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tx_wells_near

Read-onlyIdempotent

Find Texas oil & gas wells near a location using the Texas Railroad Commission (RRC) public well map (keyless public record). Given a longitude/latitude and a radius, returns the wells within it, each with its API well number, well number, and type/status (e.g. 'Oil Well', 'Gas Well', 'Permitted Location', 'Dry Hole', 'Injection/Disposal'), plus a breakdown by type. Use geocode_address first to turn a street address into coordinates. Texas covers the Permian and Eagle Ford basins. This is well LOCATION + type data; operator, production volumes, and permit dates are not in this layer.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
latYesLatitude of the center point (WGS84), e.g. 31.9974.
lonYesLongitude of the center point (WGS84), e.g. -102.0779.
limitNoMax wells to return (default 25, max 100).
radius_kmNoSearch radius in kilometers (default 1.5, max 10).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed5 schema fields changed
    • addedInput schema / properties / limit / maximum
      Added value: +100
    • addedInput schema / properties / limit / minimum
      Added value: +1
    • changedInput schema / properties / limit / type
      Previous value: -"number"New value: +"integer"
    • addedInput schema / properties / radius_km / maximum
      Added value: +10
    • addedInput schema / properties / radius_km / minimum
      Added value: +0.1
  2. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnly/idempotent/non-destructive, so the bar is lower, and the description still adds real context: keyless public record (no auth), a concrete enumeration of return fields and type/status values, and a breakdown-by-type note. With no output schema, this return-shape disclosure is genuinely useful; it just doesn't cover pagination or truncation behavior near the limit cap.

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?

Front-loads the core action and resource, then layers prerequisite, scope, and exclusions in tight clauses with zero filler. Every sentence (data source, return fields, geocode routing, exclusions) carries information an agent needs to call the tool correctly.

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?

With no output schema, the description carries the return-value burden and does so fully by naming the fields and type/status values plus the by-type breakdown. Combined with auth (keyless), geography, a prerequisite step, and explicit limitations, an agent has everything needed to invoke it 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?

Schema description coverage is 100%, so lat, lon, limit, and radius_km are already fully documented with types, bounds, and examples. The description restates 'longitude/latitude and a radius' but adds no syntax, units, or ordering detail beyond the schema, so the baseline 3 applies.

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 specific verb (Find) plus a precisely scoped resource (Texas oil & gas wells near a location) and the underlying data source (Texas RRC public well map). The geographic limitation (Texas, Permian/Eagle Ford basins) distinguishes it from the sibling ok_wells_search for Oklahoma without the agent opening either schema.

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?

Gives an explicit prerequisite and routing instruction: 'Use geocode_address first to turn a street address into coordinates.' It also clarifies the data scope boundaries (location + type only, not operator/production/permit dates). It never states when NOT to use it or names a competing alternative, so it stops short of a 5.

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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