Signals
PostHog/posthog
How to query the documentembeddings table for raw signal data using HogQL.
Design effective excitation signals (step tests) for system identification and parameter estimation in control systems.
Apache-2.0Auto-check passed
Install Excitation Signal Design
$ npx skills add benchflow-ai/skillsbench --skill excitation-signal-design -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install benchflow-ai/skillsbench excitation-signal-design --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/benchflow-ai/skillsbench.git skills-src && mkdir -p .claude/skills && cp -r skills-src/tasks/hvac-control/environment/skills/excitation-signal-design .claude/skills/excitation-signal-design && rm -rf skills-srcUse ~/.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/
Install the "excitation-signal-design" agent skill from https://github.com/benchflow-ai/skillsbench/tree/main/tasks/hvac-control/environment/skills/excitation-signal-design into .claude/skills/excitation-signal-design/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "excitation-signal-design", 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 install https://github.com/benchflow-ai/skillsbench/tree/main/tasks/hvac-control/environment/skills/excitation-signal-designType 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.
$ npx skills add benchflow-ai/skillsbench --skill excitation-signal-design -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install benchflow-ai/skillsbench excitation-signal-design --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/benchflow-ai/skillsbench.git skills-src && mkdir -p .agents/skills && cp -r skills-src/tasks/hvac-control/environment/skills/excitation-signal-design .agents/skills/excitation-signal-design && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "excitation-signal-design" agent skill from https://github.com/benchflow-ai/skillsbench/tree/main/tasks/hvac-control/environment/skills/excitation-signal-design into .agents/skills/excitation-signal-design/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "excitation-signal-design", 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.
$ npx skills add benchflow-ai/skillsbench --skill excitation-signal-design -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install benchflow-ai/skillsbench excitation-signal-design --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/benchflow-ai/skillsbench.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/tasks/hvac-control/environment/skills/excitation-signal-design .cursor/skills/excitation-signal-design && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "excitation-signal-design" agent skill from https://github.com/benchflow-ai/skillsbench/tree/main/tasks/hvac-control/environment/skills/excitation-signal-design into .cursor/skills/excitation-signal-design/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "excitation-signal-design", 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 https://github.com/benchflow-ai/skillsbench.git --path tasks/hvac-control/environment/skills/excitation-signal-design--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add benchflow-ai/skillsbench --skill excitation-signal-design -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install benchflow-ai/skillsbench excitation-signal-design --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/benchflow-ai/skillsbench.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/tasks/hvac-control/environment/skills/excitation-signal-design .gemini/skills/excitation-signal-design && rm -rf skills-srcUse ~/.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/
Install the "excitation-signal-design" agent skill from https://github.com/benchflow-ai/skillsbench/tree/main/tasks/hvac-control/environment/skills/excitation-signal-design into .gemini/skills/excitation-signal-design/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "excitation-signal-design", 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.
$ gh skill install benchflow-ai/skillsbench excitation-signal-designInstalls 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).
$ npx skills add benchflow-ai/skillsbench --skill excitation-signal-design -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/benchflow-ai/skillsbench.git skills-src && mkdir -p .github/skills && cp -r skills-src/tasks/hvac-control/environment/skills/excitation-signal-design .github/skills/excitation-signal-design && rm -rf skills-srcUse ~/.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/
Install the "excitation-signal-design" agent skill from https://github.com/benchflow-ai/skillsbench/tree/main/tasks/hvac-control/environment/skills/excitation-signal-design into .github/skills/excitation-signal-design/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "excitation-signal-design", 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.
$ npx skills add benchflow-ai/skillsbench --skill excitation-signal-design -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install benchflow-ai/skillsbench excitation-signal-design --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/benchflow-ai/skillsbench.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/tasks/hvac-control/environment/skills/excitation-signal-design .opencode/skills/excitation-signal-design && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "excitation-signal-design" agent skill from https://github.com/benchflow-ai/skillsbench/tree/main/tasks/hvac-control/environment/skills/excitation-signal-design into .opencode/skills/excitation-signal-design/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "excitation-signal-design", 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
excitation-signal-design- GitHub stars
- 1.8k
- Token cost
- ~643 tokens
- SKILL.md length
- 309 words
- Files
- 1
- Skills in repo
- 189
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
Design effective excitation signals (step tests) for system identification and parameter estimation in control systems.
- Works in 4 steps: Start at steady state: Ensure the system… → Apply a step input: Change the input… → Hold for sufficient duration: Wait long… → …
- SKILL.md covers Overview, Step Test Method, Duration Guidelines and Sample Rate Selection, plus 3 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Excitation Signal Design is an agent skill from benchflow-ai/skillsbench. Design effective excitation signals (step tests) for system identification and parameter estimation in control systems.
Its SKILL.md is about 640 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
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.
Example prompts
- “/excitation-signal-design”
Requirements
- Python 3
Workflow steps
4 steps, taken from the first numbered list in SKILL.md.
- Start at steady state: Ensure the system is stable at a known operating point
- Apply a step input: Change the input from zero to a constant value
- Hold for sufficient duration: Wait long enough to observe the full response
- Record the response: Capture input and output data at regular intervals
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
No scripts in the folder and no shell commands in SKILL.md (its code samples are python).
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
Excitation Signal Design loads about 643 tokens when it runs. Until then it costs about 36 tokens; SKILL.md has 309 words of instructions outside code blocks.
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); files beside SKILL.md are not scanned.
