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Predicthq

by io.github.pipeworx-io
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Nearby Events

nearby_events
Read-onlyIdempotent

Find PredictHQ events within a radius of a geographic point (latitude/longitude). Useful for "what is happening near this venue/store/airport" demand-forecasting queries. Filter by category and active-date window; results are ranked by predicted impact. Example: nearby_events({ latitude: 40.7128, longitude: -74.006, radius: "10km", category: "concerts,sports" }).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
endNoOnly include events active on or before this date (YYYY-MM-DD), e.g. "2026-06-30".
limitNoMax events to return (default 15, max 50).
startNoOnly include events active on or after this date (YYYY-MM-DD), e.g. "2026-06-01".
radiusNoSearch radius with unit, e.g. "10km", "5mi" (default "10km").
_apiKeyNoREQUIRED — your own PredictHQ access token. Pipeworx does not front a key for PredictHQ (14-day trial, then sales contact). Free keyless alternatives for event listings: ticketmaster, seatgeek.
categoryNoComma-separated event categories. One or more of: concerts, sports, conferences, expos, festivals, performing-arts, community, public-holidays, observances, politics, academic, school-holidays, daylight-savings, severe-weather, airport-delays, disasters, terror, health-warnings. Example: "concerts,sports".
latitudeYesCenter latitude in decimal degrees, e.g. 40.7128.
longitudeYesCenter longitude in decimal degrees, e.g. -74.006.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / _apiKey / description
      Previous value: -"Optional — your own PredictHQ access token for your own quota; omit to use the shared Pipeworx platform key."New value: +"REQUIRED — your own PredictHQ access token. Pipeworx does not front a key for PredictHQ (14-day trial, then sales contact). Free keyless alternatives for event listings: ticketmaster, seatgeek."
  2. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "_apiKey": "your-predicthq-api-key",
+    "category": "concerts,sports",
+    "latitude": 40.7128,
+    "longitude": -74.006,
+    "radius": "10km"
+  },
+  {
+    "_apiKey": "your-predicthq-api-key",
+    "end": "2026-08-31",
+    "latitude": -33.8688,
+    "longitude": 151.2093,
+    "radius": "5mi",
+    "start": "2026-07-01"
+  }
+]
  3. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false. The description adds meaningful behavioral context beyond these flags: results are 'ranked by predicted impact' and support filtering by category and active-date window, which helps the agent know what to expect. 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?

The description is three sentences plus an example, with no extraneous words. It front-loads the core purpose, then gives the use case, then behavioral details and a concrete invocation example. Every sentence earns its place.

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?

Given the 8-parameter schema with full descriptions and rich annotations, the description is complete enough: it explains what the tool does, when to use it, how filtering/ranking works, and provides an example. It does not describe the return format (no output schema), but for an event-search tool with siblings, this is not a significant gap.

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 coverage is 100% with detailed descriptions for all 8 parameters, so the baseline is 3. The description's example shows parameter syntax (e.g., radius: '10km', category: 'concerts,sports') but does not add semantic meaning beyond what the schema already provides.

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 a specific verb and resource: 'Find PredictHQ events within a radius of a geographic point.' It clearly distinguishes from sibling tools like search_events by emphasizing the proximity/location scope, and reinforces with a concrete use case for demand forecasting.

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 a clear usage context: 'useful for "what is happening near this venue/store/airport" demand-forecasting queries.' However, it does not explicitly name when not to use it or mention alternatives (e.g., search_events) as exclusions, so it falls short of a full 5.

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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