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Glama

Zoom

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

A5/5.0
Behavior5/5

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

Describes fan-out to multiple data sources (SEC, GDELT/GNews, USPTO), fallback logic, and soft-fail for PatentsView. Adds context beyond annotations, which already indicate safety and idempotency.

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?

Single dense paragraph with no extraneous information. Front-loaded with example queries, then details on data sources and parameters.

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?

Complex tool with multiple sources and fallbacks; description covers input patterns, parameter details, output structure (grouped changes with citation URIs), and links to sibling tool. No output schema present, but return format is adequately described.

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 description adds explanations for 'since' formats, constraints on 'type', and value examples. No ambiguity remains.

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 recent window, with explicit example queries. It distinguishes itself from the sibling tool 'entity_profile'.

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 explicit when-to-use guidance by contrasting with 'entity_profile' for static profiles, and explains fallback behavior. Examples help the agent select correct parameters.

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

All Zoom toolsInspect
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TDQS

A3.5/5.0
Disambiguation2/5

The set mixes two entirely different domains: 4 Zoom tools and 31 Pipeworx/prediction-market tools. Within the Pipeworx side, ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, discover_tools, and suggest_questions overlap heavily, as do the five polymarket_* tools. An agent could easily select the wrong variant despite the long descriptions.

Naming Consistency2/5

The Zoom tools follow a clean zoom_* pattern, and there are subfamilies like ask_pipeworx_* and polymarket_*, but the overall set is a mix of snake_case verbs, bare nouns, and inconsistent styles (bet_research, entity_profile, generate_llms_txt, list_subscriptions, pipeworx_feedback, validate_claim). No single predictable convention governs the server's tool names.

Tool Count2/5

35 tools is heavy for any server, and the vast majority are unrelated to the server's declared 'Zoom' purpose. Only 4 of 35 tools actually concern Zoom, making the count both bloated and mismatched. A focused Zoom server would need far fewer tools; a Pipeworx data server would need a different name.

Completeness2/5

For a Zoom server, the surface is critically incomplete: only read-only list/get operations exist for meetings, recordings, and the current user, with no create, update, delete, or invite functionality. The Pipeworx side is comparatively rich and complete, but that does not serve the Zoom domain implied by the server name, so significant gaps remain for the apparent purpose.

Resources