TimesFM Forecasting
google-research/timesfm
Forecasts any univariate time series zero-shot with Google's TimesFM model, returning point forecasts and calibrated prediction intervals without training.
Estimate heart rate (HR) and breathing rate (BR) in bpm from a cleaned 1-D physiological time series such as radar phase, WiFi CSI amplitude, PPG, or a chest-motion signal.
$ npx skills add benchflow-ai/skillsbench --skill vital-sign-extraction -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install benchflow-ai/skillsbench vital-sign-extraction --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/radar-vital-signs/environment/skills/vital-sign-extraction .claude/skills/vital-sign-extraction && 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 "vital-sign-extraction" agent skill from https://github.com/benchflow-ai/skillsbench/tree/main/tasks/radar-vital-signs/environment/skills/vital-sign-extraction into .claude/skills/vital-sign-extraction/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "vital-sign-extraction", 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/radar-vital-signs/environment/skills/vital-sign-extractionType 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 vital-sign-extraction -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install benchflow-ai/skillsbench vital-sign-extraction --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/radar-vital-signs/environment/skills/vital-sign-extraction .agents/skills/vital-sign-extraction && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "vital-sign-extraction" agent skill from https://github.com/benchflow-ai/skillsbench/tree/main/tasks/radar-vital-signs/environment/skills/vital-sign-extraction into .agents/skills/vital-sign-extraction/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "vital-sign-extraction", 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 vital-sign-extraction -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install benchflow-ai/skillsbench vital-sign-extraction --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/radar-vital-signs/environment/skills/vital-sign-extraction .cursor/skills/vital-sign-extraction && 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 "vital-sign-extraction" agent skill from https://github.com/benchflow-ai/skillsbench/tree/main/tasks/radar-vital-signs/environment/skills/vital-sign-extraction into .cursor/skills/vital-sign-extraction/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "vital-sign-extraction", 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/radar-vital-signs/environment/skills/vital-sign-extraction--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 vital-sign-extraction -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install benchflow-ai/skillsbench vital-sign-extraction --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/radar-vital-signs/environment/skills/vital-sign-extraction .gemini/skills/vital-sign-extraction && 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 "vital-sign-extraction" agent skill from https://github.com/benchflow-ai/skillsbench/tree/main/tasks/radar-vital-signs/environment/skills/vital-sign-extraction into .gemini/skills/vital-sign-extraction/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "vital-sign-extraction", 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 vital-sign-extractionInstalls 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 vital-sign-extraction -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/radar-vital-signs/environment/skills/vital-sign-extraction .github/skills/vital-sign-extraction && 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 "vital-sign-extraction" agent skill from https://github.com/benchflow-ai/skillsbench/tree/main/tasks/radar-vital-signs/environment/skills/vital-sign-extraction into .github/skills/vital-sign-extraction/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "vital-sign-extraction", 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 vital-sign-extraction -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 vital-sign-extraction --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/radar-vital-signs/environment/skills/vital-sign-extraction .opencode/skills/vital-sign-extraction && 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 "vital-sign-extraction" agent skill from https://github.com/benchflow-ai/skillsbench/tree/main/tasks/radar-vital-signs/environment/skills/vital-sign-extraction into .opencode/skills/vital-sign-extraction/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "vital-sign-extraction", 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.
vital-sign-extractionEstimate heart rate (HR) and breathing rate (BR) in bpm from a cleaned 1-D physiological time series such as radar phase, WiFi CSI amplitude, PPG, or a chest-motion signal.
Vital Sign Extraction is an agent skill from benchflow-ai/skillsbench. Estimate heart rate (HR) and breathing rate (BR) in bpm from a cleaned 1-D physiological time series such as radar phase, WiFi CSI amplitude, PPG, or a chest-motion signal. Use when Claude needs to choose HR/BR bandpass edges, pick a peak frequency from a noisy band, reject the HR second harmonic that often dominates the fundamental, handle respiration-harmonic leakage into the HR band on slow breathers, or flag low-confidence estimates. Not for arrhythmia / beat-to-beat analysis, multi-subject source separation…
Its SKILL.md is about 930 tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files, including reference files (for example `references/band-rationale.md` and `references/harmonic-pitfalls.md`).
