Domain registration age via RDAP. Returns the FACT of the domain's age (registration date, age in days, expiry, registrar). A brand-new domain is a NEUTRAL signal to state and weigh, not a verdict — it's normal for a fresh project and also common in throwaways. Use it in PRE-LAUNCH due diligence and whenever a project points to a website.
| Name | Required | Description | Default |
|---|---|---|---|
| domain | Yes | the domain or URL (e.g. runebrokers.com) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral burden. It discloses the output is a 'FACT' and provides interpretive guidance for new domains (neutral signal), showing awareness of how results should be framed. It omits edge-case behavior (e.g., errors on invalid domains) but is sufficient for a read-only lookup.
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 three sentences, tightly written, with no redundancy. It front-loads the core function ('Domain registration age via RDAP') then adds interpretive and usage guidance, all earning their place.
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?
For a simple one-parameter tool with no output schema, the description adequately covers the return values (registration date, age, expiry, registrar) and usage context. It is complete for an agent to understand what to expect.
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% and already defines 'domain' as 'the domain or URL (e.g. runebrokers.com).' The description doesn't add parameter-specific detail beyond that, 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 explicitly states 'Domain registration age via RDAP' and lists exact data points (registration date, age in days, expiry, registrar). This clearly identifies the resource and differentiates it from sibling tools focused on tokens, NFTs, and stocks.
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?
Provides explicit usage context: 'Use it in PRE-LAUNCH due diligence and whenever a project points to a website.' It doesn't name alternative tools or exclusions, but the context is clear enough for an agent to decide when to invoke.
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.
Many tools share the same core purpose (safety checks) differentiated mainly by chain or asset type, and descriptions are detailed enough to distinguish them most of the time. However, pairs like rug_check/rugcheck and deployer_check/deployer_reputation have overlapping purposes that could lead to misselection.
Most tool names follow a lowercase snake_case pattern with clear descriptors, but there are notable exceptions like 'rugcheck', 'defillama', and 'verify'. Additionally, the 'rug_check' vs 'rugcheck' pair is an obvious naming inconsistency.
44 tools is excessive for any server. Even for a broad security/due-diligence purpose, many tools (especially the robinhood_* series) are highly specialized and could be consolidated into fewer actions.
The tool surface is impressively comprehensive, covering token/NFT safety, transaction simulation, whale/address tracking, stock analysis, prediction markets, and project validation. Minor gaps exist (e.g., no ENS resolution or stock price history), but they are not critical for the server's core purpose.
