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AI Agent Tokenized Stock OS

stocktoken_explain_routing

Explain when to use AI Agent Tokenized Stock OS vs Robinhood official Agentic Trading MCP vs raw Uniswap/0x.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
userIntentNo

TDQS

B3.3/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description must carry the full burden of behavioral disclosure. It only states the tool explains something, implying it is read-only and non-destructive, but it does not confirm whether it has side effects, requires authentication, or how it interacts with external systems. Minimal transparency.

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 sentence that directly states the tool's function. It is front-loaded and contains no filler, making it highly efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description is very brief for a decision-support tool. It does not explain what form the explanation takes (e.g., text, structured data) and lacks details on how the routing decision is made. Without an output schema, the agent has no guidance on what to expect from the tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has one parameter ('userIntent') with 0% coverage (no description in schema). The tool description does not mention this parameter at all, so it adds no meaning beyond the schema. Given low schema coverage, this is a critical gap.

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?

The description explicitly states the tool's purpose: 'Explain when to use AI Agent Tokenized Stock OS vs Robinhood official Agentic Trading MCP vs raw Uniswap/0x.' It uses a specific verb ('explain') and resource ('routing' between three systems), clearly distinguishing it from sibling tools which are mostly transactional or access-related.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage context: when a user needs to decide between three trading systems. It does not explicitly state when not to use it or mention alternatives, but the sibling list contains many other tools, and this is the only one for routing explanation, making the context clear.

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

A3.7/5.0
Disambiguation5/5

All tools have clearly distinct purposes, covering access management, token queries, trading, sessions, subscriptions, tips, and system operations. No two tools appear to do the same thing; even related tools like deposit/withdraw plans are differentiated.

Naming Consistency5/5

All tools follow a consistent 'stocktoken_' prefix with lowercase underscore-separated names. The pattern is uniform (e.g., verb_noun or single noun), with no mixing of camelCase or other styles.

Tool Count4/5

37 tools is high for an MCP server but each tool addresses a specific function within a complex domain (tokenized stock OS, on-chain payments, subscriptions, etc.). The count is justified, though slightly beyond typical scoping.

Completeness5/5

The tool surface covers all major aspects: access lifecycle, token metadata, trading (simulate, quote, execute plan), sessions, subscriptions, tips, policies, liquidity, and system status. No obvious gaps exist for the stated domain.

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