Random Kanban Board Snapshot Dataset Generator

Description

Generate supplied-title synthetic cards under column work-in-progress caps with optional ordinal-directed acyclic dependencies and count summaries.

A workflow or scheduling fixture makes ordering, dependencies, capacity, and timing explicit. Returning both the constructed records and their checks helps consumers distinguish a valid arrangement from a simulated failure case.

Generate supplied-title synthetic cards under column work-in-progress caps with optional ordinal-directed acyclic dependencies and count summaries.

When to use this tool

Use this generator to create reproducible kanban board snapshot dataset 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 columns, titles, count, dependencyProbability 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 cards, columns, dependencies, cycleAudit. Use the conventions below and keep answer-bearing fields separate when presenting an exercise.

Allocate synthetic cards among columns with capacity remaining, sample titles, and add optional dependencies only from earlier to later card IDs. Delegate cycle checking and independently verify each column count.^[1]

Delegated operations used for this result: cycle checker. Their calculation or parsing conventions apply to the corresponding result fields.^[2]

Input field	Meaning and units	Accepted input
columns	Columns	Required. Array of Object; no unknown keys.; minimum items 1; maximum items 32.
columns[].id	Literal identifier used to match records, independently of their display labels.	Required. Text; minimum UTF-16 length 1; maximum UTF-16 length 128.
columns[].capacity	Capacity	Required. Safe integer; minimum 0; maximum 128.
titles	Titles	Required. Array of Text; minimum UTF-16 length 1; maximum UTF-16 length 128.; minimum items 1; maximum items 128.
count	Requested count; the mechanics explain whether one draw expands into several returned records.	Required. Safe integer; minimum 1; maximum 128.
dependencyProbability	Dependency Probability	Required. Finite number; minimum 0; maximum 1.
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
cards	Cards	Required. Array of Object; no unknown keys.; minimum items 1; maximum items 128.
cards[].id	Literal identifier used to match records, independently of their display labels.	Required. Text; minimum UTF-16 length 1; maximum UTF-16 length 128.
cards[].title	Title	Required. Text; minimum UTF-16 length 1; maximum UTF-16 length 128.
cards[].columnId	Column Id	Required. Text; minimum UTF-16 length 1; maximum UTF-16 length 128.
columns	Columns	Required. Array of Object; no unknown keys.; minimum items 1; maximum items 32.
columns[].id	Literal identifier used to match records, independently of their display labels.	Required. Text; minimum UTF-16 length 1; maximum UTF-16 length 128.
columns[].capacity	Capacity	Required. Safe integer.
columns[].count	Requested count; the mechanics explain whether one draw expands into several returned records.	Required. Safe integer.
dependencies	Dependencies	Required. Array of Object; no unknown keys.; minimum items 0; maximum items 8128.
dependencies[].from	From	Required. Text; minimum UTF-16 length 1; maximum UTF-16 length 128.
dependencies[].to	To	Required. Text; minimum UTF-16 length 1; maximum UTF-16 length 128.
cycleAudit	Cycle Audit	Required. Object; no unknown keys.
cycleAudit.hasCycle	Has Cycle	Required. Boolean.
cycleAudit.resolvedCount	Resolved Count	Required. Safe integer.
cycleAudit.unresolvedNodes	Unresolved Nodes	Required. Array of Text; minimum UTF-16 length 1; maximum UTF-16 length 128.; minimum items 0; maximum items 128.
randomness	Replay 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.seed	Optional numeric 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": {
    "columns": [
      {
        "id": "todo",
        "capacity": 1
      },
      {
        "id": "doing",
        "capacity": 2
      },
      {
        "id": "done",
        "capacity": 2
      }
    ],
    "titles": [
      "Map",
      "Review"
    ],
    "count": 3,
    "dependencyProbability": 0.7,
    "seed": 42
  },
  "output": {
    "cards": [
      {
        "id": "card-1",
        "title": "Map",
        "columnId": "doing"
      },
      {
        "id": "card-2",
        "title": "Review",
        "columnId": "done"
      },
      {
        "id": "card-3",
        "title": "Review",
        "columnId": "todo"
      }
    ],
    "columns": [
      {
        "id": "todo",
        "capacity": 1,
        "count": 1
      },
      {
        "id": "doing",
        "capacity": 2,
        "count": 1
      },
      {
        "id": "done",
        "capacity": 2,
        "count": 1
      }
    ],
    "dependencies": [
      {
        "from": "card-1",
        "to": "card-2"
      },
      {
        "from": "card-1",
        "to": "card-3"
      }
    ],
    "cycleAudit": {
      "hasCycle": false,
      "resolvedCount": 3,
      "unresolvedNodes": []
    },
    "randomness": {
      "seed": 42,
      "source": "seed"
    }
  }
}

Limitations and assumptions

Acyclic dependencies do not imply work is finished or schedulable under time/resource constraints. Titles can repeat and column placement is a snapshot rather than a workflow simulation.
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

Tool behavior and example: Random Kanban Board Snapshot Dataset Generator — tool.io
Calculation or validation: graph/cycle-checker — tool.io

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