address_age
Look up wallet age in days for any address. The uncheatable signal; time cannot be faked.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| chain | No | Chain slug (optional, defaults to base) | |
| address | Yes | Wallet address (0x...) |
Look up wallet age in days for any address. The uncheatable signal; time cannot be faked.
| Name | Required | Description | Default |
|---|---|---|---|
| chain | No | Chain slug (optional, defaults to base) | |
| address | Yes | Wallet address (0x...) |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden of behavioral disclosure. It indicates a read-only lookup of age in days and adds a trust-related note ('time cannot be faked'), but does not detail any side effects, prerequisites, or output format. This is adequate for a simple read operation.
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 two short sentences, front-loaded with the primary action, and contains no filler. Every word contributes to understanding the tool's purpose.
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 lookup tool with full schema coverage and no output schema, the description covers the essential behavior and the unit of measurement. It could mention the output format explicitly, but the phrase 'age in days' implies the return value sufficiently.
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?
The input schema already provides 100% coverage of both parameters (address and chain) with descriptions. The tool description adds no extra parameter-specific detail, so the baseline of 3 applies.
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 uses a specific verb ('Look up') and clearly identifies the resource ('wallet age in days') for any address. The phrase 'uncheatable signal' also differentiates it from sibling tools that likely measure other metrics.
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 gives no explicit guidance on when to use this tool versus alternatives. It states 'for any address,' which is a scope, but there is no 'when not to use' or mention of alternative tools.
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.
Most tools have distinct purposes, but reviewer_analysis and reviewer_wallet overlap in analyzing reviewer behavior, and trust_check and risk_terms both provide trust assessments with different framing. Descriptions help clarify the differences, yet an agent could easily misselect between these pairs.
All tool names use snake_case, but the pattern is inconsistent: some are verb_noun (compare_agents, trust_check) while others are noun-based (address_age, entity, mcp_attestation). This mixed convention is readable but not predictable.
10 tools is well-scoped for an AI agent trust intelligence server, covering both individual lookups and network-wide statistics without unnecessary redundancy. Each tool addresses a specific analytical need.
The server covers the core trust intelligence surface: trust scores, risk assessment, wallet profiling, reviewer analysis, commerce stats, and network stats. Minor gaps exist, such as no tool to fetch a single agent's full profile independent of an operator, but overall the domain is well covered.