Agens timesfm_forecasting

skill_id: timesfm_forecasting name: timesfm-forecasting description: Zero-shot time series forecasting with Google's TimesFM foundation model. Use for any univariate time series (sales, sensors, energy, vitals, weather) without training a custom model. Supports CSV/DataFrame/array inputs with point forecasts and prediction intervals. Includes a preflight system checker script to verify RAM/GPU before first use. version: 1.0.0 author: Clayton Young / Superior Byte Works, LLC (@borealBytes) license: Apache-2.0 license tags:

• scientific-agent-skills
• timesfm-forecasting tools:
• Read
• Write
• Edit
• Bash permissions: network: true filesystem: true shell: true agents:
• executor_agent enabled: true source: scientific-agent-skills entrypoint: entry.py readme: README.md input_schema: {} output_schema: type: object metadata: upstream_repo: K-Dense-AI/scientific-agent-skills upstream_skill: timesfm-forecasting upstream_path: scientific-skills/timesfm-forecasting/SKILL.md upstream_frontmatter: name: timesfm-forecasting description: Zero-shot time series forecasting with Google's TimesFM foundation model. Use for any univariate time series (sales, sensors, energy, vitals, weather) without training a custom model. Supports CSV/DataFrame/array inputs with point forecasts and prediction intervals. Includes a preflight system checker script to verify RAM/GPU before first use. allowed-tools: Read Write Edit Bash license: Apache-2.0 license metadata: skill-author: Clayton Young / Superior Byte Works, LLC (@borealBytes) skill-version: 1.0.0