Collect alerts raised by your watch_token watches: what changed, how severe (critical | warning | info), and the on-chain numbers behind it — plus the status of every watch you own. Requires the subscriber_key from watch_token. Each alert is delivered once. FREE — poll it as often as every couple of minutes.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| subscriber_key | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It explains that alerts are delivered once and describes the data returned. It implicitly indicates a read-only operation with no side effects and mentions free usage.
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?
The description is concise at two sentences, front-loading the core purpose. It could be slightly more structured (e.g., separating prerequisites from behavior) but remains efficient.
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?
Given no output schema, the description provides a good overview of returned data (changes, severity, numbers, watch status). It is complete enough for a polling tool, though missing details on pagination or error handling.
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 0%, meaning the description adds minimal value for parameters. It mentions subscriber_key in the description but does not explain its role or the limit parameter. This is insufficient for an agent to correctly invoke the tool.
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 collects alerts from watch_token watches, detailing what is included (changes, severity, on-chain numbers, status of watches). It distinguishes itself from sibling tools like watch_token which creates watches, and other check tools.
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 specifies the prerequisite (subscriber_key from watch_token) and explicitly says it is FREE to poll frequently ('every couple of minutes'). However, it does not provide guidance on when to use this tool versus alternatives like check_transaction.
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.
Each tool targets a distinct resource and action: address checks, token checks, price analysis, transaction simulation, path finding, wallet history, pool discovery, attestation, and monitoring all have clear boundaries. While some tools share domain (e.g., check_xrpl_token vs resolve_asset), their purposes are clearly differentiated in descriptions.
Nearly all tools follow a verb_noun pattern (check_*, get_*, verify_*, analyze_*, explore_*, find_*, quote_*, watch_*, submit_*). The only slight deviation is 'token_holders', a noun phrase, but it is still concise and follows the same lowercase snake_case style, so it does not create confusion.
20 tools is on the heavier side of the ideal range, but the server's scope—cross-chain security, token analysis, monitoring, attestation, and market data—justifies this breadth. Each tool covers a distinct sub-domain, so the count is reasonable though slightly above the typical 3-15 sweet spot.
The tool surface comprehensively covers the domain: token discovery, safety, identity, price, holders, monitoring, address/issuer risk, transaction simulation, route finding, wallet activity, endpoint trust, and attestation. There are no obvious dead ends; users can discover tokens, verify them, track them, and receive alerts—a full lifecycle for crypto risk assessment.
