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Glama

Noaa Swpc

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, idempotent, openWorld), the description discloses significant behavior: parallel fan-out across sources, GDELT→GNews fallback under rate limiting/5xx, USPTO soft-fail until reactivation, and the return structure (changes[], total_changes, citation URIs). No contradictions 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.

Conciseness4/5

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

The description is dense but every sentence carries useful information. It is somewhat run-on, but front-loaded with user intents and then systematically covers sources, parameters, and output. No fluff; length is justified by the tool's complexity.

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 is exceptionally complete. It explains return format, fallback behavior, soft-failures, and parameter formats, and points to the alternative tool. This is enough 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 description coverage is 100%, so the schema already documents each parameter. The description adds minimal extra semantic value — mostly redundant examples ('2026-04-01', '7d') and a recommendation ('30d' or '1m'), but does not fundamentally enrich the parameter understanding beyond what the schema provides.

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's purpose: a change feed for a company over a recent time window, with specific data sources (SEC, GDELT/GNews, USPTO). It uses a specific verb ('fans out') and resource ('change feed for a company'), and distinguishes from its 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 Guidelines5/5

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

The description opens with concrete query phrasings ('What's new with X', 'latest on Y') and explicitly directs users to entity_profile when a static profile is needed. It also clarifies the typical window usage ('Use 30d or 1m'). This gives clear when-to-use vs. alternative 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

B3.3/5.0
Disambiguation2/5

Several tool clusters heavily overlap: multiple ask_pipeworx variants, five polymarket_* tools, and company-research tools (entity_profile, compare_entities, recent_changes) all have similar purposes. An agent would frequently need to read long descriptions to distinguish between them, and some boundaries remain unclear.

Naming Consistency2/5

Naming mixes verb-first styles (ask_pipeworx, list_subscriptions, subscribe) with noun-only names (kp_index, solar_wind, alerts), and disjointed prefixed families (polymarket_*, pipeworx_*). There is no uniform verb_noun or other consistent convention across the set.

Tool Count2/5

38 tools is well above the typical well-scoped range, especially for a server ostensibly dedicated to NOAA space weather. The count feels bloated, with many tools unrelated to the server's stated purpose.

Completeness2/5

The server name implies space-weather coverage, and that domain has only a handful of tools (alerts, kp_index, solar_wind, etc.), leaving gaps (no proton flux, no Dst index). Meanwhile, the extensive non-space-weather tools are over-provisioned and their inclusion makes the overall surface incoherent and impossible to navigate as a complete domain.

Resources