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Glama

Sec Form D

by io.github.pipeworx-io

Form D Search Issuers

form_d_search_issuers
Read-onlyIdempotent

Search live SEC Form D filings by issuer, executive, fund, or other filing text and return normalized offering notices. Useful for private-company financing diligence and VC market scans. Results are notices, not independently verified closed rounds.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoResults to hydrate (1-10, default 5).
queryYesIssuer, person, fund, or filing text to search.
sinceNoStart filing date YYYY-MM-DD. Default 5 years ago.
untilNoEnd filing date YYYY-MM-DD. Default today.

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

A4.2/5.0
Behavior4/5

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

Annotations already declare the tool as read-only, idempotent, and non-destructive. The description adds that it searches 'live' filings and returns notices (not verified rounds), which provides useful nuance without contradicting annotations.

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 long with a trailing caveat, all front-loaded and free of extraneous information. Every sentence serves a purpose.

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?

Given the presence of an output schema and rich annotations, the description effectively covers the tool's purpose, data source, use case, and a data quality warning. Minor omissions (e.g., pagination, sorting) are acceptable given the schema coverage.

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?

All parameters are described in the schema (100% coverage). The description adds context for the 'query' parameter (searchable types) and mentions default for 'since'. This adds modest value beyond the schema, leading to a baseline-appropriate score of 3.

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 verb 'search' and the resource 'live SEC Form D filings', specifying the searchable entities (issuer, executive, fund, filing text) and the output (normalized offering notices). It distinguishes from sibling tools that focus on specific filings or history.

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 usage context ('private-company financing diligence and VC market scans') and a caveat about the data's verification status. However, it does not explicitly contrast with sibling tools or state when not to use it, which is a minor gap.

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