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Glama

Data Baltimore

by io.github.pipeworx-io

Baltimore Query

baltimore_query
Read-onlyIdempotent

Query any Baltimore ArcGIS layer by service path + layer id. Full ArcGIS query: where, out_fields, order_by, limit. Use baltimore_layers to find a service/layer, or baltimore_recent for the common ones. Epoch dates are converted to ISO.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
layerYesLayer id within the service (from baltimore_layers), e.g. 39.
limitNoMax rows (default 100, max 2000).
whereNoArcGIS SQL where (default "1=1").
serviceYesArcGIS service path, e.g. "311_Customer_Service_Requests_current/FeatureServer" (or a short name: crime|service_requests|permits).
order_byNoSort clause, e.g. "CreatedDate DESC".
out_fieldsNoComma-separated fields, or "*" (default).

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "layer": 0,
+    "limit": 100,
+    "order_by": "CreatedDate DESC",
+    "service": "crime",
+    "where": "OFFENSE='HOMICIDE'"
+  },
+  {
+    "layer": 39,
+    "limit": 200,
+    "out_fields": "RequestID,CreatedDate,ServiceCode",
+    "service": "311_Customer_Service_Requests_current/FeatureServer"
+  }
+]
  2. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already mark the tool as read-only and idempotent. The description adds a non-obvious behavior ('Epoch dates are converted to ISO'), which provides useful transparency beyond structured fields. No contradictions are present.

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 extremely concise with two sentences. The first sentence front-loads the core purpose and parameters. Every sentence adds value without redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with 6 parameters and no output schema, the description covers the primary use case, alternative tools, and a notable behavior. It is missing details about return format or error handling, but is adequate given the complexity.

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?

Input schema coverage is 100% with descriptions for all 6 parameters. The description mentions the key parameters but does not add significant semantic value beyond the schema. The note about date conversion is output-related, not input-specific.

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 verb 'Query' and the resource 'any Baltimore ArcGIS layer'. It lists key parameters (where, out_fields, order_by, limit) and distinguishes from siblings by referencing baltimore_layers and baltimore_recent as alternatives for discovery.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

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

The description explicitly tells the user to use baltimore_layers or baltimore_recent to find the correct service/layer, providing clear alternative guidance. It does not explicitly state when not to use this tool, but the context is sufficient for an agent.

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

A4.1/5.0
Disambiguation2/5

Several tool groups overlap heavily: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all route questions to the same catalog; entity_profile, recent_changes, and compare_entities cover overlapping company-data territory; ai_visibility_check and scan_competitor_ai_presence are near-duplicates. Agents would frequently need to read long descriptions to pick the right tool.

Naming Consistency4/5

All tool names use snake_case and mostly follow verb_noun patterns (ask_pipeworx, compare_entities, resolve_entity, validate_claim). Minor inconsistencies exist: generic noun-only names like entity_profile, recent_changes, and bet_research, plus inconsistent prefixes (ask_, baltimore_, polymarket_, pipeworx_, scan_) that group by domain rather than action.

Tool Count3/5

34 tools is on the heavy side for a data-access server, though the scope is broad. Several tools feel tangential to the core data mission (remember/recall/forget, generate_llms_txt, pipeworx_feedback, pipeworx_trending), and the ask_pipeworx family plus the six polymarket_* tools inflate the count with overlapping functionality.

Completeness4/5

The surface covers the domain well: discovery (discover_tools, suggest_questions, baltimore_layers), lookup (ask_pipeworx, baltimore_query/recent), grounded verification (ask_pipeworx_grounded, validate_claim), comparison (compare_entities), profiling (entity_profile), change tracking (recent_changes), and prediction-market analysis. Minor gaps include no direct web search and no Baltimore-specific export/bulk operations, but agents can work around these.

Resources