WalletTriage MCP
OfficialServer Quality Checklist
Latest release: v0.1.4
- Disambiguation5/5
The two tools have entirely distinct purposes: one performs a risk check on an address, the other retrieves pricing/status. There is no overlap or ambiguity.
Naming Consistency5/5Both tools follow a clear verb_noun pattern (check_address_risk, get_pricing), using consistent snake_case naming.
Tool Count3/5With only 2 tools, the server is very light. For a 'triage' server, one might expect more operations, but the focused paid-query model makes the count borderline acceptable.
Completeness2/5The server only offers a single core risk-check tool plus a pricing tool. Missing features like batch checks, historical data, or transaction simulation leave notable gaps for a 'triage' service.
Average 4/5 across 2 of 2 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 3 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
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How is the quality score calculated?
The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).
Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.
Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).
Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.
Tool Scores
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It mentions that the tool is free and specifies the payment method (x402, USDC on Base), but does not disclose any potential side effects, rate limits, or authentication requirements. The behavioral context is minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence with no wasted words. It is front-loaded with 'Free:' and immediately states the purpose. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has zero parameters, no output schema, and no annotations, the description provides sufficient context: it returns service status and pricing, and the payment method. The sibling tool is mentioned in context, aiding selection. Minor gaps include lack of detail on what 'status' encompasses, but overall complete for a simple tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has no parameters, so schema_description_coverage is 100%. The baseline is 3, but the description adds value by explaining what the tool returns (status and price) beyond the empty schema, effectively compensating for the lack of parameter information.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'returns' and clearly identifies the resources: WalletTriage service status and current price per risk query. It implicitly distinguishes from the sibling tool 'check_address_risk' by focusing on pricing and status rather than risk assessment.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for obtaining pricing information but does not explicitly state when to use this tool versus the sibling 'check_address_risk'. No alternative names or exclusion criteria are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It discloses real-time nature, cross-referencing with exploit feed, return fields (risk_score, risk_level, findings), and payment method (x402 USDC). Missing details on error handling or side effects, but overall strong behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Description is two sentences, front-loaded with purpose and key details. It is efficient but slightly verbose with payment info. Overall well-structured for an agent.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, description adequately covers return types (risk_score, risk_level, findings) and payment context. Missing error behavior or address validation, but sufficient for typical use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema has 100% description coverage for both parameters. The description adds minimal value beyond schema: it specifies default chain ('eth') and lists supported chains. Baseline 3 is appropriate as schema already covers meaning.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: performing a real-time risk check on an EVM address before acting. It specifies the resource (EVM wallet address) and context (cross-referencing approvals with exploit feed). It distinguishes from sibling tool 'get_pricing' which is unrelated.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description indicates when to use ('BEFORE acting on it') and mentions payment model. However, it does not explicitly state when not to use or provide alternatives to sibling tools. The guidance is clear but lacks exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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