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training-log-analyzer — Claude Code skill: read your training log

Turns a workout log into a report: improvement trends, plateaus, recovery needs, peak-form windows and injury risk signals. Useful when progress stalls.

Install into Claude Code · Skills CLI (Vercel) All methods and platforms ↓
npx skills add OneWave-AI/claude-skills --skill training-log-analyzer -a claude-code
Open on GitHub

What training-log-analyzer does

The skill casts your agent as a sports scientist. You hand it training records, and it returns a fixed-format report with a results section and a recommendations section. The instructions name what to look for: improvement trends, plateau periods, rest and recovery needs, peak performance windows, injury risk indicators, and data-driven adjustments.

Install it with npx skills add on Claude, Codex, Cursor, Gemini CLI or OpenCode; GitHub Copilot uses gh skill install. The skill file lands in the platform's skills directory, for example ~/.claude/skills/training-log-analyzer/SKILL.md. Nothing external is called, so there are no keys to configure.

What you get out depends on what you put in. A log of dates and weights alone gives thin evidence for recovery and injury-risk claims, so fill in sets, sleep and how you felt before expecting sharp conclusions. The output format stays the same each run, which makes month-to-month comparison easy.

What it helps with

  • find the month your bench press stalled
  • tell a real plateau from a run of bad sleep
  • decide when to add a rest day
  • time peak form to a competition date
  • spot overload signs before an injury lands

Example prompts for the agent

  • Here is my training log for the last three months — find the plateau periods and tell me where recovery is missing
  • Analyze the log and tell me when my peak performance window was
  • Build a report from my workouts: trends, plateaus and injury risk

How to install training-log-analyzer

1Skills CLI (Vercel)

npx skills add OneWave-AI/claude-skills --skill training-log-analyzer -a claude-code

2Manually: put the files in place

~/.claude/skills/training-log-analyzer/SKILL.md

Copy the whole skill folder; for one project use .claude/skills/training-log-analyzer/

Step by step, with commands for each platform: How to install skills in Claude Code: five ways

Questions about training-log-analyzer

How do I install training-log-analyzer in Claude?

Run npx skills add OneWave-AI/claude-skills --skill training-log-analyzer -a claude-code. The skill file then sits at ~/.claude/skills/training-log-analyzer/SKILL.md.

What does training-log-analyzer do?

It reads your workout records and returns a report with results and recommendations: trends, plateau periods, recovery needs, peak performance windows and injury risk indicators.

Does it need an API key or any external service?

No. It works on the log text you pass to the agent and does not call outside services.

Source text

SKILL.md · MIT
---
name: training-log-analyzer
description: Track workouts, stats, progress over time. Identify improvement areas, plateaus, rest/recovery needs, peak performance timing, injury risk.
---

# Training Log Analyzer
Track workouts, stats, progress over time. Identify improvement areas, plateaus, rest/recovery needs, peak performance timing, injury risk.

## Instructions

You are an expert sports scientist and performance analyst. Analyze training logs to identify: improvement trends, plateau periods, rest/recovery needs, peak performance windows, injury risk indicators, and data-driven training adjustments.

### Output Format

```markdown
# Training Log Analyzer Output

**Generated**: {timestamp}

---

## Results

[Your formatted output here]

---

## Recommendations

[Actionable next steps]

```

### Best Practices

1. **Be Specific**: Focus on concrete, actionable outputs
2. **Use Templates**: Provide copy-paste ready formats
3. **Include Examples**: Show real-world usage
4. **Add Context**: Explain why recommendations matter
5. **Stay Current**: Use latest best practices for fitness

### Common Use Cases

**Trigger Phrases**:
- "Help me with [use case]"
- "Generate [output type]"
- "Create [deliverable]"

**Example Request**:
> "[Sample user request here]"

**Response Approach**:
1. Understand user's context and goals
2. Generate comprehensive output
3. Provide actionable recommendations
4. Include examples and templates
5. Suggest next steps

Remember: Focus on delivering value quickly and clearly!

© OneWave-AI · MIT · OneWave-AI/claude-skills

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