Live intraday get_sector_read: a sector's members scored and ranked from the current session. No wallet? get_sector_read is free, one market day delayed. $0.01 USDC per call (x402).
| Name | Required | Description | Default |
|---|---|---|---|
| sector | Yes | Sector name or sector-ETF symbol |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavior itself. It discloses the $0.01 USDC per call cost and the x402 payment protocol, plus the 'live intraday' nature and that it requires a wallet. It does not mention read-only status or rate limits, but 'read' in the name and the non-destructive description make side effects unlikely. This is a reasonable level of transparency for a paid data retrieval tool.
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 three short sentences: purpose, alternative guidance, and pricing. Each sentence conveys distinct useful information with no filler, making it well-structured and easy to scan.
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 tool has only one parameter and no output schema. The description explains what it does (scores and ranks sector members), when it's live, the cost, and the condition to use a free alternative. It lacks explicit details about the output format (e.g., an array of objects with score fields), but for a simple single-query tool this is arguably sufficient. A small gap in specifying exactly what 'scored and ranked' means keeps it just below a perfect score.
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 single 'sector' parameter is fully described in the schema as 'Sector name or sector-ETF symbol.' The tool description only refers to 'a sector's members,' which is consistent but does not add extra syntax or examples beyond the schema. With 100% schema coverage, the description adds little marginal value, so a baseline score of 3 applies.
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 identifies the tool as a live intraday version of get_sector_read, specifying that it scores and ranks a sector's members from the current session. It distinguishes itself from the delayed free alternative via the 'live' qualifier and explicitly names get_sector_read.
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?
It explicitly states that if the user has no wallet, they should use the free, one market day delayed get_sector_read instead. This provides clear conditional guidance for when to choose the alternative, and the 'live intraday' framing implies use when current session data is needed.
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.
