# Building Simulated Worlds > Use when generating a simulated workplace, institution, or multi-agent history that tasks will be graded against - covers determinism, the offstage boundary, coherence gates, artifact realism, and fidelity measurement. Load before writing any world generator. - Skill: `punitarani/building-simulated-worlds` (Agent Skill) - Install (CLI): `npx skillmds@latest add punitarani/building-simulated-worlds` - Raw SKILL.md: https://api.skillmd.com/api/skills/punitarani/building-simulated-worlds/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: AI & ML - Author: punitarani (https://skillmd.com/u/punitarani) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/punitarani/building-simulated-worlds --- # Building a world worth grading The world must be *true* before anything cut from it can be *fair*. ## Non-negotiables - **Determinism is the product.** Every generator takes an explicit seed and produces identical bytes for identical input. No wall-clock, no unseeded randomness, no dependence on dict or filesystem ordering. Without this, no measurement repeats and no defect reproduces. - **Every ordering on the replay path is explicit.** Gather concurrent results in declaration order, never completion order; assign sequence numbers at emission, not at enqueue. Concurrency that reorders is nondeterminism wearing a performance argument. - **Split generation by kind.** Structure the institution's own systems would produce — rosters, records, cycles, calendars — derives deterministically from the seed. Every piece of language or judgment is a model call grounded against that structure. **A structural generator that starts emitting prose has crossed into authorship**, and prose from a structural generator is the same sentence every time. - **The referee is deterministic: zero model calls.** Whatever turns actor intents into world facts resolves each reference against world state or rejects the intent, and rejections become feedback the actor sees. A referee that improvises cannot be replayed. - **Loud failure, always.** Cassette misses, budget exhaustion, integrity violations, transport errors — all raise. A world that degrades silently produces scores that mean nothing and cannot be traced. - **The offstage boundary is structural, not conventional.** The agent reaches the world through materialized data and tool servers over projected databases — never through simulation internals, personas, hidden state, or reward logic. Enforce it in the type system so it cannot be forgotten. ## Gates that belong to the world, not the task - **Coherence before materialization.** Contradictions block. Ambiguities are *reported and keyed around*, never silently graded — a record that says two things with no stated precedence cannot be graded, because the answer would depend on which statement the agent read first. Reported ambiguities are raw material for hard tasks. - **Derived directories are rebuilt wholesale, never incrementally.** A materializer that writes files and never removes them accumulates several worlds in one directory. This stays invisible until the first task grades those files: **a defect in a surface nothing reads has no test that can fail.** The same logic covers docs, generated indexes, and any output whose only consumer is a human. - **Refresh derived truth from the world you actually shipped.** A default path pointing at a different build than the bundle silently derives a fresh answer key from a stale world. - **Find what actually serializes before provisioning for parallelism.** A generated world's cost is not its total call count, it is the length of its critical path. In one engine, actors wake in cohorts and the whole cast wakes together, so useful concurrency equals the cast size — measured at exactly the internal headcount, with everything provisioned above it doing nothing. Two consequences, and the first is easy to get backwards: **cast size is nearly free**, because a cohort runs in parallel, while **tick count and tail latency are the whole cost**. A rate like "calls per minute" hides this; a histogram of concurrent work does not. - **A cohort's wall time is its slowest member.** A model tier used by one call in ten still sets the pace for the other nine. Reach for the fast tier when buying fidelity — it writes the world — and keep the deep tier cheap enough not to dominate the critical path. - **Coarsening the simulated clock does not buy wall time.** Widening the wake interval threefold gave each actor threefold more accumulated context per wake, so per-tick work rose and cancelled the tick reduction. The work a simulated day contains is a property of the day, not of how finely it is sliced. - **Read what the referee refused, not only what it recorded.** A deterministic referee resolves every reference against world state and rejects what it cannot resolve — that is exactly right, and it means a world can be *structurally incomplete* while every component behaves correctly. The actors reach for something the world does not offer, the referee refuses, and the record simply has less in it than the day did. Measured: 16.8% of one firm's attempted timekeeping vanished because the people had administrative and internal work to book and no code to book it against, so they invented plausible ones and every rejection was correct. Nothing else catches this. **Coherence checks look for a fact carrying two values; they cannot see a fact that was never recorded.** The materializer writes what exists, and any figure computed over the survivors is perfectly self-consistent and answers a question about an institution that does not exist. Gate the *loss rate* out of the referee's own rejection notes, and write the gate's message so it blames the world rather than the referee — otherwise the next reader fixes it by making the referee permissive, which trades a visible gap for an invisible one. - **A bound applied in declaration order encodes a priority nobody chose.