It sits in Data & Analytics, covering Forecasting and time series. 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.
4 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit 9a1f4dd. It shows what the files ask for, not the result of running them.
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.
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.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Vital Sign Extraction loads about 925 tokens when it runs, and up to ~2.6k if it reads all its reference files. Until then it costs about 143 tokens; SKILL.md has 301 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.
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.
The full file from benchflow-ai/skillsbench at commit 9a1f4dd, republished under its Apache-2.0 licence (© benchflow-ai). 301 words, ~925 tokens.
.claude/skills/vital-sign-extraction/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.Given a cleaned 1-D periodic signal (radar phase, WiFi CSI, PPG, piezo), estimate heart rate and breathing rate in bpm.
Upstream ingestion of radar captures is the radar-signal-processing skill. This skill picks up after a 1-D signal is extracted.
butter(4, [0.08, 0.5], btype='band', fs=fs) — 4.8–30 bpmbutter(4, [0.7, 3.0], btype='band', fs=fs) — 42–180 bpmnperseg = min(len(x), int(fs * 25))
f, p = welch(x, fs=fs, nperseg=nperseg, noverlap=nperseg//2,
nfft=8*nperseg, detrend='constant')
in_band = (f >= lo) & (f <= hi)
peak_hz = f[in_band][np.argmax(p[in_band])]f_sub = f_peak / 2.0
if 0.7 <= f_sub <= 3.0:
p_sub = np.interp(f_sub, f, p)
p_top = np.interp(f_peak, f, p)
if p_sub > 0.5 * p_top:
f_peak = f_sub # the peak was the 2nd harmonic
hr_bpm = f_peak * 60ac = np.correlate(x - x.mean(), x - x.mean(), mode='full')
ac = ac[len(ac)//2:] / ac[len(ac)//2]
lag = int(fs/f_hi) + np.argmax(ac[int(fs/f_hi):int(fs/f_lo)])
bpm_ac = 60 * fs / lagabs(bpm_ac - bpm_psd) > 5, flag as low confidence.| If | Then |
|---|---|
f_peak/2 in HR band and p_sub > 0.5 × p_top | Pick sub-harmonic (fundamental) |
| PSD and autocorrelation disagree by > 5 bpm | Flag low confidence; do not commit to one value |
| BR estimate < 10 bpm (slow breather) | Expect HR-band contamination — see references/harmonic-pitfalls.md |
| HR > 150 bpm (tachycardia) | Widen HR band upper to 3.3 Hz, re-estimate |
| Clip < 15 s long | PSD bin spacing > tolerance — prefer autocorrelation or flag inconclusive |
BR < HR. Always true for a live adult at rest — if violated you swapped bands.HR × duration_minutes ≈ peak count in find_peaks(bandpassed_hr). Off by 2× → harmonic error slipped through.See references/band-rationale.md. Short version: textbook bands miss slow breathers (supine clinical subjects breathe 5–10 bpm) and bradycardia (athletes, post-tilt-down).
See references/harmonic-pitfalls.md. These are the two failure modes that cost naïve pipelines the most accuracy on real 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
SKILL.md and 2 other files (references) in tasks/radar-vital-signs/environment/skills/vital-sign-extraction of benchflow-ai/skillsbench.
Open the folder on GitHubat commit 9a1f4dd
Vital Sign Extraction 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 |
|---|---|---|---|---|---|---|
| Vital Sign Extraction this skillbenchflow-ai/skillsbench | 1.8k | — | ~925 | Automated safety check: Pass | Apache-2.0 | |
| TimesFM Forecastinggoogle-research/timesfm | 34k | — | ~4.7k | Automated safety check: Pass | Apache-2.0 | |
| StatsmodelszLanqing/codex-claude-academic-skills | 4.7k | 15 repos | ~4.9k | Automated safety check: Pass | BSD-3-Clause | |
| Timesfm ForecastingzLanqing/codex-claude-academic-skills | 4.7k | 3 repos | ~7.5k | Automated safety check: Notes | Apache-2.0 | |
| Find Hypertable Candidatestimescale/pg-aiguide | 1.9k | 1 repos | ~2.6k | Automated safety check: Pass | Apache-2.0 | |
| Pensieve Searcharkohut/pensieve | 1.4k | — | ~8.2k | Automated safety check: Pass | Apache-2.0 |
google-research/timesfm
Forecasts any univariate time series zero-shot with Google's TimesFM model, returning point forecasts and calibrated prediction intervals without training.
