Good Earth

Goodearth Pest Threshold

goodearth_pest_threshold

Where a pest model's degree-day stages stand on this ground.

Returns, per model: heat accumulated since its biofix, which stages have been crossed, and the projected date of the next one — plus a short list of which pests to go and look for this week.

Good Earth computes when your models arrive on your ground. It does not publish entomology: the thresholds are yours, because the authoritative numbers belong to your extension service and vary by region and biotype.

Input Schema

TableJSON Schema

Name	Required	Description
`npub`	No	Required. Your Nostr public key (npub1...) for credit billing.
`block`	Yes	The ground to answer for: a block you have saved — its id, its name, one of its aliases, or any part of its name that only one block has (e.g. "Meadow" for "Lower Meadow"). If several match, the error lists them with their ids. Blocks may overlap; each answers for its own ground. Save one with block_save first; geometry travels once, not on every call.
`pests`	Yes	The pests to evaluate, in any of three shapes. 1. Your own thresholds, from an extension bulletin: {"pest": "Aster leafhopper", "base_temp": 50, "biofix": "2026-05-01", "stages": [{"stage": "second flight", "gdd": 1850}]}. biofix is optional; without it the count runs from Jan 1. 2. A published model, cited rather than restated: {"pest": "Japanese beetle", "model": "usa-npn"} — the dates come from USA-NPN for your ground, and re-resolve each season instead of freezing whatever was pasted in. 3. Something you simply keep an eye out for: {"pest": "Vole", "watch": true} — no stages, no dates. Do NOT invent degree-day figures to fill shape 1. Use 2 or 3.
`dpop_token`	No

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedSep 15, 2026

TDQS

A3.9/5.0

Behavior4/5

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

With no annotations provided, the description carries the burden. It explicitly states that Good Earth does not publish its own entomology thresholds and that authoritative numbers come from the user's extension service, preventing the agent from assuming built-in science. It also notes that geometry is sent once (on block save) rather than on every call, though that detail lives in the schema.

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 five sentences, front-loads the core purpose, and uses compact phrasing. Each sentence earns its place — no filler.

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?

The description explains the key conceptual model (degree-day accumulation), the three ways to supply pest data, and the warning against inventing degree-day figures. Combined with a rich 'pests' schema and an existing output schema, the agent has enough context to call the tool correctly. Minor gaps like authentication are covered by the 'npub' schema description.

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 description coverage is 75%, and the two required parameters (block, pests) have thorough descriptions, including disambiguation rules and the three input shapes. The tool description itself adds little beyond the schema, so a 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 opens with a clear statement of what the tool computes — where degree-day stages stand per pest model — and lists the exact returns (heat accumulated, stages crossed, next projected date, and a list of pests to watch). This distinguishes it from sibling tools like crop GDD or disease risk by focusing on user-supplied pest thresholds.

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 trigger (evaluate pest models on a given ground) but does not explicitly contrast with other evaluation tools. However, the detailed 'pests' parameter schema includes three usage shapes and a clear warning, which substantially compensates for the missing when/alternatives guidance.

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

All Good Earth tools Inspect

Try in Browser

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.