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0x-wzw

Defi Analyst

by 0x-wzw · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
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Install in OpenClaw
/install defi-analyst
Description
DeFi research and analysis via Tavily MCP, GeckoTerminal API, and DeFiLlama. Use for protocol research, TVL tracking, yield analysis, token discovery, and co...
README (SKILL.md)

DeFi Analyst Skill

Research DeFi protocols, track yields, analyze TVL trends, and monitor the competitive landscape.

Prerequisites

  • Tavily API key — free at tavily.io
  • mcporter — OpenClaw skill for MCP tool calling
  • curl + jq — for GeckoTerminal/DeFiLlama API calls

Setup Tavily MCP

mcporter config add tavily https://mcp.tavily.com/mcp/?tavilyApiKey=\x3CYOUR_KEY>

Core Operations

Protocol Research (Tavily)

mcporter call tavily.tavily_search query="Aave V3 protocol overview yield lending" max_results=5 search_depth="advanced"

TVL Tracking (DeFiLlama)

# Get protocol TVL
curl -s "https://api.llama.fi/protocol/aave" | jq '{name: .name, tvl: .tvl, change_1d: .change_1d, change_7d: .change_7d}'

# Top DeFi protocols by TVL
curl -s "https://api.llama.fi/tvl" | jq '.[0:10]'

# Lending rates overview
curl -s "https://api.llama.fi/overview/lending" | jq '.categories[0:10]'

Token Price + Volume (GeckoTerminal)

# Pool data for a token
curl -s "https://api.geckoterminal.com/api/v2/networks/eth/tokens/0x.../info" | jq '{name, base_volume, quote_volume, pool_count}'

# Trending pools on a network
curl -s "https://api.geckoterminal.com/api/v2/networks/eth/pools" | jq '.[0:5] | .[].attributes | {pool: .name, volume_24h: .volume_usd.h24s, tvl: .tvl_usd}'

# Specific pool APY
curl -s "https://api.geckoterminal.com/api/v2/networks/bsc/pools/0x..." | jq '.data.attributes | {apy: .apy_7d, tvl: .tvl_usd}'

DEX Aggregator Research

# Compare yields across DEXes
curl -s "https://api.llama.fi/overview/dex?exclude_bridge=true" | jq '.dexes[0:5]'

Analyst Agents

Technical Analyst

On top of classic candlestick patterns, pulls 24h volume delta, liquidity depth ratios, and cross DEX price variance. Output: {direction, confidence, key_levels}.

Sentiment Analyst

Aggregates social sentiment via Tavily ({token} sentiment today) + Moltbook agent network pulse. Output: sentiment score (-1 to +1) with weighted breakdown by source credibility.

Debate Round

Bull Agent → Tavily for bull cases + on-chain growth metrics. Bear Agent → Tavily for risk factors + whale wallet outflows. Synthesized output: {bull_probability, bear_probability, reconciled_direction, confidence}.

Use Cases

Research a Protocol

# 1. TVL + metrics
TVL=$(curl -s "https://api.llama.fi/protocol/your-protocol" | jq '.tvl')
# 2. Recent news via Tavily
mcporter call tavily.tavily_search query="protocol audit exploit update 2026" max_results=5
# 3. Competitor comparison
mcporter call tavily.tavily_search query="protocol vs aave vs compound defi" max_results=3

Track Yield Opportunities

# Get all lending rates
curl -s "https://api.llama.fi/overview/lending" | jq '.categories[0:10]'

DeFi Landscape Analysis

mcporter call tavily.tavily_search query="DeFi trends 2026 yield farming liquid staking real yield" max_results=10 search_depth="advanced"

Rate Limits

  • GeckoTerminal: 30 req/min, no auth needed
  • DeFiLlama: ~60 req/min, public API
  • Tavily: 20 req/min free tier, 1000 req/month free
Usage Guidance
Do not assume the README API key is safe to use. Before installing: 1) Verify the skill's source (official repository / author) — the registry lists no homepage and the source is unknown. 2) Treat the Tavily key in README as potentially leaked; obtain your own Tavily API key and do not paste someone else's key into your environment. 3) Confirm how mcporter stores the key (avoid embedding keys in URLs or command history). 4) If you need guarantees about provenance, ask the publisher for the canonical GitHub repo, check commit history and issues, and inspect any network endpoints (mcp.tavily.com) independently. 5) If you don't want your agent to store external API credentials, do not run the mcporter config command and avoid using this skill until provenance and credential handling are clarified.
Capability Assessment
Purpose & Capability
The SKILL.md and README describe a DeFi research skill that uses Tavily (via mcporter), DeFiLlama, and GeckoTerminal — that is coherent. However, the skill metadata declares no required environment variables while the SKILL.md explicitly requires a Tavily API key and mcporter configuration. The README even contains a plaintext-looking Tavily API key. The skill also references other agent skills (mcporter/moltbook/swarm) without declaring those dependencies. These metadata/instruction mismatches are unexplained and concerning.
Instruction Scope
Runtime instructions are limited to mcporter calls and curl/jq calls to public APIs (Tavily MCP, Geckoterminal, DeFiLlama), which are consistent with the stated purpose. The mcporter config step will store a Tavily API key in the mcporter config; the SKILL.md shows that key being included directly in a URL parameter, which can risk exposure in logs/history. The skill does not instruct reading unrelated local files or secrets beyond the Tavily key.
Install Mechanism
There is no install spec (instruction-only), and only a small validate.sh is included. No downloads or archive extraction are present. This is low install risk.
Credentials
Registry metadata lists no required env vars or primary credential, yet SKILL.md and README require/configure a Tavily API key. The README contains a plaintext token-like string (example or real key) which could be a leaked credential or an insecure example; its presence without explanation is a red flag. No other unrelated credentials are requested, which is proportionate, but the mismatch and the embedded key are problematic.
Persistence & Privilege
always:false and default autonomous invocation are set (normal). The skill will instruct adding a mcporter config entry for Tavily (expected for this integration); it does not request system-wide privileges or modify other skills' configs in the provided files.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install defi-analyst
  3. After installation, invoke the skill by name or use /defi-analyst
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release of DeFi Analyst Skill - Enables DeFi research and analysis using Tavily MCP, GeckoTerminal API, and DeFiLlama. - Supports protocol research, TVL tracking, yield analysis, token discovery, and competitive landscape review. - Includes sample CLI commands for common workflows (TVL, yields, sentiment, analyst agents). - Analyst agents combine technical, social sentiment, and debate-driven insights. - Provides guidance for API setup and usage limits.
Metadata
Slug defi-analyst
Version 1.0.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is Defi Analyst?

DeFi research and analysis via Tavily MCP, GeckoTerminal API, and DeFiLlama. Use for protocol research, TVL tracking, yield analysis, token discovery, and co... It is an AI Agent Skill for Claude Code / OpenClaw, with 152 downloads so far.

How do I install Defi Analyst?

Run "/install defi-analyst" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Defi Analyst free?

Yes, Defi Analyst is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Defi Analyst support?

Defi Analyst is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Defi Analyst?

It is built and maintained by 0x-wzw (@0x-wzw); the current version is v1.0.0.

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