zLanqing/codex-claude-academic-skills
Statistical models library for Python. An agent skill from zLanqing/codex-claude-academic-skills.
zLanqing/codex-claude-academic-skills
Zero-shot time series forecasting with Google's TimesFM foundation model.
timescale/pg-aiguide
A skill your agent uses to analyze an existing PostgreSQL database and identify which tables should be converted to Timescale/TimescaleDB hypertables.
arkohut/pensieve
Search the user's local Pensieve screenshot archive by text, app, or time range.
ninehills/skills
Market prediction skill using Kronos. An agent skill from ninehills/skills.
benchflow-ai/skillsbench
This skill should be used when working on Lean 4 formalization projects to maintain persistent memory of successful proof patterns, failed approaches, project conventions, and user preferences…
benchflow-ai/skillsbench
World-class data engineering skill for building scalable data pipelines, ETL/ELT systems, real-time streaming, and data infrastructure.
benchflow-ai/skillsbench
AC branch pi-model power flow equations (P/Q and |S|) with transformer tap ratio and phase shift, matching acopf-math-model.md and MATPOWER branch fields.
benchflow-ai/skillsbench
Civilization 6 district mechanics library. An agent skill from benchflow-ai/skillsbench.
benchflow-ai/skillsbench
Build deterministic, verifiable data visualizations with D3.js (v6).
benchflow-ai/skillsbench
DC power flow analysis for power systems. An agent skill from benchflow-ai/skillsbench.
Categories
Estimate heart rate (HR) and breathing rate (BR) in bpm from a cleaned 1-D physiological time series such as radar phase, WiFi CSI amplitude, PPG, or a chest-motion signal. Vital Sign Extraction is an agent skill from benchflow-ai/skillsbench. Estimate heart rate (HR) and breathing rate (BR) in bpm from a cleaned 1-D physiological time series such as radar phase, WiFi CSI amplitude, PPG, or a chest-motion signal.
Vital Sign Extraction fits situations like: Claude needs to choose HR/BR bandpass edges; pick a peak frequency from a noisy band; reject the HR second harmonic that often dominates the fundamental; handle respiration-harmonic leakage into the HR band on slow breathers.
Run `npx skills add benchflow-ai/skillsbench --skill vital-sign-extraction -a claude-code`. Or copy the skill folder (tasks/radar-vital-signs/environment/skills/vital-sign-extraction in benchflow-ai/skillsbench) into .claude/skills/vital-sign-extraction in your project. Claude Code loads it when a task matches its description.
Run `npx skills add benchflow-ai/skillsbench --skill vital-sign-extraction -a codex`. Or copy the skill folder (tasks/radar-vital-signs/environment/skills/vital-sign-extraction in benchflow-ai/skillsbench) into .agents/skills/vital-sign-extraction in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add benchflow-ai/skillsbench --skill vital-sign-extraction -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/vital-sign-extraction, .gemini/skills/vital-sign-extraction, .github/skills/vital-sign-extraction and .opencode/skills/vital-sign-extraction in your project.
SKILL.md names no scripts, command-line tools or credentials: Vital Sign Extraction is instructions for the agent only. Our summary lists: Python 3.
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.
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.
Vital Sign Extraction 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.
About 925 tokens (SKILL.md is roughly 3.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.7k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Vital Sign Extraction: TimesFM Forecasting (google-research/timesfm, 34k stars), Statsmodels (zLanqing/codex-claude-academic-skills, 4.7k stars), Timesfm Forecasting (zLanqing/codex-claude-academic-skills, 4.7k stars) and Find Hypertable Candidates (timescale/pg-aiguide, 1.9k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
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.