Org Simulation
@webframp/org-simulationv2026.07.23.1
01README
Agent-guided organization design simulation model inspired by the Curious Duck simulation studio (ducksimng.onrender.com). Capture an organization as a topology of teams, repos/modules, environments (with a defect/reliability model), and customer bases, wired together by connectors. Then run a deterministic, seedable flow simulation to estimate feature/bug cycle times, defect detection, find-vs-fix balance, and customer sentiment (NPS) under a chosen deploy policy.
Designed for organization design exploration: model the current org, model a proposed redesign, run both, and compare the versioned outcomes to decide whether a structural change is worth making. The agent interviews, the model simulates and persists.
02Release Notes
2026.07.23.1
Added: Initial release of @webframp/org-simulation, an agent-guided
organization design simulation model inspired by the Curious Duck simulation
studio (ducksimng.onrender.com).
design_topology— capture an organization as a topology of teams, repos/modules, environments (with a defect/reliability model), and customer bases wired by connectors, under a named scenario label ("current"for as-is, or a descriptive label for a proposed redesign).run_simulation— run a deterministic, seedable flow simulation against a topology scenario, estimating feature/bug cycle times, defect detection and find-vs-fix balance, customer sentiment (NPS), and environment reliability over a configurable time horizon.record_design_decision— record an adopt/reject/iterate/hold decision comparing a proposed scenario's simulated outcomes against a baseline, with quantified deltas and risks the simulation can't capture.
Three resources track the model's data: topology, simulation_results, and
design_decision, each versioned per scenario/seed/comparison.
03Models
@webframp/org-simulationv2026.07.23.1org-simulation/mod.ts
Global Arguments
| Argument | Type | Description |
|---|---|---|
| organizationContext | string | Brief description of the organization, its size, business, and the team area under design |
| defectModel | object | Global defect-model parameters shared across all environments |
fn design_topology(scenarioLabel: string, widgets: array, connectors: array, notes?: string)
Capture an organization design scenario as a topology of widgets and connectors, through structured conversation.
AGENT GUIDANCE:
You are modeling an organization the way the DuckSim studio
(https://ducksimng.onrender.com/scenarios/studio) represents it: as a canvas
of widgets wired together. Guide the conversation through these phases, and
always confirm you're capturing either the CURRENT state (scenarioLabel:
"current") or a PROPOSED redesign (a descriptive scenarioLabel like
"split-platfor
| Argument | Type | Description |
|---|---|---|
| scenarioLabel | string | Label for this topology snapshot — 'current' for the as-is org, or a proposed-design name like 'split-platform-team' |
| widgets | array | Widgets on the organization canvas (teams, repos, environments, customer bases) |
| connectors | array | Wires between widgets |
| notes? | string | Context about this snapshot — what it represents and why |
fn run_simulation(scenarioLabel: string, seed: number, horizon?: enum)
Run the deterministic flow simulation against a previously-designed topology scenario.
AGENT GUIDANCE:
Before calling this, a topology must already exist for the given
scenarioLabel (call design_topology first). This method reads that snapshot,
runs a seedable simulation over the configured (or overridden) time horizon,
and persists the results.
The simulation approximates system dynamics, not a literal pixel-for-pixel
replay of the DuckSim canvas: teams generate throughput based on skill,
di
| Argument | Type | Description |
|---|---|---|
| scenarioLabel | string | Which topology snapshot to run. Must match a label previously passed to design_topology, or 'current'. |
| seed | number | RNG seed for deterministic, reproducible runs. Use different seeds to estimate variance. |
| horizon? | enum | Override the topology's metrics.horizon for this run. Defaults to the topology's configured horizon. |
fn record_design_decision(baselineLabel: string)
Record a design decision comparing a proposed scenario's simulated outcomes against a baseline.
AGENT GUIDANCE:
Before calling this, you should have run_simulation results for BOTH the
baseline scenario (usually "current") and the proposed scenario, ideally
with the same seed for a fair comparison. Read both simulation_results
resources, compute the deltas (proposed minus baseline) for feature cycle
time, bug cycle time, NPS, outstanding defects, and average certainty, and
form a recommendatio
| Argument | Type | Description |
|---|---|---|
| baselineLabel | string | Label of the baseline scenario results were compared against |
Resources
topology(infinite)— Snapshot of an organization design scenario: widgets (teams, repos, environments, customer bases), connectors, and metrics config
simulation_results(infinite)— Outcomes of a deterministic simulation run against a topology scenario
design_decision(infinite)— Recorded decision comparing a proposed scenario's simulated outcomes against a baseline
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