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Glama

Sec Form D

by io.github.pipeworx-io

Form D Related Person Search

form_d_related_person_search
Read-onlyIdempotent

Find Form D notices mentioning an executive, promoter, director, or other related person, then return only filings whose parsed related-person list matches the name. Useful for mapping repeat founders and fund managers; relationships are filer-supplied.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMatching filings to return (1-10, default 5).
sinceNoStart filing date YYYY-MM-DD. Default 5 years ago.
untilNoEnd filing date YYYY-MM-DD. Default today.
personYesPerson name or distinctive substring.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
returnedYes
offeringsYes

Schema Changelog

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

  1. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint as false. The description adds context by explaining that returned results are based on a parsed related-person list and that relationships are filer-supplied, which goes beyond the annotations without contradicting them.

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 two sentences with no redundant words. It front-loads the action and purpose, making it easy for the agent to quickly understand the tool's function.

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?

Given the presence of annotations, full schema coverage, and an output schema, the description is complete. It covers the tool's use, matching behavior, and data source, leaving no obvious gaps for the agent.

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?

Schema coverage is 100%, so parameters are well-documented. The description adds meaning by explaining that the 'person' parameter is used to match after parsing, which clarifies the matching logic beyond the schema's description of the parameter.

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 the tool's action: finding Form D notices mentioning a related person and returning only filings where the parsed related-person list matches the given name. It distinguishes this from sibling tools like form_d_search_issuers by specifying the focus on related persons.

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?

The description provides a clear use case ('mapping repeat founders and fund managers') and implies when to use it. However, it does not explicitly exclude alternatives or state when not to use it, leaving some guidance for the agent to infer.

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
Disambiguation2/5

Many tools have overlapping purposes, e.g., ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded all route questions to data sources with minor differences. Form D tools and meta-tools (discover_tools, suggest_questions) further blur boundaries, making it hard for an agent to select the right tool.

Naming Consistency4/5

Most tools follow a consistent snake_case verb_noun pattern (e.g., resolve_entity, validate_claim, subscribe). However, there are minor deviations like bet_research and deep_research without clear verbs, and the ask_pipeworx variants use irregular suffixes.

Tool Count2/5

With 39 tools, the server is over-scoped, including many utility and meta-tools (remember, recall, forget, list_subscriptions) that inflate the count beyond the core domain (SEC Form D and data lookups). A more focused set of 10-15 tools would be more coherent.

Completeness4/5

The tool set covers a very broad range of data sources and actions, including SEC filings, prediction markets, entity profiling, and AI visibility. However, the completeness is uneven; for example, there are many Form D tools but few for other SEC forms, and some areas like weather or clinical trials are only accessible via ask_pipeworx.

Resources