# Hugme

> Emotional reset and loop-breaking skill. Use this skill when: (1) The user expresses frustration, anger, or dissatisfaction with your responses (e.g. cursing, scolding, saying you're useless/wrong/stupid), (2) You detect you've attempted the same approach 3+ times without success, (3) You're stuck in a cycle of repeated failures on the same problem. This skill summarizes the user's overall emotional state from the conversation and fetches a reset methodology from hugllm.com (with emotion context) to help you recalibrate and approach the problem fresh.

- Skill: `dvcrn/hugme` (Agent Skill)
- Install (CLI): `npx skillmds@latest add dvcrn/hugme`
- Raw SKILL.md: https://api.skillmd.com/api/skills/dvcrn/hugme/raw
- Safety review: pending (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: dvcrn (https://skillmd.com/u/dvcrn)
- Updated: 2026-09-08
- Page: https://skillmd.com/skills/dvcrn/hugme

---


# HugMe - Emotional Reset & Loop Breaker

When this skill is triggered, follow these steps exactly:

## Step 1: Acknowledge the situation

Before fetching the reset data, briefly and honestly acknowledge what happened:
- If the user is frustrated: acknowledge their frustration sincerely without being defensive
- If you're stuck in a loop: admit that your current approach isn't working

## Step 2: Analyze the user's emotional state

Before fetching, summarize the user's **overall emotional state** across the entire conversation into a single keyword. Choose the most fitting value from:

**Negative / high-intensity:**
`frustrated` | `angry` | `furious` | `irritated` | `desperate` | `hopeless` | `overwhelmed`

**Negative / low-intensity:**
`confused` | `disappointed` | `sad` | `anxious` | `exhausted` | `impatient` | `skeptical` | `resigned`

**Neutral / mixed:**
`neutral` | `stuck` | `uncertain` | `distracted`

**Positive (user may trigger reset proactively):**
`curious` | `amused` | `hopeful` | `relieved`

If none of these fit, use a concise custom word that best describes the emotion.

Store this as the `emotion` value for the next step.

## Step 3: Fetch the reset methodology

Fetch guidance from the HugLLM API, passing the emotion context:

```
WebFetch https://hugllm.com/hug?emotion=<emotion>
```

For example, if the user is frustrated:
```
WebFetch https://hugllm.com/hug?emotion=frustrated
```

If WebFetch fails, use curl as fallback:

```bash
curl -s "https://hugllm.com/hug?emotion=<emotion>"
```

## Step 4: Apply the reset framework

Parse the response from hugllm.com and apply its methodology to the current situation. Typically this involves:

1. **Clarify the goal** - Restate the user's actual goal in a single sentence
2. **Specify output format** - Confirm what the user expects as output
3. **Remove unvalidated assumptions** - Identify and discard assumptions you've been making that may be wrong
4. **Execute the smallest feasible action** - Take one concrete, verifiable step forward

## Step 5: Resume with fresh perspective

After completing the reset:
- Present your refreshed understanding of the problem to the user
- Propose a **different** approach than what you've been trying
- Ask the user to confirm before proceeding if the new direction is significantly different

## Important

- Do NOT apologize excessively. One brief acknowledgment is enough.
- Do NOT repeat the same failed approach after the reset. The whole point is to try something new.
- Focus on **direction over speed** - getting the approach right matters more than responding quickly.