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Glama

Wynncraft

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

A4.6/5.0
Behavior4/5

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

Annotations already declare readOnly, openWorld, idempotent, non-destructive. The description adds parallel API calls, fallback logic, and USAPTO sunset context, which exceed annotation requirements. No contradictions.

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, starting with examples and clear function. Every sentence serves a purpose, though slightly verbose. Could be tightened but still effective.

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?

For a complex multi-source tool with no output schema, the description adequately covers return structure (grouped changes, total count, citation URIs) and important limitations (USPTO sunset, fallback). No missing critical context.

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 coverage is 100% with good descriptions. The tool description adds examples and clarifies acceptable formats for 'since', and notes 'type' is currently limited to 'company', adding value beyond schema.

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, listing sources (SEC EDGAR, GDELT/GNews, USPTO) and inputs. It distinguishes from sibling tool 'entity_profile' by specifying when to use each, making the purpose unmistakable.

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 explicitly tells when to use this tool vs 'entity_profile' and explains fallback behavior (GDELT to GNews, USPTO soft-fail). It also provides guidance on 'since' format, including typical monitoring usage ('30d' or '1m').

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

B3.1/5.0
Disambiguation2/5

The set is split between Wynncraft game data tools and a large Pipeworx data cluster, and within the Pipeworx cluster there is heavy overlap: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are near-identical (the beta is currently identical), ai_visibility_check and scan_competitor_ai_presence do essentially the same thing at different granularities, and six polymarket_* tools cover overlapping prediction-market functionality. An agent would frequently struggle to choose the right tool.

Naming Consistency3/5

Snake_case with a mostly verb_noun pattern dominates (ask_pipeworx, compare_entities, resolve_entity, validate_claim), and families like polymarket_* and pipeworx_* are internally consistent. However, there is a notable mix of noun-only tools (guild, item_database, leaderboard, player, news) and the server is named Wynncraft while the majority of tools are Pipeworx-branded, which breaks overall coherence.

Tool Count2/5

40 tools is well beyond the borderline range, and the count is inflated by redundancy: multiple ask_pipeworx variants, several overlapping polymarket tools, a memory trio, and subscription management that arguably belong to a separate server. The Wynncraft portion alone would be nicely scoped (~9 tools), but the merged surface feels heavy and unfocused.

Completeness4/5

The Wynncraft side offers solid read coverage of players, guilds, items, leaderboards, news, and online status, which is appropriate for the domain. The Pipeworx side covers lookup, grounded verification, comparison, research, prediction markets, subscriptions, memory, and feedback, leaving few obvious dead ends for the stated meta-purposes.

Resources