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get_institutional_stock

[$0.1 per call] News Gurus Intel API — one ticker's institutional picture: congressional trades + 13F fund moves in a single call. Example NVDA: J. Smith (D) Purchase $1,001-$15,000 on 2026-06-15; Vanguard Group increased. Public STOCK Act and SEC 13F filings merged by the bot; analyst-rating and fundamentals fields excluded (vendor licensing). Answers 'who is buying TICKER'. Educational data, not financial advice. HOW TO PAY: an x402-capable client settles the payment challenge automatically (USDC on Base, no account needed); wallet-less clients pass a subscriber API key instead (Authorization: Bearer , X-API-Key header, or ?api_key= query) for calls within their plan. Browse every tool + price first with the FREE get_catalog tool.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
symbolYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.6/5.0
Behavior5/5

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

With no annotations provided, the description carries the full burden, and it does so thoroughly: it discloses the $0.1 per-call cost, the x402 payment flow, subscriber API key alternatives, excluded fields due to vendor licensing, the fact that public filings are merged by the bot, and an educational-data disclaimer. It also reveals that output includes example trade details and fund movement descriptions, which is valuable beyond any structured metadata.

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

Conciseness4/5

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

The description is long but each sentence earns its place: pricing, data scope, example, exclusions, payment/auth instructions, and catalog pointer. It is front-loaded with the most decision-relevant information and the 'HOW TO PAY' section is clearly organized. Slightly dense, but not padded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers purpose, pricing, payment, auth, data sources, and exclusions, which is strong for tool selection. However, there is no output schema and the description leaves out the meaning of `limit`, return structure, and potential error/empty-result behavior. An agent could invoke it with just the required symbol, but would be guessing about parameter semantics and response shape.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate, but it only indirectly clarifies the `symbol` parameter through 'TICKER' and the NVDA example. The `limit` parameter is not mentioned at all, leaving its meaning, behavior, and default undocumented. This is only partial compensation for a fully undocumented schema.

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

Purpose4/5

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

The description clearly states the tool's function: retrieving one ticker's institutional picture by merging congressional trades and 13F fund moves. It is specific about the resource and scope, and its 'Answers who is buying TICKER' framing makes the purpose actionable. However, it does not explicitly differentiate itself from the similar sibling get_institutional_moves, so it falls short of a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies the tool should be used when a user needs institutional buying activity for a single ticker, and it provides an illustrative NVDA example. It does not state when to prefer this over siblings like get_congress_trades or get_institutional_moves, nor does it give exclusion criteria. The usage context is clear but largely implicit.

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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