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Glama

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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

A4.9/5.0
Behavior5/5

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

Annotations already declare readOnly/openWorld/idempotent, and the description adds valuable behavioral context: source-specific fallback mechanics, a USPTO soft-fail due to PatentsView sunset, and the return structure (changes[], total_changes, pipeworx:// citation URIs). No contradiction with 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 yet well-structured: it front-loads trigger phrases, then explains sources, supported formats, return values, and alternatives. Every sentence earns its place, with no filler 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?

Despite having no output schema, the description specifies return grouping, total count, and citation URIs, plus fallback and sunset behavior. It covers the complexity of a multi-source fan-out and gives an explicit alternative for static profiles, making it sufficient for a complex tool.

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%, so the schema already documents all three params. The description adds practical guidance (relative shorthand examples, 'Use 30d or 1m for typical monitoring', ticker vs CIK) that enriches schema understanding without fundamentally transforming it.

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 identifies a change-feed tool for companies over a date window, with natural-language triggers and explicit fan-out to SEC EDGAR, GDELT/GNews, and USPTO. It distinguishes itself from the sibling entity_profile tool by contrasting dynamic changes with a static 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?

It provides explicit when-to-use signals via example queries ('What's new...') and a direct alternative: 'Use entity_profile instead when you want the static profile...' It also documents fallback behavior (GDELT→GNews) and accepted input formats, giving clear invocation guidance.

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
Disambiguation2/5

The ask_pipeworx/ask_pipeworx_beta/ask_pipeworx_grounded trio are three variants of the same router — and the beta variant is explicitly stated to be identical to the stable one right now, making mis-selection nearly inevitable. The six polymarket tools (bet_research, polymarket_edges, polymarket_arbitrage, polymarket_fill_risk, polymarket_edge_tracker, polymarket_kalshi_spread) also have subtly overlapping boundaries where an agent could easily grab the wrong one.

Naming Consistency4/5

Nearly all tools use snake_case with a clear verb_noun or noun_compound shape (get_company_facts, resolve_entity, recent_changes, polymarket_edges). Minor deviations: the bare-verb memory trio (remember/recall/forget), the brand-style ask_pipeworx* naming, and a mix of verb-first vs. entity-first ordering, but the overall pattern is readable and predictable.

Tool Count3/5

34 tools is well above the typical well-scoped range, but the server's actual scope is enormous — a universal structured-data gateway, prediction-market suite, memory system, subscription system, and utility tools. However, the count feels inflated by genuine redundancy: ask_pipeworx_beta currently duplicates ask_pipeworx, and the polymarket cluster could plausibly be consolidated into fewer tools.

Completeness4/5

Each sub-domain has strong lifecycle coverage: entity resolution (resolve_entity, search_companies), company analysis (get_company_facts/filings, entity_profile, recent_changes, compare_entities), full CRUD for both memory and subscriptions, and an exhaustively covered prediction-market domain (research, edges, arb, fill risk, tracking, cross-venue). Minor gaps exist — there's no direct single-filing document fetch tool (search_within implies fetching via the gateway but no explicit getter), and the AI-visibility tools lack historical tracking — but these are workaround-able rather than blocking.

Resources