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Query Layer

query_layer
Read-onlyIdempotent

Query an ArcGIS Feature Service / Map Service layer by its url (from search_datasets). SQL-like where, comma-separated out_fields, order_by, limit, offset. Returns attribute rows (and geometry). Use where="1=1" + out_fields="*" to sample.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesFeature/Map Service layer url ending in /FeatureServer/<n> or /MapServer/<n>.
limitNoMax features (1-2000, default 50).
whereNoSQL where clause, e.g. "STATE = 'CA' AND YEAR >= 2020". Default "1=1".
offsetNoPagination offset.
order_byNoe.g. "POP DESC".
out_fieldsNoComma-separated field names, or "*" for all (default).

TDQS

A4.1/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true, so the safety profile is covered. The description adds that it 'Returns attribute rows (and geometry)' and gives a sampling tip, but does not disclose pagination behavior, response limits, or any potential external side effects. This is acceptable but not rich beyond the 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 two sentences, front-loaded with the core purpose, and includes a practical quick-start tip. Every sentence earns its place with no redundancy or fluff.

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?

With no output schema, the description appropriately explains the return type ('attribute rows (and geometry)'). It also provides enough context for typical usage, including the source of the URL, key parameters, and a sampling strategy. The tool's complexity is well-covered by the combination of description and schema.

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 baseline is 3. The description briefly restates parameter names and adds 'SQL-like' and 'comma-separated' semantics, but these are already implied in the schema descriptions. The sampling tip is a useful addition but does not significantly deepen parameter understanding beyond the schema.

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 function: 'Query an ArcGIS Feature Service / Map Service layer by its url'. It uses a specific verb (query) and resource (Feature/Map Service layer), and distinguishes itself from sibling tools like search_datasets and layer_info by focusing on data retrieval from a known layer URL.

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 provides clear usage context by indicating the URL comes 'from search_datasets', establishing a workflow prerequisite. It also offers a sampling tip ('Use where="1=1" + out_fields="*" to sample'). However, it does not explicitly mention alternatives or when not to use this tool, though the context is sufficiently clear.

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

A3.5/5.0
Disambiguation2/5

Multiple tools have overlapping purposes: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are nearly identical, and several Polymarket analysis tools (polymarket_arbitrage, polymarket_edges, polymarket_edge_tracker, polymarket_fill_risk, bet_research) blur together. The three ArcGIS tools are distinct, but they are drowned out by a large set of data-query and prediction-market tools with unclear boundaries.

Naming Consistency3/5

All tool names use snake_case, but the verb/noun pattern is mixed: some are command-style (query_layer, validate_claim), some are noun phrases (layer_info, entity_profile), and others are bare verbs (remember, forget). The naming is readable but not consistently patterned.

Tool Count2/5

34 tools is too many for a server named 'Arcgis Allegheny', especially since only three tools (search_datasets, layer_info, query_layer) relate to ArcGIS at all. The bulk of the tools address unrelated domains like Pipeworx data lookups and Polymarket betting, making the count excessive for the apparent purpose.

Completeness1/5

For a server focused on ArcGIS Allegheny County data, the surface is severely incomplete: only three read-only tools (search_datasets, layer_info, query_layer) cover the domain, and they lack operations like adding, updating, or deleting features. The remaining 31 tools are unrelated to GIS, so the server fails to provide a coherent or complete toolset for its stated purpose.