stl-transit

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stl_rt_decode

Read-onlyIdempotent

Decode a stored GTFS-Realtime snapshot into normalized JSON, preserving unknown fields under '_unknown' to avoid silent data loss.

Instructions

Decode a stored GTFS-Realtime snapshot into normalized JSON.

Fields present in the bytes but absent from the schema map are preserved under '_unknown' rather than dropped, because silently discarding fields is how you ship a decoder that is wrong in ways nobody notices.

Args: entity: 'trip_updates', 'vehicle_positions', or 'alerts'.

Input Schema

TableJSON Schema

Name	Required	Default
`limit`	No
`entity`	No	trip_updates
`snapshot`	No

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 7, 2026

TDQS

B3.4/5.0

Behavior3/5

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

The annotations already indicate read-only, idempotent, and non-destructive behavior, and the description aligns with those hints. It adds useful detail that unknown fields are preserved under '_unknown', but it does not describe output structure or error behavior, though an output schema exists.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is reasonably concise and front-loads the main purpose. The explanatory clause about silently discarding fields is slightly verbose but supports the stated behavior.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description is not complete enough given the three optional parameters and a schema with no descriptions. It omits explanations for 'limit' and 'snapshot', and does not address how the output normalizes data beyond the '_unknown' note, leaving an agent to guess at important inputs.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description mentions only the 'entity' parameter and its allowed values; 'limit' and 'snapshot' are not explained. Since the input schema has no parameter descriptions, the description fails to compensate for the missing semantics of two of the three parameters.

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 that the tool decodes a stored GTFS-Realtime snapshot into normalized JSON, with a specific verb, resource, and output format. It also calls out the entity types accepted, making the purpose unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies the appropriate use case—when a stored GTFS-Realtime snapshot needs to be decoded to normalized JSON—but it does not explicitly compare this tool with sibling tools such as stl_rt_wire or stl_rt_reference. There is no when-not-to-use guidance.

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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