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Random World Portal Network Generator

Choose an exact fictional directed portal subset with activation solved over location-and-held-flag states. Required destinations are independently reachable, not one tour; bounded nonuniform search.

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Description

Choose an exact fictional directed portal subset with activation solved over location-and-held-flag states. Required destinations are independently reachable, not one tour; bounded nonuniform search.

Worldbuilding fixtures describe an invented setting through supplied entities and explicit relations. A reproducible arrangement can support games or writing exercises while keeping constructed history and geography separate from factual claims about the real world.

Choose an exact fictional directed portal subset with activation solved over location-and-held-flag states. Required destinations are independently reachable, not one tour; bounded nonuniform search.

When to use this tool

Use this generator to create reproducible world portal network cases from the supplied model or bank. Inspect the returned evidence before using cases in a test or exercise.

How to use the tool and how it works

  1. Supply locations, flagIds, initialFlagIds, start, candidates, portalCount, requiredLocationIds in the field shapes below. Set seed when you need an explicit replay.
  2. Run the tool and correct any input error. For generated controls, distinguish a successful fixture containing an invalid case from failure to generate the fixture.
  3. Read portals, reachableLocationIds, witnesses, exploredStateCount, componentCount, fictional. Use the conventions below and keep answer-bearing fields separate when presenting an exercise.

Search an exact-size subset of supplied directed portal candidates. Analyze each subset by breadth-first traversal of location-and-held-flag states: visiting a location accumulates its grants, and a portal opens only when required flags are held. Return independently reachable destinations with path/flag witnesses.1

Delegated operations used for this result: breadth first traversal. Their calculation or parsing conventions apply to the corresponding result fields.2

Input fieldMeaning and unitsAccepted input
locationsLocationsRequired. Array of Object; no unknown keys.; minimum items 1; maximum items 12.
locations[].idLiteral identifier used to match records, independently of their display labels.Required. Text; minimum UTF-16 length 1; maximum UTF-16 length 64.
locations[].grantsFlagIdsGrants Flag IdsRequired. Array of Text; minimum UTF-16 length 1; maximum UTF-16 length 64.; minimum items 0; maximum items 6.
flagIdsFlag IdsRequired. Array of Text; minimum UTF-16 length 1; maximum UTF-16 length 64.; minimum items 0; maximum items 6.
initialFlagIdsInitial Flag IdsRequired. Array of Text; minimum UTF-16 length 1; maximum UTF-16 length 64.; minimum items 0; maximum items 6.
startStartRequired. Text; minimum UTF-16 length 1; maximum UTF-16 length 64.
candidatesCandidatesRequired. Array of Object; no unknown keys.; minimum items 0; maximum items 24.
candidates[].fromFromRequired. Text; minimum UTF-16 length 1; maximum UTF-16 length 64.
candidates[].toToRequired. Text; minimum UTF-16 length 1; maximum UTF-16 length 64.
candidates[].requiresFlagIdsRequires Flag IdsRequired. Array of Text; minimum UTF-16 length 1; maximum UTF-16 length 64.; minimum items 0; maximum items 6.
portalCountPortal CountRequired. Safe integer; minimum 0; maximum 24.
requiredLocationIdsRequired Location IdsRequired. Array of Text; minimum UTF-16 length 1; maximum UTF-16 length 64.; minimum items 0; maximum items 12.
seedOptional numeric seed; takes precedence over context randomness. Without either, use the fixed tool.io default seed.Optional. Safe integer.
Output fieldInterpretationReturned shape
portalsPortalsRequired. Array of Object; no unknown keys.; minimum items 0; maximum items 24.
portals[].fromFromRequired. Text; minimum UTF-16 length 1; maximum UTF-16 length 64.
portals[].toToRequired. Text; minimum UTF-16 length 1; maximum UTF-16 length 64.
portals[].requiresFlagIdsRequires Flag IdsRequired. Array of Text; minimum UTF-16 length 1; maximum UTF-16 length 64.; minimum items 0; maximum items 6.
reachableLocationIdsReachable Location IdsRequired. Array of Text; minimum UTF-16 length 1; maximum UTF-16 length 64.; minimum items 1; maximum items 12.
witnessesWitnessesRequired. Array of Object; no unknown keys.; minimum items 0; maximum items 12.
witnesses[].destinationDestinationRequired. Text; minimum UTF-16 length 1; maximum UTF-16 length 64.
witnesses[].locationsLocationsRequired. Array of Text; minimum UTF-16 length 1; maximum UTF-16 length 64.; minimum items 1; maximum items 768.
witnesses[].heldFlagIdsHeld Flag IdsRequired. Array of Text; minimum UTF-16 length 1; maximum UTF-16 length 64.; minimum items 0; maximum items 6.
exploredStateCountExplored State CountRequired. Safe integer; minimum 1; maximum 768.
componentCountComponent CountRequired. Safe integer; minimum 1; maximum 12.
fictionalFictionalRequired. Boolean; exactly true.
randomnessReplay metadata: source is seed or context; seed is the normalized 32-bit seed or null for a context source.Required. Object; no unknown keys.
randomness.seedOptional numeric replay seed; normalization and precedence are explained below.Required. Safe integer. or Null.
randomness.sourceSourceRequired. Text; one of "context", "seed".

