One sector's drill-down: every member of the sector scored and ranked by opportunity, plus the sector's own ETF row. Accepts a sector name (e.g. 'Energy', 'Information Technology') or its ETF symbol (e.g. XLE, XLK). Unknown values return the sector directory. Free tier: one market day delayed. Live sibling (x402, pay-per-call): get_sector_read_live.
| 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 correctly discloses key behavioral traits: one market day delay, unknown values return the sector directory, and the output includes member rankings and ETF row. It does not mention rate limits or auth, but for a read-only tool the delay and fallback are the most relevant traits.
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 sentences, each with distinct purpose: output content, input flexibility, and tier/alternative. There is no filler or redundant information.
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?
With no output schema, the description provides a clear sense of the return value ('every member... scored and ranked... plus the sector's own ETF row'). It covers the tool's function, input format, fallback behavior, and alternative tool, making it complete for a one-parameter read operation.
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 schema describes 'sector' as 'Sector name or sector-ETF symbol' (100% coverage), but the description adds concrete examples like 'Energy' and 'XLE', and explains the behavior for unknown values. This meaningfully extends the schema.
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 begins with 'One sector's drill-down' and specifies the exact outputs: every member scored and ranked by opportunity, plus the sector's own ETF row. This clearly distinguishes it from sibling tools like get_full_board or get_sector_read_live.
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 names the alternative 'get_sector_read_live' and labels it as pay-per-call, while stating the free tier has one market day delay. This tells the agent when to use this tool vs. the live sibling.
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.
