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find_systems_in_range

Read-only

Identify solar systems within a defined jump range from an origin system, considering route preferences and optional system exclusions. Uses a stargate connection graph for precise navigation in EVE Online.

Instructions

Find all solar systems within a specified jump range from an origin system using efficient graph traversal. Builds a stargate connection graph for accurate results.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
avoidSystemsNoOptional array of solar system names (English proper nouns) or IDs to avoid in routes
flagNoRoute preference: shortest (default), secure (high-sec only), or insecure (low/null-sec allowed)shortest
maxJumpsYesMaximum number of jumps to search (1-10)
originYesOrigin solar system name (English proper noun like 'Jita') or ID
Behavior4/5

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

Annotations provide readOnlyHint=true and openWorldHint=true, indicating safe read operations with potentially large result sets. The description adds valuable context beyond this by specifying 'Builds a stargate connection graph for accurate results', which explains the underlying method and accuracy assurance. However, it doesn't detail performance characteristics like speed or limitations on result size, leaving some behavioral aspects uncovered.

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 with zero waste: the first states the core purpose and method, and the second adds technical context about graph building. It's front-loaded with the main action and efficiently structured, making every sentence earn its place without redundancy or unnecessary elaboration.

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 tool's complexity (graph traversal with multiple parameters), annotations cover safety and scope, and schema fully documents inputs, the description is mostly complete. It explains the method and accuracy but lacks output details (no output schema provided) and doesn't mention potential constraints like data freshness or error handling. This minor gap prevents a perfect score.

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 the schema fully documents all parameters. The description doesn't add any parameter-specific semantics beyond what's in the schema, such as clarifying 'origin' as a starting point or 'maxJumps' as a search limit. Thus, it meets the baseline of 3 where the schema handles parameter documentation adequately.

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 specific action ('Find all solar systems') with the resource ('within a specified jump range from an origin system') and method ('using efficient graph traversal'). It distinguishes from siblings by focusing on range-based discovery rather than route calculation or information lookup, as evidenced by comparing to tools like 'calculate_route' or 'solar_system_info'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for range-based discovery but doesn't explicitly state when to use this tool versus alternatives like 'calculate_multiple_routes' or 'find_nearest_trade_hub'. It mentions 'efficient graph traversal' which suggests performance benefits, but lacks clear exclusions or named alternatives, leaving usage context partially inferred rather than directly guided.

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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