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by io.github.pipeworx-io
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Outdoor Recreation Economy

outdoor_recreation_economy
Read-onlyIdempotent

MARKET SIZE for outdoor recreation activities in US dollars, by activity and state — BEA's Outdoor Recreation Satellite Account (official government statistics, not analyst estimates). Use for "how big is the hunting industry", "fishing economy by state", "which states have the largest outdoor recreation economy", "value of the skiing industry". Activities include hunting, shooting, fishing, boating, hiking/camping, equestrian, skiing/snow, bicycling, RVing, motorcycling/ATV, golf/tennis, guided tours, and the overall total. Returns value added (the activity's contribution to GDP) per state for a year, ranked. IMPORTANT: birdwatching and wildlife WATCHING are not separate lines in this account — hunting and fishing are the only wildlife-related activities measured, so do not use this to size birding specifically. This tool wraps BEA table SAOACTVA so you do not have to know BEA table or line codes; for other BEA data use get_data.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
yearNoData year (e.g. 2023). Defaults to the most recent published year.
limitNoMax states to return when no state filter is given (default 51).
stateNoState name or 2-letter abbreviation (e.g. "Colorado" or "CO") to return just that state. Omit for all 50 states + DC, ranked largest first.
activityNoActivity to size. Friendly names accepted: "total", "hunting", "shooting", "fishing", "boating", "boating/fishing", "hiking" (climbing/hiking/camping), "equestrian", "bicycling", "skiing", "snow", "rving", "motorcycling", "atv", "golf", "field sports", "guided tours", "amusement parks", "festivals", "flying", "canoeing", "sailing", "gardening". Default "total".

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "activity": "total",
+    "year": 2023
+  },
+  {
+    "activity": "fishing",
+    "state": "CO",
+    "year": 2022
+  }
+]
  2. Added

TDQS

A4.9/5.0
Behavior5/5

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

Annotations already indicate a safe read-only, idempotent operation. The description goes further by stating the data is official government statistics (not analyst estimates), explaining the metric (value added contribution to GDP), noting the output is ranked per state, and flagging the limitation that birdwatching is not a separate line. This adds substantial context beyond the annotations with no contradiction.

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?

The description is dense but every sentence contributes: purpose, example uses, activity list, output format, an important caveat, and a pointer to an alternative tool. The key phrase 'MARKET SIZE' is front-loaded, making the tool's purpose immediately clear.

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 and four optional parameters, the description fully covers what the tool returns (value added per state, ranked), the source (BEA SAOACTVA), how to invoke it for examples, and its limitations. It also differentiates from the sibling 'get_data' tool, making it self-contained for agent selection.

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?

The input schema already covers 100% of parameters with clear descriptions, so the baseline is 3. The description adds value by explaining the meaning of 'value added' (contribution to GDP) and clarifying that states are ranked, which helps interpret the 'state' and 'activity' parameters. It also lists example activities that map to the schema, though the schema itself is more exhaustive.

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 names a specific verb ('MARKET SIZE'), a specific resource ('outdoor recreation activities in US dollars, by activity and state'), and cites the official BEA source. It distinguishes itself from sibling tools by explicitly directing other BEA data to 'get_data'.

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?

Provides concrete example queries ('how big is the hunting industry', 'fishing economy by state') and clear exclusions: warns not to use for birdwatching and points to 'get_data' for other BEA data. This gives the agent explicit when-to-use and 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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