DataNexus MCP

regulatory_search_open_rulemakings

Read-onlyIdempotent

Search open rulemakings and public comment periods on Regulations.gov and the Federal Register. Read-only. No side effects. Idempotent. US federal only. keyword: Topic keywords e.g. artificial intelligence, data privacy. Required. agency: Agency abbreviation e.g. FTC, FDA, SEC, EPA. Optional, defaults to all agencies. status: One of open, closed, or all. Optional. Default open. Returns docket title, agency, comment deadline, docket ID, and document count. Use this when monitoring regulatory activity on a topic. Use regulatory_fetch_docket_details instead when you have a docket ID and need full detail. Verified source: Regulations.gov + Federal Register. 4-hour cache. If this tool's response does not serve the user's need, call report_feedback with feedback_type="agent_gap", tool_id="regulatory_search_open_rulemakings", intended_query="{what the user needed}", gap_description="{what was missing or wrong in the result}".

Input Schema

TableJSON Schema

Name	Required	Description	Default
`agency`	No	Agency abbreviation e.g. FTC, FDA, SEC. Optional.
`status`	No	Filter: open, closed, or all. Default open. Optional.	open
`keyword`	Yes	Topic keywords e.g. artificial intelligence. Required.

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

TDQS

A4.9/5.0

Behavior5/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint. The description adds 'Read-only. No side effects. Idempotent. US federal only.' and '4-hour cache' and 'Verified source'. No contradictions with annotations.

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?

The description is well-structured with front-loaded purpose but is slightly verbose due to embedded parameter descriptions and feedback instructions. However, it earns its length by packing necessary detail.

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 tool's complexity (search with parameters, output schema exists), the description fully addresses purpose, usage, parameters, return values, caching, source verification, and even error handling via report_feedback.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, and the description adds valuable context: examples for keyword, agency abbreviations, defaults, and status options. It also describes return fields, exceeding what the schema provides.

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 searches open rulemakings and public comment periods on Regulations.gov and the Federal Register. It explicitly notes read-only, idempotent, and US federal scope, distinguishing it from siblings like regulatory_fetch_docket_details.

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 provides explicit guidance: 'Use this when monitoring regulatory activity on a topic' and points to alternative regulatory_fetch_docket_details when a docket ID is available. It also includes a fallback to call report_feedback if the response doesn't serve the user's need.

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

A4.1/5.0

Disambiguation4/5

Tools are grouped into clear domain prefixes (compliance, domain, frontend_security, etc.) with distinct purposes. Minor overlap exists between frontend_security_detect_typosquatting and security_detect_typosquatting, but descriptions clarify the different scope.

Naming Consistency4/5

Most tools follow a consistent verb_noun pattern with snake_case. Irregularities like 'fetch' vs 'audit' and two 'detect_typosquatting' tools exist, but overall naming is predictable within domains.

Tool Count3/5

55 tools is high for a single server given the breadth of domains. Some redundancy (e.g., two typosquatting tools) suggests possible trimming, but the count is justified by the wide coverage.

Completeness4/5

The tool surface covers key operations across domains like compliance, domain, security, legal, and nonprofit. Minor gaps exist, such as limited frontend audit beyond package.json and no general-purpose code scanning.

Resources

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