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Glama

Arcgis Durham

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 readOnly and idempotent. The description adds behavioral details beyond annotations: fans out to multiple sources, GDELT preferred with GNews fallback on rate limits/5xx, USPTO soft-fail, and `since` date formats. No contradiction found.

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?

Description is detailed but information-dense, covering query examples, source fan-out, parameter syntax, return shape, and sibling alternative. Slightly long but every sentence adds value for a multi-source tool.

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?

No output schema exists, so the description must explain return values—and it does: structured changes[] grouped by source, total_changes count, and citation URIs. It also covers sources, fallback, time syntax, and sibling differentiation, making it fully self-contained for tool selection.

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 covers all parameters with descriptions (100% coverage), but the description adds concrete examples for `since` (ISO date vs relative shorthand) and clarifies `value` accepts ticker or CIK. This enriches schema semantics beyond the structured definitions.

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?

Description clearly states the tool provides a change feed for a company over a time window, with specific query examples. It explicitly distinguishes from entity_profile, making the purpose unambiguous and well-differentiated from siblings.

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?

Provides explicit usage scenarios ('What's new with X') and explicitly directs users to entity_profile for static profiles. It also explains fallback behavior (GDELT→GNews, USPTO soft-fail), adding practical guidance for when to use 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

A3.8/5.0
Disambiguation2/5

Several tools have heavily overlapping purposes: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are near-identical entry points, and the polymarket family plus bet_research blur together. The three ArcGIS tools are distinct, but they are drowned out by a large set of overlapping data-research and prediction-market tools.

Naming Consistency3/5

There are clear naming families (ask_pipeworx*, polymarket_*, subscribe/unsubscribe) but overall conventions are mixed: verb_noun, noun_phrase, and domain-prefix styles all appear together. Everything uses snake_case, so it is still readable, but the pattern is not predictable across the full set.

Tool Count2/5

34 tools is a heavy surface, and the vast majority have nothing to do with the server's apparent ArcGIS Durham purpose—only search_datasets, query_layer, and layer_info are relevant. The count feels like a general-purpose data platform bolted onto a small GIS server rather than a well-scoped tool set.

Completeness2/5

For the implied ArcGIS Durham domain, the surface is thin: discover, schema, and query cover basic read-only geospatial access but omit broader GIS capabilities. For the much larger Pipeworx-looking surface, the completeness is hard to assess because the tools span unrelated domains without a coherent ArcGIS story.

Resources