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personal-coach

Use this skill to identify strategic career/work insights from conversation patterns, propose one high-leverage weekly behavior change, and provide a…

Skill by baralmanish

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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

npx agentmarket install skill/baralmanish-personal-coach

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About

Use this skill to identify strategic career/work insights from conversation patterns, propose one high-leverage weekly behavior change, and provide a lightweight tracking table plus downloadable CSV template.

Use cases: spreadsheets

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What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.

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  • codeload.github.com · found in install command

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  • ~/.claude/skills/personal-coach

What's inside

Skill name
personal-coach
Description
Use this skill to identify strategic career/work insights from conversation patterns, propose one high-leverage weekly behavior change, and provide a lightweight tracking table plus downloadable CSV template.
License
MIT
Instructions
107 lines in SKILL.md · view on GitHub

Files (6)

  • QUICK_REFERENCE.md
  • README.md
  • SKILL.md
  • weekly-coaching-tracker.csv · assets/
  • raw.txt
  • COACHING_FRAMEWORKS.json · references/

SKILL.md (first lines)

# Personal Coach

Help the user surface non-obvious strengths/opportunities from prior conversations, then run a simple 1-week experiment with measurable tracking.

## When to Use

Use this skill when the user asks for:

- Career guidance, strategic reflection, or growth coaching
- Hidden strengths/blind spots based on their working style
- A concrete weekly behavior change with accountability
- A minimal tracking setup to evaluate progress

## Inputs

- Primary input: available conversation context (prior history if available; otherwise the current conversation)
- Optional argument (`$ARGUMENTS`): focus area (e.g., communication, leadership, productivity)

## Procedure

1. **Reflect on conversation evidence**
   - Infer recurring behavior patterns from how the user frames problems, makes decisions, and follows through.
   - If no prior conversation history is available, base observations on the current conversation only and explicitly ask the user to describe recent work patterns.
   - Cite specific observed behaviors (not generic personality labels).

2. **Reveal one under-leveraged strategic insight**
   - State one hidden opportunity the user likely has not fully leveraged yet.
   - Keep it strengths-based and practical.

3. **Propose one simple weekly change**
   - Exactly one change for 7 days.
   - Must be low-friction, <15 minutes/day, and testable.

4. **Define one simple tracking method**
   - Use one daily metric and one weekly outcome metric.
   - Tracking should take <2 minutes/day.

5. **Output in required formats**
   - A concise action table with columns: `What`, `Why`, `How`.
   - A CSV section users can copy into a file.
   - Also reference the downloadable template: [`weekly-coaching-tracker.csv`](./assets/weekly-coaching-tracker.csv).

## Supporting References

This skill includes behavior change frameworks and coaching models:

- **COACHING_FRAMEWORKS.json** — Four evidence-based behavior change models (BJ Fogg Tiny Habits, Gollwitzer Implementation Intentions, James Clear Identity-Based Habits, If-Then Planning), insight identification signal lists, three tracking templates (binary, scaled, outcome), coaching principles (one-change rule, low-friction rule, strengths-first), and five common coaching themes with typical experiments. Located in `references/`.
- **weekly-coaching-tracker.csv** — Downloadable weekly experiment tracker. Located in `assets/`.

The AI uses COACHING_FRAMEWORKS.json to select the right behavior change model and design a testable weekly experiment.

## Decision Rules

- If conversation evidence is weak or sparse:
  - Say what is uncertain in one line.
  - Ask up to 2 targeted questions, then provide a provisional change.
- If user requests too many changes at once:
  - Prioritize one keystone behavior only.
- If user goal is unclear:
  - Default to improving decision quality and visibility of outcomes.
- If the user rejects the proposed insight or change:
  - Ask what feels off, then revise the recommendation while still limiting to one behavior change.

## Quality Criteria (Completion Checks)

A valid response must include all of the following:

- ✅ One clearly stated hidden strategic insight
- ✅ One weekly change (single behavior)
- ✅ One simple tracking plan (daily + weekly metric)
- ✅ A `What | Why | How` table
- ✅ CSV content with columns matching the template
- ✅ Tone: direct, supportive, non-judgmental, specific

## Output Template

### Strategic Insight

- [1–3 sentence observation of under-leveraged strength/opportunity]

### Weekly Experiment

- **Change:** [single action]
- **Duration:** 7 days
- **Time cost:** [minutes/day]

### Action Plan Table

| What                     | Why                | How                     |
| ------------------------ | ------------------ | ----------------------- |
| [single behavior change] | [strategic reason] | [daily execution steps] |

### Tracking

- **Daily metric:** [e.g., `Completed planned 15-minute block? (0/1)`]
- **Weekly outcome metric:** [e.g., `# of meaningful progress outputs`]

### CSV (copy/paste)

Use this CSV or the downloadable template at [`./assets/weekly-coaching-tracker.csv`](./assets/weekly-coaching-tracker.csv).

```csv
date,focus_area,planned_change,completed_0_1,daily_minutes,outcome_signal,notes
YYYY-MM-DD,[focus],[change],0,0,[short signal],[notes]
```

From baralmanish/AI-Agent-Skills, MIT.

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Last commit (this folder)
Jun 30, 2026 (4 months ago)

From GitHub (fetched Oct 24, 2026).

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License
MIT
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

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personal-coach skill. Agent Mart. https://agentmart.dev/skills/baralmanish-personal-coach (last updated 2026-10-24)