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Glama

Fcc Regulations

by io.github.pipeworx-io

Recent Changes

recent_changes
Read-onlyIdempotent

"What's new with X" / "latest on Y" / "what happened to Z this week / month / quarter" / "updates on Acme" / "news on Tesla recently" / "what's happening with Apple" — change feed for a company in the last N days/weeks/months in ONE parallel call. Fans out to SEC EDGAR (filings since since), GDELT→GNews fallback (news mentions in window — GDELT preferred, GNews when rate-limited or 5xx), USPTO (patents granted; PatentsView API sunset May 2025 so this soft-fails until reactivated). since accepts ISO date ("2026-04-01") or relative shorthand ("7d", "30d", "3m", "1y"). Returns structured changes[] grouped by source + total_changes count + pipeworx:// citation URIs. Use entity_profile instead when you want the static profile (filings + fundamentals + LEI + patents) regardless of window.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeYesEntity type. Only "company" supported today.
sinceYesWindow start — ISO date ("2026-04-01") or relative ("7d", "30d", "3m", "1y"). Use "30d" or "1m" for typical monitoring.
valueYesTicker (e.g., "AAPL") or zero-padded CIK (e.g., "0000320193").

Schema Changelog

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

  1. First observed

TDQS

A4.9/5.0
Behavior5/5

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

Beyond annotations (readOnly, idempotent, openWorld), the description details external API calls, fallback logic, and API status (USPTO/PatentsView sunset). This adds critical behavioral context the agent needs.

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 compact, front-loaded with natural language examples, and efficiently covers purpose, sources, parameters, and output. Every sentence provides necessary information without redundancy.

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 (multiple sources, fallback, date parsing), the description fully specifies behavior, input, and output. It also addresses edge cases (USPTO soft-failure) and distinguishes from sibling tools.

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 already covers all parameters (100% coverage). The description adds value by explaining the 'since' format in detail (ISO date vs relative shorthand) and providing a typical usage tip ('30d' or '1m').

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 provides a 'change feed for a company' using multiple sources (SEC, GDELT, GNews, USPTO). It distinguishes itself from the sibling tool 'entity_profile' which is for static profiles, thereby setting clear boundaries.

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?

Explicitly guides when to use this tool for 'what's new' queries and when to use 'entity_profile' instead. It also describes the fallback mechanism (GDELT preferred, GNews on rate limit) and explains input format options.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Fcc Regulations toolsInspect
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TDQS

A3.6/5.0
Disambiguation2/5

Several tool clusters have poorly defined boundaries: ask_pipeworx and ask_pipeworx_beta are currently functionally identical, the five polymarket tools all orbit 'find/validate trading edges', and ai_visibility_check overlaps heavily with scan_competitor_ai_presence. The memory and subscription tools are distinct, but the core query/edge clusters would cause frequent misselection.

Naming Consistency2/5

Naming conventions are mixed across the set: the ask_pipeworx* family uses verb+product, the polymarket_* family uses domain-prefixed nouns, fcc_regulation and fcc_regulations_search differ in singular/plural and lack a verb, and tools like discover_tools, entity_profile, and generate_llms_txt each follow different patterns. No single predictable convention holds across the server.

Tool Count2/5

33 tools is heavy on its own, but the count is especially inappropriate given the server is named 'Fcc Regulations': only 2 of the 33 tools actually serve FCC regulatory text, while the other 31 tools belong to a general-purpose Pipeworx data-query platform. The set is far too broad for the declared scope.

Completeness2/5

For the stated FCC-regulations purpose, the two relevant tools cover search and full-text retrieval, but there is no change tracking, no notification of rule updates, no historical/version comparison, and no adjacent FCC filings/licensing data despite the server name implying broader FCC coverage. The extra 31 unrelated tools do not fill these gaps, so an agent expecting FCC completeness would hit dead ends.

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