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Glama

Box

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
Behavior5/5

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

Beyond the annotations (readOnly, openWorld, idempotent, non-destructive), it discloses the multi-source fan-out, fallback chain, USPTO soft-fail due to PatentsView API sunset, and the exact return structure (changes[] grouped by source + total_changes + citation URIs). No contradictions with the annotations.

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 dense but efficiently organized: query intents, fan-out behavior, parameter format, return format, and alternative tool. It could be slightly trimmed (six query examples are redundant), but every sentence serves a purpose and the structure is easy to scan.

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 multi-source, fallback-capable tool with no output schema, the description covers purpose, parameter formats, source behavior, and return values. It also addresses the one relevant sibling tool. Complete for an agent to select and invoke correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema covers 100% of parameters with detailed descriptions and examples. The description reiterates `since` relative shorthand and typical monitoring values, but adds no parameter-specific semantics beyond the schema. It does contextualize why the parameters matter (parallel call, source grouping) but offers no new meaning.

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 opens with multiple natural-language query examples and then states it provides a 'change feed for a company in the last N days/weeks/months in ONE parallel call.' It explicitly names the fan-out sources (SEC EDGAR, GDELT/GNews, USPTO) and distinguishes itself from sibling entity_profile by naming it directly.

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 advises 'Use entity_profile instead when you want the static profile (filings + fundamentals + LEI + patents) regardless of window.' It also gives clear use-case examples and documents fallback behavior (GDELT→GNews when rate-limited or 5xx), setting expectations for when and how to rely on this tool.

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

A3.9/5.0
Disambiguation4/5

Most tools have distinct purposes, aided by detailed descriptions (e.g., ask_pipeworx vs. ask_pipeworx_grounded). However, some overlap exists among Pipeworx-based tools (compare_entities, entity_profile, recent_changes, validate_claim) that could cause confusion without careful reading.

Naming Consistency3/5

Snake_case is used, but naming patterns are mixed: some start with verbs (ask_pipeworx, validate_claim), others with nouns or prefixes (box_get_file, entity_profile). This inconsistency makes it harder to predict tool names.

Tool Count3/5

At 31 tools, the server covers an unusually broad set of domains (cloud storage, data queries, betting, memory, subscriptions). This is on the heavy side and could benefit from splitting into more focused servers.

Completeness3/5

Gaps exist: Box storage lacks create/update/delete, Polymarket tools offer analysis but no execution, and some data domains (e.g., weather) have only indirect coverage. The surface feels uneven across the wide scope.

Resources