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get_stats

Get graph statistics including node and edge counts by type to verify data loading, understand graph size, and identify available node and edge types before running queries.

Instructions

Get graph statistics: node and edge counts by type.

Use this to:

  • Verify analysis completed: nodeCount > 0 means the graph is loaded

  • Understand graph size before running expensive queries

  • See what node/edge types exist in this particular codebase

  • Debug empty results: check if expected node types are present

Returns:

  • nodeCount, edgeCount: Total counts

  • nodesByType: {FUNCTION: 1234, CLASS: 56, ...}

  • edgesByType: {CALLS: 5678, CONTAINS: 3456, ...}

Use BEFORE querying an unfamiliar graph to understand what data is available.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

No annotations are provided, so the description must disclose behavior. It describes the return structure (nodeCount, edgeCount, nodesByType, edgesByType) and implies it is a read-only operation. Could add performance hints, but sufficient.

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?

Well-structured with bullet points and a usage list. Every sentence is informative. No redundancy.

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?

Given no parameters and no output schema, the description fully covers purpose, usage, and output format. It is complete for a simple statistics 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 input schema has no parameters, so baseline is 4. The description does not need to add parameter details. It appropriately explains the output structure instead.

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 'Get graph statistics: node and edge counts by type.' It uses specific verbs and resources, and distinguishes from sibling tools like enox_stats by focusing on graph statistics.

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?

Explicitly lists use cases (verify analysis, understand graph size, see types, debug) and recommends using it before querying an unfamiliar graph. Provides clear context for when to use the tool.

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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