Fitness Insights

Use the bundled wrapper script to run the local analysis CLI:

scripts/run_fitness_insights.sh --help

This skill is for the second step of the workflow: the vault already contains activity notes, and the user now wants richer analysis and visualization on top of that note set.

When To Use It

Use this skill when the user wants to:

• analyze workout notes already written into Obsidian
• regenerate advanced dashboards after a new fitness-agent sync
• inspect recent load, consistency, monotony, or ACWR-style proxy metrics
• create visual trend notes from note-level fitness data
• review data quality, stream coverage, and running-efficiency proxies

Do not use this skill to authenticate with Strava or fetch activities. Use fitness-agent first for ingest and sync, then use fitness-insights for post-sync analysis.

Workflow

1. Confirm the vault already has notes under Fitness/Strava/Activities/ or another configured root.
2. Run the refresh command to scan existing notes and compute summary metrics.
3. Write the generated .base file and Markdown reports into Insights/.
4. Surface the exact paths that were written so the user can open them in Obsidian.
5. Explain that the load and efficiency numbers are heuristic proxies derived from note-level fields, not medical or lab-grade metrics.

Command

Refresh the insights package from the configured vault:

scripts/run_fitness_insights.sh analyze refresh

Override the vault path or root folder when needed:

scripts/run_fitness_insights.sh \
  --vault-path "/path/to/YourVault" \
  --root-folder "Fitness/Strava" \
  analyze refresh \
  --weeks 16

Outputs

The skill writes these artifacts under the configured root folder:

• Insights/Fitness Insights.base
• Insights/Fitness Insights.md
• Insights/Fitness Snapshot.md
• Insights/Training Trends.md

These files are built from existing activity notes and can be regenerated safely at any time.

Guardrails

• Treat ACWR, monotony, strain, and efficiency as planning proxies only.
• Stop and report configuration or parsing errors instead of guessing missing vault paths.
• Default to ~/.fitness-agent/config.json when the user does not provide overrides.
• Prefer regenerating the analysis package rather than editing generated reports by hand.
• Be explicit that this skill depends on the frontmatter produced by fitness-agent.

Trigger Examples

• $fitness-insights 重新分析我 vault 里的运动笔记并生成新的可视化
• $fitness-insights 基于现有 Obsidian 数据做训练负荷和趋势分析
• $fitness-insights 刷新最近 16 周的训练趋势图

Resources

• fitness_insights.py: self-contained CLI entrypoint packaged with the skill.
• src/fitness_insights/: parser, analysis engine, and output generators.
• scripts/run_fitness_insights.sh: stable wrapper for local execution.
• references/metrics.md: metric definitions and scientific caution language.