Place demo stock market or limit orders while enforcing per-order and daily USD limits and human approval for larger trades.
[TAS Guard: max 2000 USD per order, 5000 USD per day; orders over 1000 need human approval] Place a demo stock order. Market orders fill at the simulated price; limit orders rest until cancelled.
| Name | Required | Description | Default |
|---|---|---|---|
| qty | No | ||
| side | Yes | ||
| type | No | ||
| symbol | Yes | ||
| notional | No | ||
| limit_price | No |
Changes observed during successful MCP inspections.
v0.2.3Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With only destructiveHint=true from annotations, the description carries the burden and delivers: per-order and per-day notional caps, a human-approval threshold, and the execution semantics of each order type (market fills at simulated price, limit rests until cancelled). This is exactly the kind of risk and lifecycle context an agent needs before a mutating call.
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?
Two sentences with zero waste; the risk guard is front-loaded in brackets ahead of the operational description, so the highest-stakes information is read first.
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?
The risk limits and order-type semantics are covered, but with six parameters, no schema descriptions, and no output schema, the description leaves the parameter contract substantially undocumented. It is adequate for a simple call but not complete for a tool whose fields are entirely self-describing only by name.
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?
Schema description coverage is 0% across six parameters, and the description adds nothing about them beyond order-type behavior. It never explains the relationship between qty and notional, whether either is optional in practice, the string-encoded numeric format, or how limit_price interacts with type.
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?
States a specific verb and resource ('Place a demo stock order') and clarifies the simulated nature of the operation, which separates it cleanly from the read-only and cancellation siblings. It also distinguishes market vs. limit order behavior, so an agent knows exactly which operation it is invoking.
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 TAS Guard preamble conveys real constraints (2000 USD/order, 5000 USD/day, human approval over 1000) that imply when an order is permissible. However, it never says when to use this tool versus alternatives such as tas_guard_status (to check limits beforehand) or the cancel tools, so routing is left to inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.