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Financial Datasets

by io.github.pipeworx-io
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Fd Insider Transactions

fd_insider_transactions
Read-onlyIdempotent

Insider (Form 4) transactions for — recent buys/sells by officers, directors, and 10%+ owners as reported on SEC Form 3/4/5. Returns insider name, title, transaction type, shares, price, date, and board-director flag. Example: fd_insider_transactions({ ticker: "AAPL", limit: 25, _apiKey: "your-key" })

Example tool call

This call uses example arguments supplied in the tool’s input schema.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "ticker": "AAPL",
      "_apiKey": "your-financial-datasets-api-key"
    },
    "name": "fd_insider_transactions"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNoMax transactions to return (default 25, max 1000)
tickerYesStock ticker symbol, e.g. "AAPL"
_apiKeyYesFinancial Datasets API key (from financialdatasets.ai)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds context beyond that: it names the data source (SEC Form 3/4/5) and enumerates the returned fields, which matters because no output schema exists. It does not mention rate limits or pagination, keeping it at a 4.

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?

Three tight sentences with the core purpose front-loaded, followed by return fields and a concrete call example. No wasted prose, though the example partially duplicates the schema's own examples.

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 simple read-only lookup with no output schema, the description carries the return-value burden well by listing the fields an agent will receive. Combined with full schema coverage and clear annotations, almost nothing needed to call it correctly is missing.

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?

Schema coverage is 100%, so ticker, limit, and _apiKey are already documented in the schema, and the description adds no syntax or format detail beyond restating ticker and limit in an example. Baseline 3 is appropriate when the schema does the heavy lifting.

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?

States a specific verb and resource: insider Form 4 transactions for a given ticker, covering buys/sells by officers, directors and 10%+ owners. An agent immediately knows what data is returned, but the description never differentiates itself from sibling financial tools such as fd_filings or fd_institutional_holders, so it lands just 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?

Usage is implied by the phrasing ('transactions for <ticker>'), which tells the agent this is a per-ticker lookup, but there is no explicit when-to-use, when-not-to-use, or routing to alternatives like fd_filings for other SEC data. Adequate but with a clear gap.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Financial Datasets toolsInspect
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