc-power-flow && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "dc-power-flow" agent skill from https://github.com/benchflow-ai/skillsbench/tree/main/tasks/energy-market-pricing/environment/skills/dc-power-flow into .github/skills/dc-power-flow/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dc-power-flow", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add benchflow-ai/skillsbench --skill dc-power-flow -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install benchflow-ai/skillsbench dc-power-flow --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/benchflow-ai/skillsbench.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/tasks/energy-market-pricing/environment/skills/dc-power-flow .opencode/skills/dc-power-flow && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "dc-power-flow" agent skill from https://github.com/benchflow-ai/skillsbench/tree/main/tasks/energy-market-pricing/environment/skills/dc-power-flow into .opencode/skills/dc-power-flow/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dc-power-flow", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: dc-power-flow
GitHub stars: 1.8k
Token cost: ~717 tokens
SKILL.md length: 182 words
Files: 2 (incl. scripts)
Skills in repo: 178
Repo updated: Jul 23, 2026
First seen: Oct 7, 2026
Licence: Apache-2.0

At a glance

DC power flow analysis for power systems. An agent skill from benchflow-ai/skillsbench.

Works in 3 steps: Lossless lines - Ignore resistance (R ≈ 0) → Flat voltage - All bus voltages = 1.0 pu → Small angles - sin(θ) ≈ θ, cos(θ) ≈ 1
Computing power flows using DC approximation
SKILL.md covers DC Approximations, Bus Number Mapping, Susceptance Matrix (B) and Power Balance Equation, plus 5 more sections
Runs Python scripts from its folder

What it does

Dc Power Flow is an agent skill from benchflow-ai/skillsbench. DC power flow analysis for power systems. Use when computing power flows using DC approximation, building susceptance matrices, calculating line flows and loading percentages, or performing sensitivity analysis on transmission networks.

Its SKILL.md is about 720 tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including scripts (for example `scripts/build_b_matrix.py`).

The repository describes itself as: SkillsBench evaluates how well skills work and how effective agents are at using them. The licence is Apache-2.0.

When your agent uses it

Computing power flows using DC approximation
Building susceptance matrices
Calculating line flows and loading percentages
Performing sensitivity analysis on transmission networks

Example prompts

“/dc-power-flow”

Requirements

Python 3

Workflow steps

3 steps, taken from the first numbered list in SKILL.md.

Lossless lines - Ignore resistance (R ≈ 0)
Flat voltage - All bus voltages = 1.0 pu
Small angles - sin(θ) ≈ θ, cos(θ) ≈ 1

What it can do on your machine

Read from SKILL.md and the folder at commit 9a1f4dd. It shows what the files ask for, not the result of running them.

Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships 1 file in scripts/ (Python), which the agent can run.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Dc Power Flow loads about 717 tokens when it runs. Until then it costs about 63 tokens; SKILL.md has 182 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~63
When it runs · the whole SKILL.md, loaded when a task matches: ~717

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from benchflow-ai/skillsbench at commit 9a1f4dd, republished under its Apache-2.0 licence (© benchflow-ai). 182 words, ~717 tokens.

Download SKILL.mdSave it as .claude/skills/dc-power-flow/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.

name: dc-power-flow
description: DC power flow analysis for power systems. Use when computing power flows using DC approximation, building susceptance matrices, calculating line flows and loading percentages, or performing sensitivity analysis on transmission networks.

DC Power Flow

DC power flow is a linearized approximation of AC power flow, suitable for economic dispatch and contingency analysis.

DC Approximations

Lossless lines - Ignore resistance (R ≈ 0)
Flat voltage - All bus voltages = 1.0 pu
Small angles - sin(θ) ≈ θ, cos(θ) ≈ 1

Result: Power flow depends only on bus angles (θ) and line reactances (X).

Bus Number Mapping

Power system bus numbers may not be contiguous (e.g., case300 has non-sequential bus IDs). Always create a mapping from bus numbers to 0-indexed array positions:

python

# Create mapping: bus_number -> 0-indexed position
bus_num_to_idx = {int(buses[i, 0]): i for i in range(n_bus)}

# Use mapping for branch endpoints
f = bus_num_to_idx[int(br[0])]  # NOT br[0] - 1
t = bus_num_to_idx[int(br[1])]

Susceptance Matrix (B)

Build from branch reactances using bus number mapping:

python

# Run: scripts/build_b_matrix.py
# Or inline:
bus_num_to_idx = {int(buses[i, 0]): i for i in range(n_bus)}
B = np.zeros((n_bus, n_bus))

for br in branches:
    f = bus_num_to_idx[int(br[0])]  # Map bus number to index
    t = bus_num_to_idx[int(br[1])]
    x = br[3]  # Reactance
    if x != 0:
        b = 1.0 / x
        B[f, f] += b
        B[t, t] += b
        B[f, t] -= b
        B[t, f] -= b

Power Balance Equation

At each bus: Pg - Pd = B[i, :] @ θ

Where:

Pg = generation at bus (pu)
Pd = load at bus (pu)
θ = vector of bus angles (radians)

Slack Bus

One bus must have θ = 0 as reference. Find slack bus (type=3):

python

slack_idx = None
for i in range(n_bus):
    if buses[i, 1] == 3:
        slack_idx = i
        break
constraints.append(theta[slack_idx] == 0)

Line Flow Calculation

Flow on branch from bus f to bus t (use bus number mapping):

python

f = bus_num_to_idx[int(br[0])]
t = bus_num_to_idx[int(br[1])]
b = 1.0 / br[3]  # Susceptance = 1/X
flow_pu = b * (theta[f] - theta[t])
flow_MW = flow_pu * baseMVA

Line Loading Percentage

python

loading_pct = abs(flow_MW) / rating_MW * 100

Where rating_MW = branch[5] (RATE_A column).

