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Glama

Arcgis Fairfield

by io.github.pipeworx-io

Recent Alerts

recent_alerts
Read-onlyIdempotent

Pull fired events from your subscription feed. Returns the most recent alerts the evaluator has written to your persisted feed — each carries source, citation_uri (pipeworx:// when available), and the raw event payload. Filter by type (e.g. "sec_8k") and/or since (ISO timestamp). Set mark_read:true to flag returned events read so the next call only shows newer ones. Polls work fine; the same feed is also at GET registry.pipeworx.io/alerts.json for scripts and dashboards.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNoOptional — filter to one subscription type.
limitNoMax events to return (1-200, default 50).
sinceNoOptional ISO timestamp — return events fired_at >= this time.
mark_readNoFlag the returned events read in the same call (default false).
unread_onlyNoReturn only events where read_at is null (default false).

Schema Changelog

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

  1. First observed

TDQS

A4.5/5.0
Behavior4/5

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

The description discloses the mark_read side-effect (flagging events read), which is beyond the readOnly annotation. It also explains the persisted feed and mentions that polling works fine, adding value beyond the annotations without contradicting them.

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 three sentences: purpose, filtering/state, and alternative access. It is front-loaded with the main action and contains no redundant information—every sentence earns its place.

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 adequately describes the return payload (source, citation_uri, raw event payload). It covers filtering, mark_read, polling, and the alternative endpoint, fully explaining the tool's behavior without needing further documentation.

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?

The schema already provides 100% coverage for all parameters, but the description adds a concrete type example ('sec_8k') and explains how mark_read affects subsequent calls. This goes beyond the schema's descriptions, making parameters more actionable.

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 opens with 'Pull fired events from your subscription feed,' which is a specific verb+resource. It clearly distinguishes from sibling tools like list_subscriptions by focusing on fired events rather than subscription management, and it specifies the return contents.

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 gives clear usage context: filtering options, mark_read behavior, and an alternative HTTP endpoint for scripts/dashboards. It doesn't explicitly name an alternative tool within the sibling list, but the guidance is sufficient for deciding 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

A3.5/5.0
Disambiguation2/5

Many tools have overlapping purposes, such as ask_pipeworx, ask_pipeworx_grounded, deep_research, and also multiple Polymarket tools (bet_research, polymarket_edges, polymarket_arbitrage). Descriptions try to differentiate but the boundaries are unclear, causing confusion.

Naming Consistency2/5

Naming conventions are mixed: some use snake_case (ask_pipeworx, query_layer), some use descriptive phrases (entity_profile, recent_changes), and there is no consistent verb_noun pattern. The variety makes it hard to predict tool names.

Tool Count1/5

33 tools is far too many for a server named 'Arcgis Fairfield', as most tools are unrelated to GIS or Fairfield (e.g., npm dependency checks, prediction markets, AI visibility). The tool count severely mismatches the server's purported scope.

Completeness1/5

The server's stated purpose is ArcGIS Fairfield, but only 3 tools (layer_info, query_layer, search_datasets) relate to that domain. Critical GIS operations like updating features or managing services are missing, while the vast majority of tools are for other domains.

Resources