List Services
list_servicesList every Cybercentry verification service with its price, inputs and SLA. Free.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Cybercentry Verification
TDQS
A4/5.0
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries the burden. It adds 'Free' and 'every', providing some context, but does not disclose output format, pagination, or any other behavioral traits. For a simple list tool, this is adequate but not comprehensive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that conveys purpose, content, and cost without any filler. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (no params, no output schema), the description covers the essential information: what it lists and that it is free. It could mention the return format, but for a zero-parameter list tool, this is nearly complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so there is nothing to explain beyond the schema. Baseline for 0 params is 4, and the description correctly focuses on what the tool returns.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description states a specific verb ('List') and resource ('every Cybercentry verification service') with detailed content (price, inputs, SLA). This clearly distinguishes it from the sibling tools, which are individual verification services.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage is implied: use this tool to list all services. However, it does not explicitly state when to use it versus alternatives (e.g., specific verification tools), nor does it provide 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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TDQS
A4.1/5.0
Disambiguation4/5
Most tools target distinct domains (token, media, AI agent, wallet, web app, code), but `base_token_verification` and `ethereum_token_verification` are closely related and could be confused despite chain-specific descriptions. The informational tools (`list_services`, `recent_exploits`) are clearly separate.
Naming Consistency4/5
All tool names are lowercase snake_case, with the majority following a `[domain]_verification` pattern. The exceptions (`cyber_security_consultant`, `list_services`, `recent_exploits`) are still clear but deviate from the dominant suffix convention.
Tool Count5/5
12 tools is a well-scoped size for a multi-domain verification service. Each tool represents a distinct service category, and the count feels appropriately comprehensive without being bloated.
Completeness5/5
The tool surface covers major verification needs across tokens, code, media, AI agents, wallets, web apps, private data, and quantum-safe encryption. The addition of `cyber_security_consultant`, `list_services`, and `recent_exploits` provides context and support, leaving no obvious dead ends for typical use cases.