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Glama

US Economic, SEC EDGAR & On-Chain Data (x402)

by net.agentfund

SEC Insider Transactions (Form 4)

edgar_insider_transactions
Read-onlyIdempotent

Insider buying and selling for a U.S. public company, parsed from SEC Form 4 filings.

Form 4 is published as raw ownership XML, one document per filing, with the machine-readable file hidden behind an XSL-rendered URL. This resolves the ticker to a CIK, finds the most recent filings, fetches each XML document, and returns clean transactions: who traded, their role, the date, the SEC transaction code with its plain-English meaning, share count, price, computed dollar value, and shares held afterwards.

When to use: tracking insider sentiment, checking whether executives are buying or selling, auditing recent officer and director activity.

When NOT to use: you need institutional holdings (that is Form 13F), or derivative/option detail (only non-derivative transactions are returned), or non-U.S. issuers.

Args:

  • ticker (string, required): a ticker such as "AAPL", or a bare CIK such as "320193".

  • limit (integer, optional, default 5): how many recent filings to parse (1-20).

  • forms (string[], optional, default ["4"]): which ownership forms to include ("3", "4", "5").

Returns structuredContent: { "cik": "0000320193", "issuer": "Apple Inc.", "ticker": "AAPL", "count": 1, "filings": [{ "filedAt": "2026-08-13", "owner": "Newstead Jennifer", "ownerTitle": "SVP, GC and Secretary", "isOfficer": true, "isDirector": false, "transactions": [{ "date": "2026-08-11", "code": "S", "codeMeaning": "Open-market or private sale", "acquiredDisposed": "D", "shares": 1439, "pricePerShare": 307.75, "value": 442852.25, "sharesOwnedAfter": 40107 }], "documentUrl": "https://www.sec.gov/Archives/..." }], "source": "https://www.sec.gov/edgar" }

An individual filing that cannot be parsed is skipped rather than failing the call. If nothing at all is parseable the call errors and is not billed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
formsNoWhich ownership forms to include. Defaults to ["4"].
limitNoHow many recent ownership filings to parse (1-20). Default 5.
tickerYesTicker symbol (e.g. "AAPL") or a bare SEC CIK (e.g. "320193").

Schema Changelog

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

  1. First observed

TDQS

A4.7/5.0
Behavior5/5

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

Discloses important behaviors beyond the read-only/idempotent annotations: individual unparseable filings are skipped, total parse failure errors and is not billed, and the underlying XSL-rendered URL quirk is explained. This gives the agent confidence in edge-case handling.

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?

The description is well-structured with clear sections and no filler. The JSON example is lengthy but necessary given there is no output schema, and every sentence serves a purpose.

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

Completeness5/5

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

Despite lacking an output schema, the description includes a complete JSON response example, covers error behavior, exclusions, and the data source. It thoroughly equips an agent to use the tool correctly.

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 provides full descriptions for all three parameters (ticker, limit, forms) with default values and constraints. The description's Args section essentially repeats this information without adding new semantic nuance.

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 clearly states it parses SEC Form 4 filings to return insider transactions for a U.S. public company. It explicitly differentiates from sibling tools like edgar_13f_holdings by noting that institutional holdings are NOT the intended use case.

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

Usage Guidelines5/5

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

The description includes dedicated 'When to use' and 'When NOT to use' sections, naming Form 13F as the alternative for institutional holdings. This explicitly guides the agent on when to select this tool versus siblings.

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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TDQS

A4.5/5.0
Disambiguation5/5

Every tool targets a distinct resource and action. The macro_* tools each cover one economic indicator, the edgar_* tools cover different SEC filing types, and the onchain_* tools are split by chain scope (single vs multi), asset type, and operation. Even the two data-cleaning tools are clearly distinct (JSON repair vs table parsing). No two tools appear to do the same thing.

Naming Consistency4/5

Names follow a mostly consistent snake_case pattern with domain prefixes: macro_*, edgar_*, onchain_*. The exceptions are bls_cpi (could be macro_cpi) and the utility tools structured_json_repair and tabular_to_json, which break the prefix pattern but are still descriptive and predictable. Overall, the convention is clear with minor deviations.

Tool Count3/5

21 tools is in the 'heavy' range (16-25). However, the server spans three distinct domains (US economic data, SEC EDGAR, on-chain data), and each tool serves a unique purpose within its domain. While it feels dense, the breadth is justified by the server's stated multi-domain scope.

Completeness4/5

The tool surface covers the major needs in each domain: key macro indicators, common EDGAR filings and searches, and core on-chain reads. Minor gaps exist (e.g., no PPI, no historical on-chain balances, no company CIK lookup), but agents can work around these with existing tools or by combining them.

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