/crypto-token-analysis

name: crypto-token-analysis
description: Deep-dive framework for analyzing crypto tokens — market data, liquidity health, tokenomics, unlock schedules, and risk assessment. Combines on-chain data, API queries, and multi-source validation to generate actionable investment verdicts.
tags: [crypto, token-analysis, defi, research, trading, airdrop, risk-assessment]
origin: unknown
source_license: see upstream
language: en

Crypto Token Deep Analysis Framework

Systematic approach for analyzing crypto tokens with focus on **profit opportunities** and **risk avoidance**. Used when user requests token analysis, investment research, or airdrop evaluation.

When to Use

• User asks to analyze a specific token (e.g., "$HPL analysis")
• Requests for "deep dive", "fundamental analysis", or "is X token good?"
• **Airdrop opportunity evaluation** (token OR project-level)
• Risk assessment before investment
• Comparing tokens in an ecosystem
• **Analyzing crypto projects/protocols for airdrop potential** (AI agents, DeFi protocols, infrastructure)
• **Evaluating X/Twitter announcements** for alpha/farming opportunities
• **DePIN project analysis** (Decentralized Physical Infrastructure Networks — Helium, IoTeX, Peaq, Render, etc.)
• **Stock market dividend analysis** (IDX/Indonesian stocks) — see `references/idx-dividend-analysis.md` for workflow when APIs fail
• **NFT collection analysis** (OpenSea, Blur, etc.) — floor price, volume, holder distribution, project status

Analysis Types

Type A: Token Analysis (existing token with market data)

Use when: Token already listed on CoinGecko/CMC, has trading volume, circulating supply.

Type B: Project/Protocol Analysis (pre-token or early-stage)

Use when: Analyzing for **airdrop potential**, product is live but no token yet, or token just launched with minimal data.

**Key difference:** Type B focuses on **product reality**, **user onboarding**, **VC backing**, and **airdrop signals** rather than liquidity metrics.

Type C: DePIN Project Analysis (hardware-based infrastructure)

Use when: Analyzing **Decentralized Physical Infrastructure Networks** — projects requiring hardware (IoT devices, sensors, nodes, GPUs, wireless hotspots).

**Key difference:** Type C evaluates **hardware requirements**, **operator economics**, **network effects**, and **adoption barriers** unique to physical infrastructure.

Type D: NFT Collection Analysis (floor price, volume, holders)

Use when: Analyzing **NFT collections** on OpenSea, Blur, or other marketplaces — evaluating floor price trends, trading volume, holder distribution, and project status.

**Key difference:** Type D focuses on **floor price trends**, **volume/holder ratio**, **chart patterns** (pump & dump, death spiral), and **project abandonment signals** rather than tokenomics.

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Core Analysis Framework (Type A: Token Analysis)

1. Market Data (CoinGecko API)

**Primary endpoint:**

curl -s "https://api.coingecko.com/api/v3/coins/{token_id}"

**Key metrics to extract:**

• Market cap & FDV (Fully Diluted Valuation)
• 24h volume
• Circulating vs total supply
• Price performance (24h, 7d, 30d)
• ATH/ATL with dates
• Contract addresses

**Critical calculation:**

vol_mcap_ratio = (volume_24h / market_cap) * 100

# Benchmarks:
# Healthy: >10%
# Acceptable: 3-10%
# Weak: 1-3%
# Dead: <1%

2. Liquidity Health Assessment

**Volume/MCap ratio is THE critical metric for exit risk.**

If ratio < 1%, token is **illiquid** regardless of other fundamentals.

**Slippage estimation (rough):**

• <0.1% ratio: Expect 10-30% slippage on $5K trade
• 0.1-1%: Expect 3-10% slippage on $5K trade
• 1-5%: Expect 1-3% slippage on $5K trade
• >5%: Liquid, <1% slippage

3. Tokenomics & Unlock Risk

**Supply breakdown:**

circulating_pct = (circulating_supply / total_supply) * 100
locked_pct = 100 - circulating_pct

# Risk levels:
# <20% locked: Low risk
# 20-50% locked: Medium risk
# 50-70% locked: High risk
# >70% locked: Extreme risk (avoid)

**Unlock schedule:**

• Check project docs, GitHub, or token vesting contracts
• If not disclosed = RED FLAG
• Calculate potential sell pressure per unlock event

4. Protocol Fundamentals (for DeFi tokens)

**For lending/DEX/yield protocols:**

# Revenue efficiency
revenue_tvl_ratio = (annual_revenue / tvl) * 100

# Benchmarks (lending protocols):
# Excellent: >2%
# Good: 1-2%
# Acceptable: 0.5-1%
# Poor: <0.5%

# Utilization rate
utilization = (total_borrowed / total_supplied) * 100

# Healthy range: 40-80%
# Too low (<30%): Dead capital
# Too high (>90%): Liquidity risk

**TVL quality check:**

• Look for "dead capital" (high TVL, low utilization)
• Check if TVL is real or wash farming
• Compare TVL to actual user count

5. Ecosystem & Narrative

**Context matters:**

• Is the base chain/ecosystem growing or dying?
• Compare token performance to ecosystem native token
• Check if token is listed on major trackers (CMC, CoinGecko)

**Example comparison:**

# If analyzing token on Hyperliquid:
hype_vol_mcap = 1.2%  # Native token
target_vol_mcap = 0.02%  # Your token

relative_health = target_vol_mcap / hype_vol_mcap
# If <0.1 (10x worse), token is dying relative to ecosystem

6. Sentiment & Catalyst Check

**Use delegation for:**

• Recent X/Twitter mentions (sentiment, KOL coverage)
• Upcoming events (CEX listings, partnerships, protocol upgrades)
• Community activity (Discord, Telegram, Reddit)

**Red flags:**

• No social media presence
• Last announcement >1 month ago
• Community size << TVL (fake TVL indicator)

---

Type B: Project/Protocol Airdrop Analysis Framework

**Use when:** Analyzing projects for airdrop potential (no token yet, or token just launched with minimal market data).

1. Context Extraction (from X/Twitter or announcement)

**What to extract:**

• Tweet content (product update? funding? campaign? teaser?)
• Account type (official project? founder? influe