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chrischall
by chrischall

Sample climate baseline for an area by pulling a few addresses

redfin_get_area_climate_baseline
Read-onlyIdempotent

Fetch climate risk for 2–10 sample Redfin URLs, average fire, flood, and heat factors, and return a shared cluster baseline to avoid redundant per-property calls.

Instructions

Fetch climate risk for a small set of representative URLs in an area, then return their averaged baseline values plus the shared cluster_id when present. Use this as a cheap area-level read BEFORE fanning out a per-property call: if all sample properties agree (same cluster_id, same fire/flood/heat factors), the baseline applies to the whole cluster and N redundant fetches are avoidable. Pass 2–10 URLs you believe represent the area; returns the aggregate plus the per-URL responses for transparency. Server-side concurrency (~5 fetches in flight) with retry-once-on-timeout per URL; the whole call is bounded by an overall deadline, and any sample still unsettled then comes back as status: "pending" (retryable) with a pending count and is left out of the averages. Limitations of the per-property tool apply (no landslide coverage — note documented in the per-property tool description).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sample_urlsYesArray of 2–10 sample Redfin URLs representative of the area.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.0.0
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
  2. First observedv0.10.1

TDQS

A4.8/5.0
Behavior5/5

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

Goes well beyond the readOnly/idempotent/openWorld annotations: server-side concurrency (~5 fetches in flight), retry-once-on-timeout per URL, an overall deadline after which unsettled samples return status "pending" with a pending count and are excluded from averages, and inherited per-property limitations (no landslide coverage). This is exactly the operational context an agent needs.

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?

Front-loads the purpose and the routing rationale, and packs retry/deadline/pending semantics tightly. It is a dense single paragraph, and the closing limitations pointer to another tool's description is slightly indirect, but no sentence is filler.

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?

Although there is no output schema, the description enumerates the return shape (aggregate baseline values, shared cluster_id, per-URL responses for transparency, pending status/count) and the failure mode, so nothing needed to call or interpret the result is missing.

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?

Schema coverage is 100% and the single parameter is already documented, so the baseline is 3. The description adds genuine meaning beyond the schema: the URLs must be representative of the area, and the count rationale (enough samples to establish cluster agreement).

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?

States a concrete verb and resource (fetch climate risk for a set of representative URLs, return averaged baseline plus cluster_id) and immediately frames it as an area-level read distinct from per-property calls. An agent can tell it apart from redfin_get_climate_risk, redfin_get_climate_risk_bulk, and redfin_get_property from the description alone.

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

Usage Guidelines5/5

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

Gives explicit when-to-use (a cheap area-level read BEFORE fanning out per-property calls), the decisive condition (if all sample properties share cluster_id and fire/flood/heat factors, the baseline applies to the whole cluster and redundant fetches are avoidable), and the input guidance (pass 2–10 URLs you believe represent the area). No alternatives are left to inference.

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