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BotSpot: AI Trading, Backtests and Bots

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Query market research data

query_data
Read-only

Query a registered research dataset by datasetId. Use for versioned symbol-membership universes, SEC company facts, SEC financial statements, SEC current filings, SEC full-text search, SEC filing exhibits, SEC insider transactions, SEC 13F holdings, Treasury FiscalData/yield curves, BLS series, BEA datasets, OFR funding data, and CFTC COT positioning. For person-named 13F research, resolve the legal filer from official filing/search evidence before querying holdings. A manager filing is delayed institutional disclosure, not a current personal portfolio. A symbol universe supplies membership only. Retrieve market observations through the user's exact saved broker connection. For bea_gdp_release_archive, filters.releaseYear and timezone-aware asOf select publisher-attested original annualized real-GDP growth estimates at the exact UTC release clock. Qualification covers that metric only, not current document bytes or complete history. Other historical sources must advertise their qualified capabilities; unavailable evidence fails visibly. For botspot.news.public.v1, pass filters.query and optional UTC calendar timeRange bounds. This profile returns GDELT metadata only: headlines and links, not article bodies or verified ticker matches. Observation timestamps do not prove publication time or original historical availability. Full-text and historical asOf requests fail visibly. For botspot.news.alpaca.v1, select your own filters.brokerCredentialId and aware filters.start/end. Optional filters.symbols, includeContent, contentMaxChars and pageToken request one bounded licensed page. Historical asOf requires explicit filters.availabilityMode=provider_versions: provider publication/update ceilings exclude known future versions, but coverage and original history remain unqualified. Never substitute this profile for public news or another owner’s connection. Do not use this for real-time prices, broker account data or options chains.

Input Schema

NameRequiredDescriptionDefault
asOfNoHistorical availability ceiling, preferably a timezone-aware ISO timestamp. Calendar-period selection alone is not publication-time or original-vintage replay. Unqualified source history returns unsupported_capability.
limitNo
entityNoTicker, CIK, company/manager name, market name, or public series query depending on the dataset. For 13F holdings, use a verified legal filing manager name or CIK; resolve person names or fund nicknames from official filing evidence first.
filtersNoDataset-specific bounded filters, such as SEC forms, Treasury topic/apiPath, BLS seriesIds, BEA method/datasetName/parameters, OFR mnemonics, or CFTC reportType.
metricsNoMetric aliases or source-native series/concepts, such as revenue, CPI, unemployment, or BEA table metrics.
entitiesNo
datasetIdYesDataset id from search_data_catalog, for example sec.company_facts or bea.api_datasets.
timeRangeNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior5/5

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

Annotations already mark this as read-only, but the description adds substantial behavior detail beyond that: qualification limits, visibility of unsupported historical requests, metadata-only news results, broker-credential scoping, provider-version ceilings, and page-bound behavior. No contradiction with readOnlyHint is present.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The core purpose is front-loaded, but the description becomes a dense wall of dataset-specific qualifications that is hard to scan and likely contains details better placed in dataset-specific documentation. It is information-rich but not concise.

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 complex eight-parameter, nested, multi-dataset query tool with no output schema, the description is unusually thorough about dataset-specific constraints, failure modes, and historical limitations. It still does not explain general return shape, pagination beyond the Alpaca news profile, or limit behavior, leaving some contextual gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description adds significant meaning beyond the schema for datasetId, asOf, entity, filters, and timeRange in specific profiles, including dataset-specific filters such as releaseYear, query, brokerCredentialId, availabilityMode, and UTC calendar bounds. It still leaves limit, entities, and metrics comparatively underspecified, and schema coverage is only 63%.

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 first sentence states a specific verb and resource: query a registered research dataset by datasetId. The description also enumerates the dataset families it covers and explicitly excludes real-time prices, broker account data, and options chains, which separates it from sibling broker-market tools.

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?

It gives clear positive use cases (SEC, Treasury, BLS, BEA, OFR, CFTC, news profiles) and negative exclusions (real-time prices, broker account data, options chains). It also gives conditional guidance for person-named 13F queries and the two news profiles, though it does not explicitly say in prose to use search_data_catalog first to obtain datasetId.

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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