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Ca Procurement Supplier

ca_procurement_supplier
Read-onlyIdempotent

Aggregate a supplier's California STATE contract awards from the SCPRS purchase-order data on data.ca.gov: total dollars awarded, number of purchase orders, and a breakdown by awarding department (agency) and by fiscal year. Matches the supplier name as a case-insensitive substring, so it also surfaces name variants (e.g. "Pitney Bowes" vs "Pitney Bowes, Inc"). Use this to size up a single vendor's business with the State of California. This is CALIFORNIA STATE data (not federal).

Input Schema

NameRequiredDescriptionDefault
supplierYesSupplier / vendor name to aggregate (case-insensitive substring), e.g. "Deloitte", "Dell".
fiscal_yearNoOptional: restrict to one fiscal year, e.g. "2014-2015".

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
      +  {
      +    "supplier": "Deloitte"
      +  },
      +  {
      +    "fiscal_year": "2014-2015",
      +    "supplier": "Dell"
      +  }
      +]
  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 readOnlyHint=true, openWorldHint=true, idempotentHint=true, destructiveHint=false. Description adds that matches are case-insensitive and surfaces name variants, and notes the data is California state, not federal. No contradictions. Provides useful context beyond annotations.

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?

Three concise sentences front-loaded with the main purpose. Second sentence adds behavioral detail, third gives usage guidance. No wasted words. Every sentence earns its place.

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?

The description explains the return structure (totals, counts, breakdowns) despite no output schema. With only 2 parameters and simple semantics, the description is complete for an agent to understand what the tool does and what it returns.

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 baseline is 3. The description reinforces 'case-insensitive substring' for supplier and optional fiscal_year, but does not add new meaning beyond the schema's own property descriptions. Adequate but not exceptional.

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 specifies the action (aggregate), resource (SCPRS California state contract awards), and outputs (total dollars, purchase orders, breakdown by department and fiscal year). It clearly distinguishes from sibling tools like ca_procurement_department or ca_procurement_top_suppliers by focusing on a single supplier.

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?

Explicitly states use case: 'size up a single vendor's business with the State of California.' Mentions substring matching for name variants. Does not explicitly list when not to use, but sibling tools provide context for alternatives. Clear enough for an agent to select appropriately.

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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