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Glama

Soilgrids

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

A4.9/5.0
Behavior5/5

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

Annotations already indicate readOnlyHint and idempotentHint. The description adds context on data sources, fallback, and API sunset (PatentsView soft-fail). 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?

A single dense paragraph front-loaded with typical queries, then covers fallback, parameter notes, and sibling comparison without wasted words. Efficient and well-structured.

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?

Given 3 required parameters, high schema coverage, and no output schema, the description covers return structure (changes grouped, total_changes, URIs) and explicitly states only 'company' type is supported. Completes the picture.

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% and descriptions are already detailed. The description adds value with examples of 'since' formats (ISO vs relative) and explains that 'value' accepts ticker or CIK. This goes beyond baseline.

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 gets a change feed for a company (SEC filings, news, patents) in a time window. It distinguishes from the sibling entity_profile by explicitly noting when to use the static profile instead.

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 example queries, fallback behavior (GDELT to GNews), and when-not-to-use (use entity_profile for static profile). This gives clear guidance on when to invoke this tool vs alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Soilgrids toolsInspect
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TDQS

A3.7/5.0
Disambiguation2/5

Multiple tools have overlapping purposes: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all serve similar question-answering roles. The soil-specific tools are distinct but mixed with many general tools, causing confusion.

Naming Consistency2/5

Naming conventions are inconsistent: some tools use snake_case (ask_pipeworx, list_soil_properties), others are compound nouns (suggest_questions, deep_research), and there is no uniform pattern like verb_noun across the set.

Tool Count3/5

With 34 tools, the count is high but might be justified for a broad platform. However, the server name 'Soilgrids' suggests a focused soil data service, making the count feel excessive and unfocused.

Completeness3/5

For soil data, the three dedicated tools (list_soil_properties, soil_classification, soil_properties) cover basic needs but lack advanced queries. The general tools are extensive but introduce many gaps unrelated to soil, so overall completeness for the server's stated purpose is mediocre.

Resources