layer_infoGet an ArcGIS Feature/Map Service layer's schema by url: fields (name + type), geometry type, total record count, and capabilities.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | Feature/Map Service layer url, e.g. ".../FeatureServer/0". |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and idempotentHint=true, so the safety profile is known. The description adds value by specifying the exact information returned (fields, geometry type, record count, capabilities), which gives the agent a clear picture of the tool's output. 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with every word earning its place. It immediately states the action and resource, then compactly lists the output. No fluff or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter read-only tool with strong annotations, the description is complete. It fully covers what the tool returns and the type of input expected. No output schema exists, but the description explicitly lists return components, so no ambiguity remains.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage with a well-described 'url' parameter and an example. The description adds no new parameter semantics beyond the schema, but the schema is fully sufficient. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a clear, specific verb+resource: 'Get an ArcGIS Feature/Map Service layer's schema by url.' It also enumerates what is returned (fields, geometry type, total record count, capabilities), distinguishing it from sibling tools like query_layer that retrieve data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly implies when to use the tool: when the schema or metadata of an ArcGIS layer is needed. It provides clear context without exclusions or explicit alternatives, but the purpose statement itself is sufficient for an agent to select this tool over data-querying siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Several tool groups overlap heavily: the three ask_pipeworx variants (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded) differ mainly in guarantees, and six Polymarket tools (bet_research, polymarket_arbitrage, polymarket_edges, polymarket_edge_tracker, polymarket_fill_risk, polymarket_kalshi_spread) all target the same trading-concept space with fuzzy boundaries. While ArcGIS, memory, and subscription tools are distinct, an agent will frequently struggle to pick the right research or analysis tool.
All names are snake_case, but the structural pattern is inconsistent. Some are verb-first (query_layer, search_datasets, validate_claim), others are noun-first or domain-prefixed (entity_profile, layer_info, polymarket_edges, recent_alerts, pipeworx_feedback). There is no predictable verb_noun convention across the set, making it hard to guess a tool's name from its function.
At 34 tools, the set is well above the typical focused-server range, and the server name 'Arcgis Eagan' suggests a narrow GIS purpose while only 3–4 tools are actually ArcGIS-related. The remaining ~30 tools form a broad, unrelated utility collection (Pipeworx data, memory, subscriptions, trending, npm scanning), making the count feel bloated and unfocused.
For the primary ArcGIS domain, only search, layer inspection, and querying are supported — there are no create, update, delete, or editing tools, leaving obvious lifecycle gaps. Meanwhile, the Pipeworx side is over-stocked with redundant analysis tools, and the overall mix lacks a coherent coverage story for any single stated purpose.