Random Fantasy Guild Membership Network Generator

Description

Assign fictional guild quota slots with resident caps and exclusions using bounded nonuniform bipartite search, retaining weak subgroup counts including isolated residents.

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.

Assign fictional guild quota slots with resident caps and exclusions using bounded nonuniform bipartite search, retaining weak subgroup counts including isolated residents.

When to use this tool

Use this generator to create reproducible fantasy guild membership 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

Supply residentIds, guilds, maximumMembershipsPerResident in the field shapes below. Set seed when you need an explicit replay.
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.
Read memberships, residentCounts, guildCounts, componentCount, fictional. Use the conventions below. Keep answer-bearing fields separate when presenting an exercise.

Expand each guild quota into membership slots and use bounded search to assign distinct permitted residents per guild while respecting maximum memberships per resident. Return guild/resident counts and components of the resulting bipartite graph.^[1]

Input field	Meaning and units	Accepted input
residentIds	Resident Ids	Required. Array of Text; minimum UTF-16 length 1; maximum UTF-16 length 64.; minimum items 1; maximum items 16.
guilds	Guilds	Required. Array of Object; no unknown keys.; minimum items 1; maximum items 8.
guilds[].id	Literal identifier used independently of display labels.	Required. Text; minimum UTF-16 length 1; maximum UTF-16 length 64.
guilds[].quota	Quota	Required. Safe integer; minimum 0; maximum 16.
guilds[].forbiddenResidentIds	Forbidden Resident Ids	Required. Array of Text; minimum UTF-16 length 1; maximum UTF-16 length 64.; minimum items 0; maximum items 16.
maximumMembershipsPerResident	Maximum Memberships Per Resident	Required. Safe integer; minimum 0; maximum 8.
seed	Optional numeric seed; takes precedence over context randomness. Without either, use the fixed tool.io default seed.	Optional. Safe integer.

Output field	Interpretation	Returned shape
memberships	Memberships	Required. Array of Object; no unknown keys.; minimum items 0; maximum items 128.
memberships[].guildId	Guild Id	Required. Text; minimum UTF-16 length 1; maximum UTF-16 length 64.
memberships[].residentId	Resident Id	Required. Text; minimum UTF-16 length 1; maximum UTF-16 length 64.
residentCounts	Resident Counts	Required. Array of Object; no unknown keys.; minimum items 1; maximum items 16.
residentCounts[].id	Literal identifier used independently of display labels.	Required. Text; minimum UTF-16 length 1; maximum UTF-16 length 64.
residentCounts[].count	Count	Required. Safe integer; minimum 0; maximum 8.
guildCounts	Guild Counts	Required. Array of Object; no unknown keys.; minimum items 1; maximum items 8.
guildCounts[].id	Literal identifier used independently of display labels.	Required. Text; minimum UTF-16 length 1; maximum UTF-16 length 64.
guildCounts[].count	Count	Required. Safe integer; minimum 0; maximum 16.
componentCount	Component Count	Required. Safe integer; minimum 1; maximum 24.
fictional	Fictional	Required. Boolean; exactly true.
randomness	Replay source and normalized 32-bit seed, or null seed for an advancing context source.	Required. Object; no unknown keys.
randomness.seed	Optional safe-integer replay seed; normalization and precedence are explained below.	Required. Safe integer. or Null.
randomness.source	Source	Required. 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": {
    "residentIds": [
      "ada",
      "ben",
      "cy"
    ],
    "guilds": [
      {
        "id": "sailors",
        "quota": 2,
        "forbiddenResidentIds": [
          "cy"
        ]
      },
      {
        "id": "smiths",
        "quota": 1,
        "forbiddenResidentIds": [
          "ada",
          "ben"
        ]
      }
    ],
    "maximumMembershipsPerResident": 1,
    "seed": 42
  },
  "output": {
    "memberships": [
      {
        "guildId": "sailors",
        "residentId": "ada"
      },
      {
        "guildId": "sailors",
        "residentId": "ben"
      },
      {
        "guildId": "smiths",
        "residentId": "cy"
      }
    ],
    "residentCounts": [
      {
        "id": "ada",
        "count": 1
      },
      {
        "id": "ben",
        "count": 1
      },
      {
        "id": "cy",
        "count": 1
      }
    ],
    "guildCounts": [
      {
        "id": "sailors",
        "count": 2
      },
      {
        "id": "smiths",
        "count": 1
      }
    ],
    "componentCount": 2,
    "fictional": true,
    "randomness": {
      "seed": 42,
      "source": "seed"
    }
  }
}

Limitations and assumptions

Residents can belong to several guilds but never twice to the same guild. Quotas must be jointly feasible. The result is fictional membership structure, not social inference or uniform sampling over assignments.
A replay requires the same complete input and implementation. The stated sampling convention applies within its eligible space. A finite draw does not exhaust all possible outputs; repeats remain possible unless a distinct-selection rule is explicit.
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

Tool behavior and example: Random Fantasy Guild Membership Network Generator — tool.io

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