Assess rug pull risk for a specific DEX trading pair. Scores 6 risk factors (0-100): liquidity depth, pair age, volume/liquidity ratio, price action, buy/sell imbalance, and metadata.
Example: check if a new Solana pair is a potential rug pull.
| Name | Required | Description | Default |
|---|---|---|---|
| chain | Yes | Blockchain (solana, ethereum, base, bsc). | |
| pair_address | Yes | DEX pair contract address. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, establishing safety. The description adds behavioral detail by specifying the six risk factors and the 0-100 scoring scale, which informs the agent what the tool will compute. No contradictions with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences: the first states the purpose and output details, the second gives a practical example. No wasted words, and the most important information is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With strong annotations, complete schema, and a description that names the six risk factors and scoring range, the tool is adequately specified for selection and invocation. The lack of an output schema is partially compensated by the description's reference to 0-100 scores, though exact return structure is not specified.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, with both 'chain' and 'pair_address' already described. The description's example ('new Solana pair') reinforces the parameters but does not add substantive new meaning beyond the schema, so the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Assess rug pull risk for a specific DEX trading pair.' It identifies the resource (DEX pair) and the specific action (rug risk assessment), and the list of six risk factors differentiates it from siblings like validate_trade or scan_token.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context: it is used to evaluate a DEX pair's rug pull risk, with an explicit example ('check if a new Solana pair is a potential rug pull'). It does not name alternatives or state when not to use it, but the use case is sufficiently clear from the tool's focus.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Several tools overlap in purpose: validate_trade and validate_trade_plus both validate trades, while scan_token and rug_check are bundled into validate_trade's checks. This creates ambiguity about which tool to use for a given task, especially for agents trying to distinguish the premium versus standard validation flow.
All tool names share the 'cryptoguard_' prefix and snake_case, but the structure varies: some are verbs (search, scan_token, validate_trade), while others are nouns or adjective-noun combinations (health, rug_check, counterfactual_trade). The inconsistency in verb usage makes the set feel less predictable, though the prefix provides a unifying element.
Seven tools is within the typical well-scoped range for a crypto risk assessment server. The count is reasonable, but the overlap between validate_trade and validate_trade_plus suggests one could arguably be consolidated, making the set slightly redundant.
The server covers the core domain well: health checking, token search, rug pull assessment, anomaly scanning, trade validation, and counterfactual analysis. Minor gaps exist (e.g., no batch processing or explicit market data endpoints) but the main workflows for trade validation and risk assessment are represented.