SKILL.md
The full file from benchflow-ai/skillsbench at commit 9a1f4dd, republished under its Apache-2.0 licence (© benchflow-ai). 309 words, ~643 tokens.
Download SKILL.mdSave it as
.claude/skills/excitation-signal-design/SKILL.md (or your agent's skills folder).- name
- excitation-signal-design
- description
- Design effective excitation signals (step tests) for system identification and parameter estimation in control systems.
Excitation Signal Design for System Identification
Overview
When identifying the dynamics of an unknown system, you must excite the system with a known input and observe its response. This skill describes how to design effective excitation signals for parameter estimation.
Step Test Method
The simplest excitation signal for first-order systems is a step test:
- Start at steady state: Ensure the system is stable at a known operating point
- Apply a step input: Change the input from zero to a constant value
- Hold for sufficient duration: Wait long enough to observe the full response
- Record the response: Capture input and output data at regular intervals
Duration Guidelines
The test should run long enough to capture the system dynamics:
- Minimum: At least 2-3 time constants to see the response shape
- Recommended: 3-5 time constants for accurate parameter estimation
- Rule of thumb: If the output appears to have settled, you've collected enough data
Sample Rate Selection
Choose a sample rate that captures the transient behavior:
- Too slow: Miss important dynamics during the rise phase
- Too fast: Excessive data without added information
- Good practice: At least 10-20 samples per time constant
Data Collection
During the step test, record:
- Time (from start of test)
- Output measurement (with sensor noise)
- Input command
# Example data collection pattern
data = []
for step in range(num_steps):
result = system.step(input_value)
data.append({
"time": result["time"],
"output": result["output"],
"input": result["input"]
})Expected Response Shape
For a first-order system, the step response follows an exponential curve:
- Initial: Output at starting value
- Rising: Exponential approach toward new steady state
- Final: Asymptotically approaches steady-state value
The response follows: y(t) = y_initial + K*u*(1 - exp(-t/tau))
Where K is the process gain and tau is the time constant.
Tips
- Sufficient duration: Cutting the test short means incomplete data for fitting
- Moderate input: Use an input level that produces a measurable response without saturating
- Noise is normal: Real sensors have measurement noise; don't over-smooth the data
- One good test: A single well-executed step test often provides sufficient data
© benchflow-ai, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in tasks/hvac-control/environment/skills/excitation-signal-design of benchflow-ai/skillsbench.
Open the folder on GitHubat commit 9a1f4dd
Compare with similar skills
Excitation Signal Design 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Excitation Signal Design this skillbenchflow-ai/skillsbench | 1.8k | — | ~643 | Automated safety check: Pass | Apache-2.0 | |
| SignalsPostHog/posthog | 40k | — | ~4.3k | Automated safety check: Pass | Custom licence | |
| Add Effectremotion-dev/remotion | 63k | — | ~2.8k | Automated safety check: Pass | Custom licence | |
| Effect V4ComposioHQ/composio | 30k | — | ~1k | Automated safety check: Pass | MIT | |
| Trader Signalruvnet/ruflo | 74k | — | ~605 | Automated safety check: Notes | MIT | |
| Parallax Effectsthedaviddias/Front-End-Checklist | 74k | — | ~523 | Automated safety check: Pass | MIT |
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Questions about Excitation Signal Design
What does Excitation Signal Design do?
Design effective excitation signals (step tests) for system identification and parameter estimation in control systems. Excitation Signal Design is an agent skill from benchflow-ai/skillsbench. Design effective excitation signals (step tests) for system identification and parameter estimation in control systems.
How do I install Excitation Signal Design in Claude Code?
Run `npx skills add benchflow-ai/skillsbench --skill excitation-signal-design -a claude-code`. Or copy the skill folder (tasks/hvac-control/environment/skills/excitation-signal-design in benchflow-ai/skillsbench) into .claude/skills/excitation-signal-design in your project. Claude Code loads it when a task matches its description.
How do I install Excitation Signal Design in Codex?
Run `npx skills add benchflow-ai/skillsbench --skill excitation-signal-design -a codex`. Or copy the skill folder (tasks/hvac-control/environment/skills/excitation-signal-design in benchflow-ai/skillsbench) into .agents/skills/excitation-signal-design in your project. Codex loads it when a task matches its description.
Can I use Excitation Signal Design 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 excitation-signal-design -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/excitation-signal-design, .gemini/skills/excitation-signal-design, .github/skills/excitation-signal-design and .opencode/skills/excitation-signal-design in your project.
What does Excitation Signal Design need to run?
SKILL.md names no scripts, command-line tools or credentials: Excitation Signal Design is instructions for the agent only. Our summary lists: Python 3.
Does Excitation Signal Design 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 Excitation Signal Design 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. Review the folder before installing.
What licence does Excitation Signal Design use?
Excitation Signal Design 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 Excitation Signal Design use?
About 643 tokens (SKILL.md is roughly 2.6k 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 Excitation Signal Design?
Skills that share tags, products or a category with Excitation Signal Design: Signals (PostHog/posthog, 40k stars), Add Effect (remotion-dev/remotion, 63k stars), Effect V4 (ComposioHQ/composio, 30k stars) and Trader Signal (ruvnet/ruflo, 74k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Excitation Signal Design?
benchflow-ai (a GitHub organization) maintains it in benchflow-ai/skillsbench, which has 1,835 GitHub stars. The repository holds 189 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.