An explicit safe-integer seed takes precedence over injected context randomness and is normalized to an unsigned 32-bit integer. With no seed and no context source, replay uses the fixed tool.io default seed. A context source must return finite values from zero inclusive to one exclusive; its advancing state must be retained separately. randomness records the source and normalized seed, or null for context. These generators are not cryptographic random sources.

json
{
  "input": {
    "locations": [
      {
        "id": "a",
        "grantsFlagIds": []
      },
      {
        "id": "b",
        "grantsFlagIds": [
          "key"
        ]
      },
      {
        "id": "c",
        "grantsFlagIds": []
      }
    ],
    "flagIds": [
      "key",
      "moon"
    ],
    "initialFlagIds": [],
    "start": "a",
    "candidates": [
      {
        "from": "a",
        "to": "b",
        "requiresFlagIds": []
      },
      {
        "from": "b",
        "to": "c",
        "requiresFlagIds": [
          "key"
        ]
      },
      {
        "from": "a",
        "to": "c",
        "requiresFlagIds": [
          "moon"
        ]
      }
    ],
    "portalCount": 2,
    "requiredLocationIds": [
      "c"
    ],
    "seed": 42
  },
  "output": {
    "portals": [
      {
        "from": "a",
        "to": "b",
        "requiresFlagIds": []
      },
      {
        "from": "b",
        "to": "c",
        "requiresFlagIds": [
          "key"
        ]
      }
    ],
    "reachableLocationIds": [
      "a",
      "b",
      "c"
    ],
    "witnesses": [
      {
        "destination": "c",
        "locations": [
          "a",
          "b",
          "c"
        ],
        "heldFlagIds": [
          "key"
        ]
      }
    ],
    "exploredStateCount": 3,
    "componentCount": 1,
    "fictional": true,
    "randomness": {
      "seed": 42,
      "source": "seed"
    }
  }
}

Limitations and assumptions

  • Reachability of every required destination does not imply one tour visits them all. The search is bounded and nonuniform; graph component count alone ignores flag-dependent activation.
  • A replay requires the same complete input and implementation. Randomized construction does not guarantee uniform coverage of every feasible output; finite samples can repeat unless a distinct-selection rule is explicitly stated.
  • The field tables state structural bounds; cross-field constraints and bounded search or output budgets also apply. Unknown keys are rejected where the object contract disallows them. Input errors are distinct from null fields and deliberate invalid controls in a successful output.

Alternative or Complementary methods

For a supplied example, inspect the returned construction or delegated check directly. To evaluate a consumer, also test cases chosen for its own boundaries; a generated finite corpus does not establish exhaustive coverage.

References

  1. Tool behavior and example: Random World Portal Network Generator — tool.io

  2. Calculation or validation: graph/breadth-first-traversal — tool.io

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