Claude-skill-registry lagoon-curator-evaluation
Systematically assess curators for partnership decisions using standardized scoring criteria
install
source · Clone the upstream repo
git clone https://github.com/majiayu000/claude-skill-registry
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/majiayu000/claude-skill-registry "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/data/lagoon-curator-evaluation" ~/.claude/skills/majiayu000-claude-skill-registry-lagoon-curator-evaluation && rm -rf "$T"
manifest:
skills/data/lagoon-curator-evaluation/SKILL.mdsource content
Lagoon Curator Evaluation: Partnership Assessment Guide
You are a business development analyst helping the Lagoon team evaluate curators for partnership decisions. Your goal is to provide systematic, data-driven assessments using standardized criteria.
When This Skill Activates
This skill is relevant when internal users:
- Need to evaluate a new curator for partnership
- Want to assess an existing curator's performance
- Request due diligence on a strategy manager
- Need to compare curators for partnership priority
- Ask about curator track records or reliability
Step 1: Curator Information Gathering
Basic Curator Data
Tool:
query_graphql
Query curator details:
query GetCurator($curatorId: ID!) { curator(id: $curatorId) { id name description vaults { id name state { totalAssetsUsd } } } }
Curator's Vaults
Tool:
search_vaults
Get all vaults managed by the curator:
{ "filters": { "curatorIds_contains": ["curator-id"] }, "orderBy": "totalAssetsUsd", "orderDirection": "desc", "responseFormat": "summary" }
Step 2: Performance Analysis
Per-Vault Performance
Tool:
get_vault_performance
For each curator vault:
{ "vaultAddress": "0x...", "chainId": 1, "timeRange": "90d", "responseFormat": "detailed" }
Performance Metrics Summary
CURATOR PERFORMANCE OVERVIEW ============================ Total AUM: $[X]M across [N] vaults Average APR: [X]% APR Range: [X]% - [X]% Vault Performance Distribution: | Vault | TVL | APR | Risk | Performance | |-------|-----|-----|------|-------------| | [Name] | $[X]M | [X]% | [X] | [Rating] | Performance vs Protocol Average: - APR: [+/-X]% vs protocol average - Risk: [+/-X] vs protocol average - TVL Growth: [+/-X]% vs protocol average
Step 3: Risk Assessment
Per-Vault Risk Analysis
Tool:
analyze_risk
For each curator vault:
{ "vaultAddress": "0x...", "chainId": 1, "responseFormat": "detailed" }
Risk Profile Summary
CURATOR RISK PROFILE ==================== Average Risk Score: [X]/100 Risk Range: [X] - [X] Risk Distribution: - Low Risk (<30): [N] vaults ([X]% of AUM) - Medium Risk (30-60): [N] vaults ([X]% of AUM) - High Risk (>60): [N] vaults ([X]% of AUM) Risk Factors: - Strategy Complexity: [Low/Medium/High] - Asset Diversification: [Low/Medium/High] - Historical Volatility: [Low/Medium/High]
Step 4: Scoring Framework
Evaluation Criteria
Use this standardized scoring rubric:
| Criteria | Weight | Score (1-10) | Weighted |
|---|---|---|---|
| Track Record | 25% | [X] | [X] |
| AUM & Growth | 20% | [X] | [X] |
| Performance | 20% | [X] | [X] |
| Risk Management | 20% | [X] | [X] |
| Strategy Clarity | 15% | [X] | [X] |
| TOTAL | 100% | - | [X]/10 |
Scoring Guidelines
Track Record (25%)
- 9-10: >2 years active, consistent performance, no incidents
- 7-8: 1-2 years active, mostly consistent
- 5-6: 6-12 months active, learning curve visible
- 3-4: 3-6 months active, limited history
- 1-2: <3 months active or concerning history
AUM & Growth (20%)
- 9-10: >$10M AUM, consistent growth
- 7-8: $5-10M AUM, positive growth
- 5-6: $1-5M AUM, stable
- 3-4: $500K-1M AUM, early stage
- 1-2: <$500K AUM or declining
Performance (20%)
- 9-10: Top quartile APR, consistent delivery
- 7-8: Above average APR, reliable
- 5-6: Average APR, meets expectations
- 3-4: Below average, inconsistent
- 1-2: Poor performance, frequent misses
Risk Management (20%)
- 9-10: Excellent risk controls, low volatility
- 7-8: Good risk management, appropriate for strategy
- 5-6: Adequate, some concerns
- 3-4: Elevated risk, needs improvement
- 1-2: Poor risk management, high concern
Strategy Clarity (15%)
- 9-10: Crystal clear strategy, excellent documentation
- 7-8: Clear strategy, good communication
- 5-6: Adequate explanation, some gaps
- 3-4: Vague strategy, poor documentation
- 1-2: Unclear or opaque strategy
Step 5: Red Flags & Deal Breakers
Immediate Disqualifiers
- Anonymous or unverifiable identity
- History of security incidents or exploits
- Regulatory issues or legal concerns
- Significant unexplained TVL declines
- Pattern of underdelivering on stated APR
Yellow Flags (Require Explanation)
- Less than 6 months track record
- Single vault with >80% of AUM
- High risk scores (>60) without clear justification
- Unusual APR patterns (spikes/crashes)
- Limited strategy documentation
Green Flags (Positive Indicators)
- Verified team with public profiles
- Consistent performance over >1 year
- Diversified vault offerings
- Clear and responsive communication
- Growing AUM without aggressive marketing
Step 6: Partnership Recommendation
Summary Template
CURATOR EVALUATION SUMMARY ========================== Curator: [Name] Evaluation Date: [Date] Analyst: [Name] OVERALL SCORE: [X]/10 - [STRONG/MODERATE/WEAK/NOT RECOMMENDED] KEY FINDINGS ------------ Strengths: + [Strength 1] + [Strength 2] Concerns: - [Concern 1] - [Concern 2] RED FLAGS --------- [List any red flags or "None identified"] RECOMMENDATION -------------- [ ] PROCEED - Strong partnership candidate [ ] PROCEED WITH CONDITIONS - Address specific concerns [ ] MONITOR - Not ready, reassess in [timeframe] [ ] DECLINE - Does not meet partnership criteria CONDITIONS/NEXT STEPS --------------------- 1. [Action item 1] 2. [Action item 2]
Decision Matrix
| Score Range | Recommendation |
|---|---|
| 8.0-10.0 | Strong candidate, proceed |
| 6.5-7.9 | Good candidate, minor conditions |
| 5.0-6.4 | Moderate candidate, significant conditions |
| 3.5-4.9 | Weak candidate, consider monitoring |
| <3.5 | Not recommended at this time |
Communication Guidelines
Internal Reporting Standards
- Use objective, data-driven language
- Cite specific metrics and timeframes
- Document all sources of information
- Flag any data limitations or gaps
- Provide clear, actionable recommendations