← 返回 Skills 市场

Uniswap Research Token

Name: Uniswap Research Token
Author: wpank

作者 wpank · GitHub ↗ · v0.1.0

cross-platform ✓ 安全检测通过

838

总下载

当前安装

版本数

在 OpenClaw 中安装

/install research-token

功能描述

Research a token's Uniswap liquidity, volume profile, pool distribution, and risk factors. Use when the user asks about a token's tradability, liquidity depth, or wants due diligence.

使用说明 (SKILL.md)

Research Token

Overview

Performs comprehensive due diligence on a token from a Uniswap protocol perspective. Delegates to the token-analyst agent to analyze liquidity across all pools, volume trends, and risk factors.

When to Use

Activate when the user asks:

"Research UNI token"
"Is there enough liquidity for X?"
"Token analysis for PEPE"
"Due diligence on this token"
"What pools trade X?"
"How liquid is X on Uniswap?"
"Is X safe to trade?"

Parameters

Parameter	Required	Default	Description
token	Yes	—	Token name, symbol, or contract address
chain	No	All chains	Specific chain or "all" for cross-chain view
focus	No	Full analysis	"liquidity", "volume", or "risk"

Workflow

Extract parameters from the user's request: identify the token and any chain/focus filters.
Delegate to token-analyst: Invoke Task(subagent_type:token-analyst) with the token identifier. The agent resolves the token, discovers all pools, analyzes liquidity and volume, and produces a risk assessment.
Present results: Format the token-analyst's report into a user-friendly summary.

Output Format

Token Research: UNI (Uniswap)

  Address:  0x1f9840a85d5aF5bf1D1762F925BDADdC4201F984
  Chains:   Ethereum, Arbitrum, Optimism, Polygon, Base
  Pools:    24 active pools across all chains

  Liquidity:
    Total TVL:   $85M across all pools
    Best pool:   WETH/UNI 0.3% (49.4% of liquidity)
    Depth (1%):  $2.5M trade size
    Fragmentation: Moderate

  Volume:
    24h: $15M | 7d: $95M | 30d: $380M
    Trend: Stable
    Turnover: 0.18x daily

  Risk Factors:
    - Moderate pool concentration (49.4% in one pool) — LOW severity

  Trading: Suitable for trades up to $2.5M with \x3C 1% price impact

Important Notes

Delegates entirely to token-analyst — no direct MCP tool calls.
The analysis is from a Uniswap protocol perspective only — not a general investment analysis.
Risk factors are based on observable on-chain metrics, not price predictions.

Error Handling

Error	User-Facing Message	Suggested Action
Token not found	"Could not find token X on Uniswap."	Provide contract address
No pools	"No Uniswap pools found for this token."	Token may not be listed
Insufficient data	"Limited trading data available for this token."	Token may be too new

安全使用建议

This skill itself is small and coherent: it only forwards token identifiers to a token-analyst subagent and formats the returned report. Before installing, review or ask for the token-analyst skill/agent implementation because that component will perform on-chain queries and external network calls and may require RPC/API credentials. If you plan to use this for real trading due diligence, prefer giving explicit contract addresses (not just names) to avoid misidentification, avoid providing high-privilege environment secrets to the agent, and consider running tests on well-known tokens to validate the reports. If you are uncomfortable with autonomous subagent network access, disable autonomous invocation or restrict the agent's environment until you can audit the token-analyst code.

功能分析

Type: OpenClaw Skill Name: research-token Version: 0.1.0 The skill is designed for token research and explicitly restricts the AI agent to use only the `Task(subagent_type:token-analyst)` tool, as defined in `SKILL.md`. This strong security control prevents the agent from executing arbitrary commands, accessing local files, or making unauthorized network calls, even in the event of a prompt injection attempt. There is no evidence of data exfiltration, malicious execution, persistence mechanisms, or obfuscation within any of the provided files. All instructions and code are aligned with the stated purpose.

能力评估

✓ Purpose & Capability

Name, description, parameters, and workflow align: the skill's sole job is to extract token parameters and delegate Uniswap-focused analysis to a token-analyst subagent. It does not declare unrelated requirements (no cloud creds, no binaries).

ℹ Instruction Scope

SKILL.md is narrowly scoped and delegates all analysis to Task(subagent_type:token-analyst). That keeps this skill simple, but the actual runtime behavior depends on the token-analyst subagent (network calls, RPC endpoints, or credential usage) which is not included for review.

✓ Install Mechanism

Instruction-only skill with no install steps, no downloads, and no code files — lowest-risk install footprint.

✓ Credentials

The skill declares no environment variables, secrets, or config paths. This is proportionate to its stated purpose. Note: the delegated token-analyst subagent may require RPC keys or API tokens at runtime (not visible here).

✓ Persistence & Privilege

always:false and no privileges or config changes are requested. The skill does not request persistent system presence or modification of other skills' configs.

如何使用

确保已安装 OpenClaw（本地或 Docker 部署）
在对话框中输入安装命令：/install research-token
安装完成后，直接呼叫该 Skill 的名称或使用 /research-token 触发
根据 Skill 的参数说明提供必要输入，即可获得结构化输出

版本历史

v0.1.0

Initial release — provides due diligence for tokens on Uniswap protocol. - Analyzes token liquidity, volume trends, pool distribution, and risk factors via the token-analyst agent. - Supports user queries about tradability, liquidity depth, and pool details for any token. - Accepts parameters for token symbol/address, optional chain, and focus area (liquidity, volume, or risk). - Formats findings in a clear, user-friendly summary highlighting TVL, trading depth, volume, and risks. - Handles missing tokens, pools, or data with concise error messages.

元数据

Slug research-token

版本 0.1.0

许可证 —

累计安装 1

当前安装数 1

历史版本数 1

常见问题