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Draft Order

draft_order

Draft a stock order (buy/sell) with symbol and quantity for human review and approval. Prevents automatic order execution, requiring manual confirmation in the dashboard.

Instructions

Drafts an order for human review and approval in the Streamlit Dashboard. For safety, the assistant NEVER places orders directly. All orders must be drafted and manually approved.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
actionYesBUY or SELL.
symbolYesTicker symbol (e.g. AAPL, TSLA).
quantityYesNumber of shares.
order_typeNoLMT (Limit) or MKT (Market).LMT
limit_priceNoThe limit price if order_type is LMT.
Install Server

TDQS

A4/5.0
Behavior4/5

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

Annotations already indicate non-read-only, non-destructive, and non-idempotent behavior, but the description adds valuable context: the tool does not execute orders, only creates a draft requiring human approval. This discloses a key side-effect limitation. It omits details about whether the draft is persisted or what happens after approval, but the core behavior is transparent.

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 three concise sentences that front-load the purpose and immediately present the safety rule. Every sentence earns its place with no wasted words or 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?

For a 5-parameter tool with no output schema, the description provides sufficient context: what the tool does, the mandatory manual approval workflow, and the dashboard environment. It lacks explicit return-value or post-approval details, but these are not essential for selecting or invoking the tool correctly.

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?

The input schema has 100% coverage for all 5 parameters, so the baseline is 3. The description does not add any parameter-specific guidance beyond what the schema already provides. There are no enums or nested objects requiring further explanation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the purpose with a specific verb ('drafts') and resource ('an order for human review and approval'). It distinguishes the tool from direct order placement via the safety constraint. However, it does not explicitly differentiate from the sibling preview_order, leaving some ambiguity about when to use draft vs preview.

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 delivers an explicit when-to-use guideline: all orders must be drafted and manually approved, so the assistant should use this tool instead of placing orders directly. This is clear and actionable. It does not explicitly name alternatives or when not to use the tool, but the safety rule is sufficient.

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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