Simulate / pre-trade check for a tokenized stock swap on chain 4663: allowlist, policy, multi-venue quote integrity.
| Name | Required | Description | Default |
|---|---|---|---|
| tokenIn | Yes | ||
| amountIn | No | ||
| tokenOut | Yes | ||
| sessionId | No | ||
| notionalUsd | Yes | ||
| slippageBps | No | ||
| amountInHuman | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses that the tool performs a pre-trade check on allowlists, policies, and quote integrity, indicating it is a read-only simulation. It does not describe authentication needs, rate limits, or potential side effects, but the core behavior is adequately communicated.
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 a single, front-loaded sentence that conveys the tool's purpose and key aspects efficiently with no wasted words.
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?
Given the complexity (7 parameters, no output schema, many sibling tools), the description is insufficient. It covers only the high-level purpose and omits parameter details, return value, and usage context, leaving significant gaps for an agent to use the tool correctly.
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 has 7 parameters with 0% schema description coverage, and the description does not explain any parameter's meaning or format. Required parameters (tokenIn, tokenOut, notionalUsd) are not detailed, leaving an agent to guess their purpose.
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 clearly states the tool simulates a pre-trade check for a tokenized stock swap, listing specific checks (allowlist, policy, multi-venue quote integrity). It distinguishes this from sibling tools like stocktoken_quote (which provides a quote) and stocktoken_execute_plan (which executes).
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 implies this tool is used for simulation before a trade, but does not explicitly state when to use it versus alternatives (e.g., stocktoken_quote for a simple quote). No exclusions or alternative tools are named, but the context is clear enough for an agent.
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.
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.
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.
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.
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.