remove_from_cart
Storefront: remove a line.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| product_id | Yes |
Storefront: remove a line.
| Name | Required | Description | Default |
|---|---|---|---|
| product_id | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states 'remove a line' without revealing what happens to the cart, whether the operation is idempotent, what errors may occur, or what the effect is on other cart state. The mutation implication is clear, but beyond that the behavior is opaque.
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 short sentence with no wasted words. It is front-loaded and easy to skim. However, the brevity crosses into under-specification, omitting key context, which limits the structural value.
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?
For a tool with one parameter and no output schema, the description should at minimum define what 'line' means and how product_id is used. It does neither. The absence of annotations and schema descriptions leaves gaps in what the agent needs to call it correctly and predict outcomes.
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% and the description does not mention product_id at all. The parameter's role must be inferred entirely from its name and the tool name. The description adds no meaning about how product_id identifies the line to remove, any constraints, or behavior when the product is not in the cart.
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 'Storefront: remove a line' uses a clear action verb ('remove') and a resource ('line') that aligns with the tool's name 'remove_from_cart'. However, 'line' is somewhat vague jargon and the description does not explicitly connect it to a cart item, nor does it differentiate itself from siblings like update_cart_item beyond the verb.
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 gives no guidance on when to use this tool versus alternatives such as add_to_cart or update_cart_item. There is no mention of context, prerequisites, or situations that would favor remove_from_cart over other cart-related tools.
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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Most market-data and storefront tools are cleanly scoped, but there is meaningful overlap: get_full_board and get_engine_feed are near-duplicates, get_buy_list overlaps with get_morning_brief's candidate list, and get_orders / get_order_status are identical NotOffered stubs. The free/live twin pairs are clearly labeled so agents can distinguish latency/payment intent, but the sheer number of related reads creates selection friction.
The large get_* data family is very predictable (get_stock_read, get_stock_read_live, get_rotation, get_rotation_live), and storefront ools use clear verb_noun actions (add_to_cart, remove_from_cart, save_memory). Minor deviations like checkout_handoff and the get_live_setup / get_live_rules naming (which could be misread as *_live twins) keep it from a perfect score.
46 tools is well abovethe 25+ threshold for a coherent toset; at leat13 are direc live twins of free readable plus a 14-tool storefont/memory subdomain. Many could be consoliated into ingle tools with a delay/live param or a single storefront resource, making the surface feel bloated for agents.
The market-data surface is very comphehensive: regime, buy-list, hold-state, rotation, sector, stock, crypto day/night/trend/setups, full board, archived board, changes, and engine-feed coverage leave few dead ends for the stated trading-intelligence purpose. Storefont is adequate but has minor acknowledged gaps—orders/order-status are NotOffered stubs and session memories have no update/delete—so it is not a perfect 5.