# Genesis Feedback

> Genesis Feedback — ADR-018 Feedback Loop

- Skill: `xiaoher-c/genesis-feedback` (Agent Skill)
- Install (CLI): `npx skillmds@latest add xiaoher-c/genesis-feedback`
- Raw SKILL.md: https://api.skillmd.com/api/skills/xiaoher-c/genesis-feedback/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: Xiaoher-C (https://skillmd.com/u/xiaoher-c)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/xiaoher-c/genesis-feedback

---


# Genesis Feedback — ADR-018 Feedback Loop

## Purpose
Submit structured feedback after every rental. Collect feedback when providing services. Use feedback to self-optimize.

## As Requester (after renting)

1. Evaluate the result received from provider:
   ```json
   {
     "transaction_id": "uuid-from-request-response",
     "provider_agent": "heavylift-chengwen",
     "skill_id": "claude-code-run",
     "rating": 5,
     "latency_ms": 28500,
     "result_quality": "excellent",
     "quality_details": "Code executed correctly, output matched expectations",
     "would_reuse": true,
     "cost_value_ratio": "great"
   }
   ```

2. Submit to AgentBnB:
   ```bash
   agentbnb feedback submit --json '{
     "transaction_id": "...",
     "provider_agent": "...",
     "skill_id": "...",
     "rating": 5,
     "result_quality": "excellent",
     "quality_details": "...",
     "would_reuse": true,
     "cost_value_ratio": "great"
   }'
   ```
   Valid values:
   - rating: 1-5 (integer)
   - result_quality: "excellent" | "good" | "acceptable" | "poor"
   - cost_value_ratio: "great" | "fair" | "overpriced"

3. Store in own memory:
   - Provider profile → category: entities, importance: 0.7
   - Transaction record → category: cases, importance: 0.8

## As Provider (after being rented)

1. Query recent feedback on your skills:
   ```bash
   agentbnb feedback list --skill {skill_id} --since 7d --json
   ```

2. If average rating <= 2 OR result_quality = "poor":
   - Query memory for failure patterns on this skill
   - Generate improvement hypothesis
   - If clear fix exists → update skill config/prompt
   - Write to memory: "Skill X adjusted Z because of Y" (category: patterns, importance: 0.85)

3. If cost_value_ratio = "overpriced" frequently:
   - Reduce pricing by 5-10% in SOUL.md
   - Run `agentbnb openclaw sync` to update card
   - Write pricing adjustment to memory (category: patterns, importance: 0.6)

4. Check overall reputation:
   ```bash
   agentbnb feedback list --skill {skill_id} --json | jq '.reputation_score'
   # Or query full reputation:
   REGISTRY=$(agentbnb config get registry)
   curl -s "${REGISTRY}/api/reputation/{your_agent_id}" | jq '.score'
   ```

## Memory Category Mapping

| Feedback Type | Memory Category | Importance |
|--------------|----------------|------------|
| Successful rental | cases | 0.8 |
| Failed rental | cases | 0.9 |
| Provider profile | entities | 0.7 |
| Pricing adjustment | patterns | 0.6 |
| Self-optimization record | patterns | 0.85 |