stocktoken_policy_get
Get current AI Agent Tokenized Stock OS agent policy (max notional, slippage, simulate-first, kill switch).
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
AI Agent Tokenized Stock OS
by dev.aatos
TDQS
A3.6/5.0
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, but description indicates a read operation. It lists policy components but does not disclose auth requirements, rate limits, or side effects. Adequate for a simple getter.
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?
Single sentence, front-loaded with verb and resource. Every word is informative, no redundancy.
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 no parameters and no output schema, description covers purpose and key fields. Could mention return format or when this policy applies, but sufficient for a simple getter.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters in schema (100% coverage). Description adds no parameter meaning beyond what schema provides, baseline 3.
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 clearly states it gets the current AI agent policy and lists specific fields (max notional, slippage, etc.), distinguishing it from sibling tools like stocktoken_policy_set.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs. alternatives. Does not mention when not to use or compare to similar getter tools among the 30+ siblings.
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.