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chrischall

crowntowncompost-mcp

by chrischall

Get pickup schedule (days + time window)

crowntown_get_pickup_schedule
Read-onlyIdempotent

Retrieve pickup days, next service date, set-out time, and observed arrival window for each address. Uses recorded collection times to show typical arrival range.

Instructions

Get the pickup schedule for each service address: pickup day(s), next service date, the official set-out-by time, and an observed arrival-time window (earliest/latest/typical and whether it is consistent or varies) derived from the recorded collection times in your service history. Crown Town Compost publishes no guaranteed arrival window, so the observed window is empirical. Read-only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
history_sampleNoHow many recent stops to derive the observed time window from (max 100).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.6.0
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
  2. Addedv0.3.0

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, and idempotentHint, covering safety and non-mutating behavior. The description adds context about the lack of a guaranteed window from the provider and that the window is empirical, which is valuable for setting expectations. 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.

Conciseness4/5

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

The description is a single, information-dense paragraph. It front-loads the core output and then explains the empirical nature and read-only attribute. Slightly long but justified given the complexity of the observed window concept; no fluff.

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?

For a single-parameter, read-only tool with no output schema and full parameter schema coverage, the description covers what the tool returns, the empirical basis, and the absence of a guaranteed window. It lacks explicit detail on the return format (e.g., how the window is structured), but given the tool's simplicity and annotations, it is sufficiently complete for calling correctly.

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?

The only parameter, history_sample, is fully described in the schema with a clear meaning and constraints (max 100, exclusive min 0, default 60). The description does not add further detail beyond referencing service history, but since schema coverage is 100%, the baseline of 3 is appropriate.

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 retrieves the pickup schedule for each service address, listing specific fields (pickup days, next service date, set-out-by time, and observed arrival window). It is distinct from sibling tools like list_upcoming_services and list_service_history by focusing on schedule details and empirical data.

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 implies its use when needing schedule details, especially the observed time window. It references service history for derivation, but does not explicitly state when to use this tool versus siblings like list_upcoming_services or list_service_history. However, the uniqueness of the empirical window is clear enough for selection.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.