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Glama

timezone

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. Added

TDQS

A5/5.0
Behavior5/5

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

Discloses multi-source fan-out behavior (SEC, GDELT/GNews, USPTO), fallback logic (GDELT preferred, GNews on rate-limit/5xx), and the patent API sunset soft-fail. This goes well beyond the readOnly/idempotent 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 dense but every sentence carries valuable information: user query examples, source details, fallback behavior, parameter syntax, output format, and an alternative tool reference. No fluff or 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?

With no output schema, the description fully explains return structure (changes[], total_changes, citation URIs) and covers error/fallback scenarios. It provides sufficient context for a complex multi-source tool.

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%, but the description adds meaningful parameter context: provides examples for the 'since' parameter (ISO vs relative shorthand), recommends '30d'/'1m', and clarifies accepted value formats (ticker or CIK). This exceeds the baseline for high schema coverage.

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 over a time window, with examples of natural language queries. It explicitly distinguishes from sibling tool entity_profile, making its purpose unambiguous.

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?

Provides clear usage context through example queries and explicitly directs users to entity_profile for static profile needs, effectively differentiating when to use this tool vs an alternative.

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

A3.5/5.0
Disambiguation2/5

Many tools have overlapping purposes, especially the multiple 'ask_pipeworx' variants and several Polymarket utilities. The server mixes a few timezone tools with a large collection of unrelated data lookup and analysis tools, making it hard for an agent to distinguish which tool to use for a given task.

Naming Consistency2/5

While all tool names use snake_case, the verbs are highly inconsistent (e.g., 'ask_pipeworx', 'convert_time', 'discover_tools', 'validate_claim'). There is no clear pattern or predictable naming convention across the set.

Tool Count2/5

The server name 'timezone' suggests a narrow domain, but it contains 35 tools, the vast majority of which are unrelated to timezones. This is far too many for the implied scope, and the server seems to be a dumping ground for various services.

Completeness1/5

For a timezone server, only 4 tools (convert_time, get_time_by_ip, get_time_by_timezone, list_timezones) are relevant. Critical timezone functionality like time zone conversions with arbitrary offsets, DST handling, or time zone by coordinates is missing. The remaining tools are completely unrelated to the server's stated purpose.

Resources