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Glama

Bart

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

A4.8/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint. The description adds richer behavioral context: fans out to multiple data sources (SEC, GDELT→GNews, USPTO), describes fallback logic (GNews when rate-limited), and notes soft-fail for USPTO. 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.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, well-organized paragraph. It front-loads purpose with examples, details sources and fallbacks, explains parameters and return structure, and ends with sibling guidance. Every sentence adds value with no 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?

Despite no output schema, the description clearly states the return format: 'structured changes[] grouped by source + total_changes count + pipeworx:// citation URIs'. It covers inputs, sources, fallbacks, and output, leaving no critical gaps.

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 value by explaining the 'since' parameter formats (ISO date, relative shorthand like '7d', '30d'), providing usage recommendations ('Use "30d" or "1m" for typical monitoring'), and clarifying that 'value' can be ticker or CIK.

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 starts with concrete query examples ('What's new with X'), then states 'change feed for a company in the last N days/weeks/months in ONE parallel call', clearly defining the tool's purpose and scope. It also distinguishes from sibling 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 Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides explicit guidance on when to use this tool vs entity_profile: 'Use entity_profile instead when you want the static profile...'. It also gives example queries but does not exhaustively list when not to use.

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

A4/5.0
Disambiguation4/5

Most tools have clearly distinct purposes, but the three ask_pipeworx variants (stable, beta, grounded) overlap significantly in functionality, as do the Polymarket tools (bet_research, arbitrage, edges, etc.), which could cause an agent to misselect without careful reading of descriptions.

Naming Consistency3/5

Naming follows multiple styles: verb_noun (ask_pipeworx, compare_entities), domain first (polymarket_arbitrage, bart_departures), and single words (remember, forget). There is no consistent pattern, making the set feel disjointed.

Tool Count3/5

35 tools is on the heavy side for a single server. While each tool has a defined role, the count suggests potential for consolidation (e.g., merging ask_pipeworx variants or Polymarket tools). The server's broad scope partially justifies the count.

Completeness4/5

The tool surface covers a wide range of functionalities: structured querying, entity lookup, comparison, fact-checking, subscription management, memory, and domain-specific tools for BART and Polymarket. Minor gaps exist (e.g., no direct API for some data sources), but overall it feels comprehensive.

Resources