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Septa

by io.github.pipeworx-io
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Septa Next To Arrive

septa_next_to_arrive
Read-onlyIdempotent

Next SEPTA Regional Rail trains from an origin station to a destination station in Philly — direct trains and connecting itineraries (with transfer station), departure/arrival times, and live delay status. Answers "when is the next train from X to Y" in Philadelphia. Example: septa_next_to_arrive({ orig: "Suburban Station", dest: "Airport Terminal B", n: 3 })

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nNoHow many upcoming trains to return (default 3, max 10)
destYesDestination Regional Rail station, e.g. "Airport Terminal B", "Ardmore" (fuzzy-matched)
origYesOrigin Regional Rail station, e.g. "Suburban Station", "Fox Chase" (fuzzy-matched)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "dest": "Airport Terminal B",
+    "orig": "Suburban Station"
+  },
+  {
+    "dest": "Ardmore",
+    "n": 5,
+    "orig": "Fox Chase"
+  }
+]
  2. First observed

TDQS

A4.7/5.0
Behavior5/5

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

Annotations indicate read-only, idempotent, open-world, non-destructive. The description adds valuable behavioral context: 'direct trains and connecting itineraries (with transfer station), departure/arrival times, live delay status', and notes fuzzy matching for station names. This goes well beyond the annotations, fully disclosing what the tool does and its capabilities.

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 only two sentences plus an example, with no wasted words. It front-loads the core functionality and immediately gives a concrete usage example. Every sentence earns its place, making it highly efficient for an agent to parse.

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?

Given the tool's complexity (querying schedule and live status with transfers), the description covers all essential aspects: what it does, how to use it (example), key parameters, and behavior (fuzzy matching, live delay). There is no output schema, so the description adequately informs the agent about the return content without needing excessive detail.

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?

Input schema covers 100% parameter descriptions, so the baseline is 3. The description adds context by including an example with specific station names and explaining fuzzy matching, which helps the agent understand parameter values. It also notes the default for 'n' (3). This adds meaningful guidance 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 purpose: 'Next SEPTA Regional Rail trains from an origin station to a destination station in Philly — direct trains and connecting itineraries (with transfer station), departure/arrival times, and live delay status.' It distinguishes itself from sibling tools like septa_alerts and septa_train_view by focusing on the 'next to arrive' functionality and includes an example call.

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 answers 'when is the next train from X to Y in Philadelphia' and includes a concrete example. It implies usage for Regional Rail queries but does not explicitly state when not to use it or mention alternative tools for other transit modes (e.g., buses). The guidance is clear but could be more specific about exclusions.

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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