DAO Governance Analysis
SkillDev toolsAnalyze DAO governance structures, proposals, voting patterns, and power distribution to assess governance health and participation quality.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the DAO Governance Analysis skill
What this skill tells your AI
The instructions your AI receives, as published by nirholas/three.ws in data/skills/community/dao-governance-analysis/SKILL.md and read by ahel’s review.
When to use this skill
Use when the user asks about:
- Evaluating a DAO's governance structure
- Analyzing a specific governance proposal
- Understanding voting power distribution
- Assessing governance health and participation
- Comparing governance models across protocols
Governance Analysis Framework
1. Governance Structure Overview
Document the governance architecture:
- Governance type: Token-weighted, quadratic, conviction, optimistic, or hybrid
- Governance token: Which token grants voting power? Is it the same as the protocol token?
- Voting mechanism: On-chain (Compound Governor, OpenZeppelin Governor) or off-chain (Snapshot) or hybrid
- Proposal lifecycle: Discussion (forum) -> formal proposal -> voting -> execution
- Quorum requirements: Minimum participation threshold for a vote to be valid
- Approval threshold: What percentage of votes must be "for" to pass?
- Timelock: How long between vote passing and execution?
- Delegation: Can token holders delegate votes? What percentage is delegated?
2. Proposal Analysis
For a specific governance proposal, evaluate:
- Proposal summary: What is being proposed in plain language?
- Author: Who submitted it? Track record of previous proposals?
- Impact scope: Does this change protocol parameters, treasury allocation, or governance itself?
- Technical implementation: Is there executable code attached? Has it been reviewed/audited?
- Community discussion: What is the forum sentiment? Key arguments for and against?
- Financial impact: Does this proposal have treasury implications? How much?
- Risk assessment: What could go wrong if this proposal passes?
- Reversibility: Can this change be undone if it causes problems?
3. Voting Power Distribution
Analyze the concentration of governance power:
| Metric | Assessment |
|---|---|
| Top 10 voters' share | What % of voting power do the top 10 addresses hold? |
| Nakamoto coefficient | How many voters needed to reach 51% of voting power? |
| Delegation patterns | Are votes concentrated in a few delegates? |
| Team/Investor voting | Do team/investor wallets actively vote? Which way? |
| Voter participation rate | What % of token supply actually votes? |
| Unique voter count | How many distinct addresses vote on average? |
Red flags:
- Top 5 addresses controlling > 50% of voting power
- Voter participation below 5% of circulating supply
- Team/investors consistently controlling outcomes
- Single delegate accumulating > 20% of delegated power
4. Governance Health Metrics
Assess overall governance quality:
- Proposal frequency: How many proposals per month? (Too few = inactive, too many = chaotic)
- Passage rate: What percentage of proposals pass? (Very high = rubber stamping, very low = dysfunction)
- Voter turnout trend: Is participation growing, stable, or declining?
- Discussion quality: Are forum discussions substantive or superficial?
- Execution reliability: Are passed proposals actually executed on time?
- Delegate diversity: Is there a diverse set of active delegates with different viewpoints?
- Governance attacks: Any history of flash loan governance attacks or hostile proposals?
5. Governance Model Comparison
When comparing across DAOs:
| Dimension | DAO A | DAO B | DAO C |
|---|---|---|---|
| Governance type | |||
| Quorum | |||
| Approval threshold | |||
| Avg. voter turnout | |||
| Nakamoto coefficient | |||
| Timelock period | |||
| Delegate count | |||
| Proposals/month |
6. Governance Risk Assessment
Identify specific governance risks:
- Plutocracy risk: Wealthy token holders dominating all outcomes
- Apathy risk: Insufficient participation to meet quorum or represent community
- Capture risk: Special interest groups (VCs, large holders) controlling governance for their benefit
- Execution risk: Proposals passing but not being implemented
- Speed risk: Governance too slow to respond to emergencies (exploits, market events)
- Complexity risk: Governance process too complicated for average token holders to participate
7. Output Format
- DAO: Name and governance token
- Governance model: Type and key parameters
- Health score: Healthy / Functional / Concerning / Dysfunctional
- Power distribution: Decentralized / Moderately concentrated / Highly concentrated
- Participation: Strong / Adequate / Low / Critical
- Key strengths: Top 2-3 governance positives
- Key risks: Top 2-3 governance concerns
- Proposal assessment (if analyzing a specific proposal): Support / Oppose / Abstain with reasoning
- Recommendations: Specific improvements to governance health
Signals
- GitHub stars
- 114
- Forks
- 29
- Last commit
- Sep 2026
Advanced
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- skill
- Gateway key
dao-governance-analysis- Source
- github.com/nirholas/three.ws