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extract_sec_filings

Read-only

SEC 8-K filings via EDGAR full-text search. 8-K = legally mandated material event disclosures (CEO changes, M&A, breaches). Pass company name, ticker, or keyword.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesCompany name, ticker, or keyword

Schema Changelog

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

  1. Added

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already indicate readOnlyHint and openWorldHint, so the description adds context about EDGAR full-text search and the legal nature of 8-K filings. Yet it does not disclose potential limitations such as date ranges, pagination, or specific search syntax, which would be valuable for a search tool.

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 concise, with two sentences that front-load the purpose and method in the first sentence and provide context and usage in the second. Every word adds value; no filler.

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 single-parameter tool with annotations covering safety and open-world behavior, the description is fairly complete: it states what it does, how to call it, and the meaning of 8-K. The lack of output schema and detailed return format is acceptable, though a note about result size or limitations would push it higher.

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 schema describes the single parameter 'url' as 'Company name, ticker, or keyword', and the tool description repeats this, giving clear semantics. However, the parameter name 'url' is misleading since it expects a search term, and the description does not provide examples or format details, so it doesn't add much beyond the 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 identifies the tool as retrieving SEC 8-K filings via EDGAR full-text search, with a specific resource and method. It also explains the nature of 8-K filings, distinguishing it from other extract_* tools, though it doesn't explicitly name an alternative.

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 usage for material event disclosures by defining 8-K, and provides a direct instruction to pass a company name, ticker, or keyword. However, it does not explicitly state when to prefer this tool over siblings like extract_finance or other SEC-related tools.

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

A3.9/5.0
Disambiguation5/5

Each tool targets a distinct data source (finance, GitHub, Hacker News, etc.), with clear separation and no overlap. An agent can easily distinguish which tool to use for a given source.

Naming Consistency4/5

Tools use a consistent verb_noun pattern with 'extract_' for data extraction and 'search_' for search functions. The outlier 'package_trends' is still descriptive and fits the theme, so the pattern is mostly predictable.

Tool Count5/5

11 tools is well-scoped for a data aggregation server. Each tool serves a clear purpose and the count is neither too sparse nor overwhelming.

Completeness4/5

The server covers a broad range of sources (finance, code, news, social, academia, jobs, packages). Minor gaps like missing Twitter or general news are acceptable given the breadth already provided.