flight-controls
- Repo stars 0
- Author updated Live
- Author repo AGI_engineering_forge
- Domain
- Design
- Compatible agents
-
- Claude Code
- Cursor
- Cline
- Codex
- Windsurf
- Gemini CLI
- +20
- Trust score
- 88 / 100 · community maintained
- Author / version / license
- @00000star · no license declared
- Token usage
- Lean
- Setup complexity
- Plug-and-play
- External API key
- Not required
- Operating systems
- Unspecified (assume cross-platform)
- Runtime requirements
- No special requirements
- Permissions
-
- Read-only
- Write / modify
- Network behavior
- Local-only
- Install commands
- 26 variants
Profile is derived at build time from SKILL.md and install vectors. Subject to drift from author intent.
Heads up: 未限定 allowed-tools，默认拥有全部工具权限。
---
name: flight-controls
description: Design and simulate control systems — transfer functions, PID controllers, Bode plots, root locu…
category: design
runtime: no special runtime
---
# flight-controls output preview
## PART A: Task fit
- Use case: Design and simulate control systems — transfer functions, PID controllers, Bode plots, root locus, stability analysis, state-space modeling. Uses scipy.signal and sympy..
- Inputs: target material, constraints, expected output, and acceptance criteria.
- Evidence boundary: follow “Usage” and do not present inference as author intent.
## PART B: Execution result
- **01** The card summarizes the use case; runtime output centers on “Design and simulate control systems — transfer functions, PID controllers, Bode plots, root locus, stability analysis, state-space modeling. Uses scipy.signal and sympy.”.
- **02** When the source has headings, the agent prioritizes “Usage” so the result follows the author’s structure.
- **03** Typical output includes task judgment, concrete steps, required commands or file edits, validation, and follow-up options.
- **04** Risk context follows the fingerprint: read files, write/modify files; mostly runs locally; usually needs no extra API key.
## Running Rules
- read files, write/modify files; mostly runs locally; usually needs no extra API key.
- Validate with a small sample before expanding scope.
- Return the result, validation criteria, and next iteration options. Choose the trigger
The source mentions slash commands such as `/workspace`; use them first when your agent supports command triggers.
Provide inputs and boundaries
Name target files or source material, expected output, forbidden changes, and whether network or shell access is allowed. Permission fingerprint: read files, write/modify files.
Validate with a small run
Start with a small task and check whether the result follows “Usage”. Inspect diffs, logs, previews, or tests before expanding scope.
Review before delivery
Confirm the final output includes a concrete result, evidence, and next action. If it stays generic, tighten inputs, boundaries, and acceptance criteria.
---
name: flight-controls
description: Design and simulate control systems — transfer functions, PID controllers, Bode plots, root locu…
category: design
source: 00000star/AGI_engineering_forge
---
# flight-controls
## When to use
- Design and simulate control systems — transfer functions, PID controllers, Bode plots, root locus, stability analysis…
- Use it when the task has clear inputs, repeatable steps, and validation criteria.
## What to provide
- Target material, scope, expected result, and forbidden changes.
- Whether network, commands, file writes, or external services are allowed.
## Execution rules
- Organize steps around “Usage” and keep inference separate from source facts.
- read files, write/modify files; mostly runs locally; usually needs no extra API key.
- Validate with a small sample before expanding the task.
## Output requirements
- Return the deliverable, key evidence, validation method, and next action.
- Mark missing information as unknown; do not invent commands, platforms, or dependencies. Evidence boundary and execution chain
The author source anchors workflow facts; repository files anchor sources and commands; Fluxly only adds fit, limitations, and quality judgment.
skill "flight-controls" {
input -> user goal + target files + boundaries + acceptance criteria
context -> Usage
rules -> SKILL.md triggers / order / output contract
runtime -> no special runtime | read files, write/modify files | mostly runs locally
guardrails -> usually needs no extra API key + small-sample validation + diff/log review
output -> copyable result + checklist + next iteration
}Control Systems Engineering
Usage
# PID step response
python3 /workspace/bridge.py scipy_solver '
from scipy import signal
num = [129.6, 324, 81]
den = [15, 131.6, 324, 81]
sys = signal.TransferFunction(num, den)
t, y = signal.step(sys, T=np.linspace(0, 5, 1000))
overshoot = (max(y) - 1.0) * 100
print(f"Overshoot: {overshoot:.1f}%")
print(f"Final value: {y[-1]:.4f}")
'
# Symbolic transfer function
python3 /workspace/bridge.py sympy_math '
s = symbols("s")
G = 100 / (s**2 + 10*s + 100)
print(f"DC gain: {limit(G, s, 0)}")
print(f"Poles: {solve(s**2 + 10*s + 100, s)}")
'For visualization (Bode plots, step response plots):
python3 /workspace/bridge.py matplotlib_plot 'YOUR_PLOTTING_CODE'
Decide Fit First
Design Intent
How To Use It
Boundaries And Review