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enox_traverse

Traverse a knowledge graph from a starting entity, filtering by relationship type and direction to discover dependencies, superseding relations, or full neighborhoods.

Instructions

Graph traversal from a knowledge entity following specific edge types and direction.

Use this for structured exploration:

  • "What does X depend on?" → traverse(start="X", direction="outgoing", edge_types=["depends_on"])

  • "What supersedes X?" → traverse(start="X", direction="incoming", edge_types=["supersedes"])

  • Full neighborhood: traverse(start="X", direction="both", max_depth=2)

Returns nodes with depth info (0 = start, 1 = direct, 2+ = transitive).

Example: traverse(start="RFDB", direction="outgoing", edge_types=["depends_on", "uses"], max_depth=3)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
startYesStarting entity name or ID
directionNoTraversal direction (default: "both")
edge_typesNoFilter by edge/relation types. Omit for all.
max_depthNoMaximum traversal depth (default: 2)
Behavior3/5

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

No annotations are provided, so the description carries full burden. It mentions return structure (nodes with depth info) but does not disclose side effects, permissions, rate limits, or scope limitations. Adding such details would improve transparency.

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 concise and well-structured: starts with purpose, lists usage examples with clear formatting, explains return format, and provides a concrete example. Every sentence is valuable, and it is front-loaded with key information.

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?

Given the parameters (all documented in schema), no output schema, and the tool's complexity, the description covers essential behaviors: traversal logic, direction, edge filtering, depth, and return format. It could be more complete by mentioning any traversal limits or pagination, but it is adequate.

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?

Schema coverage is 100%, but the description adds meaning beyond the schema: it explains directions with examples, suggests edge_types filtering via 'omit for all', and notes max_depth default. This enhances the agent's understanding of parameter usage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it performs graph traversal from a knowledge entity, with specific edge types and direction. Examples illustrate usage. However, it does not explicitly differentiate from the sibling 'traverse_graph' tool, which may lead to confusion.

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 examples (dependencies, supersedes, full neighborhood) showing when to use the tool. It lacks explicit 'when not to use' or alternative tools, but the examples give strong contextual 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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