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Govcon Intel

by io.github.pipeworx-io
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Govcon Agency Landscape

govcon_agency_landscape
Read-onlyIdempotent

Get contracting activity and market insights for a federal agency (e.g., 'Department of Defense', 'NASA'). Returns spending trends, recent awards, SBIR stats, and top contractors by volume.

Example tool call

This call uses example arguments supplied in the tool’s input schema.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "agency": "Department of Defense"
    },
    "name": "govcon_agency_landscape"
  }
}

Input Schema

NameRequiredDescriptionDefault
agencyYesFederal agency name

Output Schema

NameRequiredDescriptionDefault
agencyYesFederal agency name queried
analysisYesAnalysis type identifier
sbir_programYesSBIR/STTR program statistics for agency
recent_awardsYesRecent award contracts from this agency
spending_trendsYesHistorical spending trends for agency
spending_overviewYesAgency spending breakdown by category

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "properties": {
+    "agency": {
+      "description": "Federal agency name queried",
+      "type": "string"
+    },
+    "analysis": {
+      "description": "Analysis type identifier",
+      "enum": [
+        "agency_landscape"
+      ],
+      "type": "string"
+    },
+    "recent_awards": {
+      "description": "Recent award contracts from this agency",
+      "type": [
+        "object",
+        "null"
+      ]
+    },
+    "sbir_program": {
+      "description": "SBIR/STTR program statistics for agency",
+      "type": [
+        "object",
+        "null"
+      ]
+    },
+    "spending_overview": {
+      "description": "Agency spending breakdown by category",
+      "type": [
+        "object",
+        "null"
+      ]
+    },
+    "spending_trends": {
+      "description": "Historical spending trends for agency",
+      "type": [
+        "object",
+        "null"
+      ]
+    }
+  },
+  "required": [
+    "analysis",
+    "agency",
+    "spending_overview",
+    "recent_awards",
+    "sbir_program",
+    "spending_trends"
+  ],
+  "type": "object"
+}
  2. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "agency": "Department of Defense"
+  },
+  {
+    "agency": "NASA"
+  }
+]
  3. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is known. The description adds behavioral context by specifying the types of insights returned (spending trends, recent awards, SBIR stats, top contractors), giving the agent a concrete picture of what the tool produces.

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 one tight sentence that packs purpose, examples, and return summary without any filler. Every piece of information 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?

With only one parameter, full annotations covering safety, and an output schema present, the description is complete. It explains the tool's purpose, scope, and sample output, and no further caveats are needed for this simple read-only tool.

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 schema covers the single 'agency' parameter with 'Federal agency name'. The description adds realistic examples ('Department of Defense', 'NASA') that clarify expected input format and scope, going beyond the schema's minimal definition.

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 uses a specific verb ('Get') and resource ('contracting activity and market insights for a federal agency'), with concrete examples (DoD, NASA) and an enumeration of return content. This clearly differentiates it from sibling tools like govcon_contractor_profile and govcon_opportunity_scan.

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 provides clear context: it is for agency-level landscape insights, which implies when to use it. However, it does not explicitly mention alternatives or exclusions, so it stops short of full 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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