Branch Susceptances for Constraints

Store susceptances when building constraints:

python

branch_susceptances = []
for br in branches:
    x = br[3]
    b = 1.0 / x if x != 0 else 0
    branch_susceptances.append(b)

Line Flow Limits (for OPF)

Enforce thermal limits as linear constraints:

python

# |flow| <= rating  →  -rating <= flow <= rating
flow = b * (theta[f] - theta[t]) * baseMVA
constraints.append(flow <= rate)
constraints.append(flow >= -rate)

Files

SKILL.md and 1 other file (scripts) in tasks/energy-market-pricing/environment/skills/dc-power-flow of benchflow-ai/skillsbench.

SKILL.md
scripts/build_b_matrix.py

Open the folder on GitHubat commit 9a1f4dd

Compare with similar skills

Dc Power Flow next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Dc Power Flow compared with similar skills
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Dc Power Flow this skillbenchflow-ai/skillsbench	1.8k	—	~717	Automated safety check: Pass	Apache-2.0	2 mo ago
Ito Computeaffaan-m/ECC	275k	1 repos	~1.7k	Automated safety check: Pass	MIT	4 days ago
Kotlin Coroutines Flowsaffaan-m/ECC	275k	4 repos	~2k	Automated safety check: Pass	MIT	4 days ago
Kotlin Coroutines Flowsaffaan-m/ECC	275k	—	~1.7k	Automated safety check: Pass	MIT	4 days ago
Channel Message Flowsopenclaw/openclaw	392k	1 repos	~306	Automated safety check: Pass	MIT	yesterday
Login Flownexu-io/open-design	100k	—	~334	Automated safety check: Pass	Apache-2.0	yesterday

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Questions about Dc Power Flow

What does Dc Power Flow do?

DC power flow analysis for power systems. An agent skill from benchflow-ai/skillsbench. Dc Power Flow is an agent skill from benchflow-ai/skillsbench. DC power flow analysis for power systems.

When should I use Dc Power Flow?

Dc Power Flow fits situations like: computing power flows using DC approximation; building susceptance matrices; calculating line flows and loading percentages; performing sensitivity analysis on transmission networks.

How do I install Dc Power Flow in Claude Code?

Run `npx skills add benchflow-ai/skillsbench --skill dc-power-flow -a claude-code`. Or copy the skill folder (tasks/energy-market-pricing/environment/skills/dc-power-flow in benchflow-ai/skillsbench) into .claude/skills/dc-power-flow in your project. Claude Code loads it when a task matches its description.

How do I install Dc Power Flow in Codex?

Run `npx skills add benchflow-ai/skillsbench --skill dc-power-flow -a codex`. Or copy the skill folder (tasks/energy-market-pricing/environment/skills/dc-power-flow in benchflow-ai/skillsbench) into .agents/skills/dc-power-flow in your project. Codex loads it when a task matches its description.

Can I use Dc Power Flow in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add benchflow-ai/skillsbench --skill dc-power-flow -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/dc-power-flow, .gemini/skills/dc-power-flow, .github/skills/dc-power-flow and .opencode/skills/dc-power-flow in your project.

What does Dc Power Flow need to run?

Going by SKILL.md and its folder, Dc Power Flow needs Python for the scripts in its folder. Our summary lists: Python 3.

Does Dc Power Flow access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Dc Power Flow safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Dc Power Flow use?

Dc Power Flow is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Dc Power Flow use?

About 717 tokens (SKILL.md is roughly 2.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Dc Power Flow?

Skills that share tags, products or a category with Dc Power Flow: Ito Compute (affaan-m/ECC, 275k stars), Kotlin Coroutines Flows (affaan-m/ECC, 275k stars), Kotlin Coroutines Flows (affaan-m/ECC, 275k stars) and Channel Message Flows (openclaw/openclaw, 392k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Dc Power Flow?

benchflow-ai (a GitHub organization) maintains it in benchflow-ai/skillsbench, which has 1,832 GitHub stars. The repository holds 178 skills in this directory. The repository was last updated on July 23, 2026.

Source: benchflow-ai/skillsbench on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Dc Power Flow

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

Workflow steps

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

DC Power Flow

DC Approximations

Bus Number Mapping

Susceptance Matrix (B)

Power Balance Equation

Slack Bus

Line Flow Calculation

Line Loading Percentage

Branch Susceptances for Constraints

Line Flow Limits (for OPF)

Files

Compare with similar skills

Similar skills

More from benchflow-ai/skillsbench

Questions about Dc Power Flow