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Glama

Helious market intelligence

NASDAQ-100 board

get_nasdaq100
Read-onlyIdempotent

The NASDAQ-100 ranked best to worst on the session: price, change and sector for every stock. Pass symbol to ask about ONE company instead, like AAPL or NVDA, and you get its price, its move on the session and where it ranks on the board today. Equities are market data: live on Pro and Ultimate, upgrade steps instead of numbers below.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMost stocks to return.
symbolNoOne or more NASDAQ-100 tickers, comma separated, like AAPL or AAPL,MSFT. Empty returns the whole ranked board.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already mark the tool as readOnly and idempotent, so the description does not need to repeat that. It adds meaningful behavior: the ordering semantics ('best to worst'), what each board entry includes, and that live data requires Pro/Ultimate. The 'upgrade steps instead of numbers below' detail is genuinely useful for interpreting placeholder responses.

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?

Three short sentences, each earning its place: first defines the board content, second defines the symbol-filtered behavior, third explains data freshness and access tier. Information is front-loaded and there is no padding or repetition of schema details.

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 read-only board/filter tool with full schema descriptions and rich annotations, the description covers the essential outputs, ordering, filtering, and access-tier nuance. While a structured output schema is missing, the prose is enough for an agent to call it correctly. Minor gaps such as the interaction with limit are already handled by the schema.

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 already documents both parameters 100%, including that symbol supports comma-separated tickers and empty returns the full board. The description's prose reinforces the symbol parameter and adds examples, but does not significantly extend or clarify beyond the schema. The phrase 'ONE company' is slightly narrower than the schema's 'one or more' but the schema resolves that difference.

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

Purpose5/5

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

The description states a specific action and resource: it returns the NASDAQ-100 ranked best to worst, with price, change, and sector for each stock. It distinguishes itself from the sibling board tools (fx_board, vol_board) via the NASDAQ-100 qualifier and adds filtering to a single company. No ambiguity remains about what the tool does.

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 clearly explains two usage modes: no symbol returns the whole ranked board, and passing a symbol returns a single company's price, session move, and rank. It also conveys access-tier behavior by noting data is live on Pro/Ultimate. It does not explicitly name alternatives for exclusion, but the two modes provide clear practical guidance.

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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