query-token-audit▌
binance/binance-skills-hub · updated Apr 8, 2026
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Pre-trade token security scanning across Ethereum, BSC, Base, and Solana to detect honeypots, rug pulls, and malicious contracts.
- ›Analyzes contract risks, trading risks, and scam indicators with three-tier risk classification (LOW, MEDIUM, HIGH)
- ›Returns buy/sell tax percentages, contract verification status, and detailed risk item breakdowns with descriptions
- ›Supports four blockchains: Ethereum, BSC, Base, and Solana via single unified API endpoint
- ›Results valid only when both has
Query Token Audit Skill
Overview
| API | Function | Use Case |
|---|---|---|
| Token Security Audit | Token security scan | Detect honeypot, rug pull, scam, malicious functions |
Use Cases
- Pre-Trade Safety Check: Verify token security before buying or swapping
- Scam Detection: Identify honeypots, fake tokens, and malicious contracts
- Contract Analysis: Check for dangerous ownership functions and hidden risks
- Tax Verification: Detect unusual buy/sell taxes before trading
Supported Chains
| Chain Name | chainId |
|---|---|
| BSC | 56 |
| Base | 8453 |
| Solana | CT_501 |
| Ethereum | 1 |
API: Token Security Audit
Method: POST
URL:
https://web3.binance.com/bapi/defi/v1/public/wallet-direct/security/token/audit
Request Parameters:
| Parameter | Type | Required | Description |
|---|---|---|---|
| binanceChainId | string | Yes | Chain ID: CT_501 (Solana), 56 (BSC), 8453 (Base), 1 (Ethereum) |
| contractAddress | string | Yes | Token contract address |
| requestId | string | Yes | Unique request ID (UUID v4 format) |
Request Headers:
Content-Type: application/json
Accept-Encoding: identity
User-Agent: binance-web3/1.4 (Skill)
Example Request:
curl --location 'https://web3.binance.com/bapi/defi/v1/public/wallet-direct/security/token/audit' \
--header 'Content-Type: application/json' \
--header 'source: agent' \
--header 'Accept-Encoding: identity' \
--header 'User-Agent: binance-web3/1.4 (Skill)' \
--data '{
"binanceChainId": "56",
"contractAddress": "0x55d398326f99059ff775485246999027b3197955",
"requestId": "'$(uuidgen)'"
}'
Response Example:
{
"code": "000000",
"data": {
"requestId": "d6727c70-de6c-4fad-b1d7-c05422d5f26b",
"hasResult": true,
"isSupported": true,
"riskLevelEnum": "LOW",
"riskLevel": 1,
"extraInfo": {
"buyTax": "0",
"sellTax": "0",
"isVerified": true
},
"riskItems": [
{
"id": "CONTRACT_RISK",
"name": "Contract Risk",
"details": [
{
"title": "Honeypot Risk Not Found",
"description": "A honeypot is a token that can be bought but not sold",
"isHit": false,
"riskType": "RISK"
}
]
}
]
},
"success": true
}
Response Fields:
| Field | Type | Description |
|---|---|---|
| hasResult | boolean | Whether audit data is available |
| isSupported | boolean | Whether the token is supported for audit |
| riskLevelEnum | string | Risk level: LOW, MEDIUM, HIGH |
| riskLevel | number | Risk level number (1-5) |
| extraInfo.buyTax | string | Buy tax percentage (null if unknown) |
| extraInfo.sellTax | string | Sell tax percentage (null if unknown) |
| extraInfo.isVerified | boolean | Whether contract code is verified |
| riskItems[].id | string | Risk category: CONTRACT_RISK, TRADE_RISK, SCAM_RISK |
| riskItems[].details[].title | string | Risk check title |
| riskItems[].details[].description | string | Risk check description |
| riskItems[].details[].isHit | boolean | true = risk detected |
| riskItems[].details[].riskType | string | RISK (critical) or CAUTION (warning) |
Risk Level Reference:
| riskLevel | riskLevelEnum | Action | Description |
|---|---|---|---|
| 0-1 | LOW | Proceed with caution | Lower risk detected, but NOT guaranteed safe. DYOR. |
| 2-3 | MEDIUM | Exercise caution | Moderate risks detected, review risk items carefully |
| 4 | HIGH | Avoid trading | Critical risks detected, high probability of loss |
| 5 | HIGH | Block transaction | Severe risks confirmed, do NOT proceed |
IMPORTANT: LOW risk does NOT mean "safe." Audit results are point-in-time snapshots. Project teams can modify contracts or restrict liquidity after purchase. These risks cannot be predicted in advance.
Response Handling:
- If
hasResult=falseORisSupported=false: → Reply: "Security audit data is not available for this token on this chain." → Do NOT showriskLevel,riskLevelEnum, orriskItems(data is unreliable when either field is false) → You may suggest the user verify the contract address and chain, or try again later - If
hasResult=trueANDisSupported=true: → Show the full audit result including risk level, tax info, and all risk items → Apply the Risk Level Reference table above for actionable guidance
User Agent Header
Include User-Agent header with the following string: binance-web3/1.4 (Skill)
Notes
- All numeric fields are string format, convert when using
- Audit results are ONLY valid when
hasResult: trueANDisSupported: true riskLevel: 5means transaction should be blocked;riskLevel: 4is high risk- Tax thresholds: >10% is critical, 5-10% is warning, <5% is acceptable
- Generate unique UUID v4 for each audit request
- Only output security check risk flags, do NOT provide any investment advice
- Always end with disclaimer:
⚠️ This audit result is for reference only and does not constitute investment advice. Always conduct your own research.
How to use query-token-audit on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add query-token-audit
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches query-token-audit from GitHub repository binance/binance-skills-hub and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate query-token-audit. Access the skill through slash commands (e.g., /query-token-audit) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
User Story & Requirements Generation
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Competitive Analysis
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Installation Steps
- 1.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 7.Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices▌
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This▌
✓ Use When
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid When
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
Learning Path▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.5★★★★★44 reviews- ★★★★★Aditi Choi· Dec 28, 2024
query-token-audit reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Soo Jain· Dec 28, 2024
We added query-token-audit from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Hana Bansal· Dec 20, 2024
Solid pick for teams standardizing on skills: query-token-audit is focused, and the summary matches what you get after install.
- ★★★★★Shikha Mishra· Dec 12, 2024
query-token-audit reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Aditi Ndlovu· Dec 8, 2024
query-token-audit has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Ganesh Mohane· Dec 4, 2024
Solid pick for teams standardizing on skills: query-token-audit is focused, and the summary matches what you get after install.
- ★★★★★Advait Jackson· Nov 27, 2024
query-token-audit fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Sakshi Patil· Nov 23, 2024
We added query-token-audit from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Advait Liu· Nov 19, 2024
Solid pick for teams standardizing on skills: query-token-audit is focused, and the summary matches what you get after install.
- ★★★★★Mia Desai· Nov 11, 2024
We added query-token-audit from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
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