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Denue

by io.github.pipeworx-io
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Denue Count

denue_count
Read-onlyIdempotent

Count establishments by economic activity + geography + size stratum. Returns totals — no detail records. Use for market-sizing questions like "how many pharmacies are in Jalisco".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
stratumNoEmployee-size stratum: 0=any, 1=0-5, 2=6-10, 3=11-30, 4=31-50, 5=51-100, 6=101-250, 7=251+. Default "0".
area_codeYesGeography code(s), comma-separated. "00" = all Mexico; 2 digits = state; 5 digits = municipality (state+mun). Examples: "09" (CDMX), "14039" (Guadalajara).
activity_codeYesSCIAN economic activity code(s), comma-separated. 2-6 digits (sector → branch → class). Use "0" for any activity. Examples: "46" (retail), "722" (food services), "464111" (pharmacies).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "activity_code": "464111",
+    "area_code": "14"
+  },
+  {
+    "activity_code": "722",
+    "area_code": "14039",
+    "stratum": "1"
+  }
+]
  2. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already indicate read-only, idempotent, open-world, and non-destructive behavior. The description adds value by clarifying that only totals are returned and no detail records, which is a behavioral trait beyond the annotations. No contradictions exist.

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 two sentences: one for function and one for usage example. No filler, front-loaded with the core purpose. Every sentence earns its place.

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 counting tool with no output schema, the description adequately explains the result type (totals) and provides a concrete use case. It could be more complete by hinting at the return format, but given the tool's simplicity and the sibling context, it is largely sufficient.

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 input schema already provides detailed descriptions for all three parameters (100% coverage). The description groups them into 'economic activity + geography + size stratum' but does not add new parameter-level details beyond the schema. Baseline 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 counts establishments by three dimensions (economic activity, geography, size stratum) and distinguishes from siblings by noting it returns totals, not detail records. The sibling tools include other denue tools that likely provide detail records or search by name, so this tool's purpose is well-differentiated.

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 gives an explicit use case ('how many pharmacies are in Jalisco') and implies market-sizing questions. However, it does not explicitly state when to avoid this tool or mention alternatives by name, missing some guidance on selection among siblings.

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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