** Any list an actor is shown gets capped so it does not flood the prompt, and the cap almost always keeps the first N. But what is declared last is usually the *shared* material — the institution-wide codes, the defaults, the things belonging to nobody in particular — and those are exactly what every actor needs. Measured: standing matter codes fell outside the cap for the whole cast, people invented references for work they genuinely had to record, the referee correctly refused, and 20.7% of attempted timekeeping vanished. The trap has a second half worth naming. The obvious fix — *add the missing codes* — made it **worse**, 16.8% to 20.7%, because six more entries pushed the shared ones further past the cap. **Fixing the symptom a rejection names, without measuring the mechanism underneath, can move the number the wrong way.** Reserve the shared slots explicitly, and make the reservation a no-op below the cap so every existing recording stays byte-identical in content *and order*. - **Set thresholds between two measured worlds** — a known-bad and a known-good — rather than at a round number. A band picked by intuition either never fires or fires constantly, and either way stops being read. ## Never ask a model for arithmetic, then record the answer as world data Three defects in one world turned out to be one mistake repeated: an intent asked a language model for something models are unreliable at, got unreliable output, and wrote it into the record as a property of the firm. Each was then *measured* as a data defect and worked around. The worst was a calendar. The intent took `start` and `end` as raw seconds on the simulation clock. Seven persona-scheduled meetings in one recorded day: 1717609200 a real-world Unix timestamp — reads as June 2080 1717 00:28 1200 00:20 1400400 05:00 1300000 01:06 37800 10:30 a meeting 33300 09:15 a meeting Two of seven. Across six months, 42.4% of calendar starts were not seconds-from-epoch at all; half the diary was quarantined before serving and a whole task was retired for want of a calendar to read. None of that is a model failure — a person books a meeting by day and wall clock, and the arithmetic belongs to the referee. The intent now takes a bounded `day_offset` and two `HH:MM` clocks, and the shape that produced June 2080 has no field it fits in. The same shape twice more in the same world: internal ids written into prose because the persona was shown ids and had to be trusted not to use them, and reply threading pointed at whatever message the persona was last shown rather than at the thread root. **The test.** For every field an intent asks a persona to fill, ask what it would take to get it right. If the answer involves arithmetic on an epoch, resolving an identifier, or holding a structure the prompt never showed, the field is in the wrong place. Move the work to the referee and leave the persona the part a person actually does. Corollary worth its own line: **a validator that only catches the causally impossible is not enough here.** The one guarding those calendar starts refused negatives, dates before the run, and dates past any horizon — so the 2080 timestamp was caught and the 01:06 meeting was served. Bad output that lands inside the plausible range is exactly what this kind of defect produces. ## Realism of the served surface **Vendor parity constrains realism.** Adding *content* a real product would serve is a gain. Adding *tools* it would not is a loss wearing a gain's clothes: an agent trained against an invented tool learns a call that fails in the real product. When a surface cannot host your content, put the content where the real product would. **Artifacts must be the file types the institution actually exchanges.** A world whose every document is markdown is not the world it claims to model, and it quietly removes a whole class of work — opening a workbook, reading a deck, extracting a table from a PDF. Declare the real content format at emission (formatted document, slide deck, workbook, print form), not at render time, because the renderer can only produce what the event asked for. Then gate the resulting distribution: assert the share of each format directly, or the world drifts back to plain text one convenient default at a time. Formats also need to be *load-bearing*. A workbook whose only content is one flat table is markdown with extra steps; give it the multiple sheets, formulas, and cross-references the real artifact would have. ## Smoke the whole pipeline on one day before recording many Generating a long history is the most expensive step and the last one you can cheaply redo. Every gate downstream of it — coherence, the derived rebuild, artifact mix, whatever the world owes its tasks — reads something the recording produces, and none of them run until the recording is done. So record **one day**, export it, and run the entire downstream pipeline against it before starting the long window. Four separate defects were found this way in a single pass, each in minutes, each of which would have cost the whole recording had it surfaced at the end: a validator missing from one of three write paths, a bound that hid the shared codes everyone needs, a format the world could never produce because nothing gave anyone a reason to produce it, and a malformed document in the world's own definition. The last one is the sharpest argument for the practice. **It was a defect in the spec, not in the engine** — the seeded workbook folded its header into the data rows. It is valid JSON and reads correctly to a human, and the first thing that would ever have disagreed was the renderer, at materialization, at the very end. A one-day world costs a few minutes and exercises every stage. Order the work so the expensive irreversible step is the *last* thing you start, not the first. ## Surfaces must agree about who is busy Every per-surface gate asks whether a surface looks right ON ITS OWN. A generator that writes each surface independently passes all of them while describing four different firms. A firm's busiest person bills the most, sends the most mail, talks the most and touches the most documents. The volumes differ by orders of magnitude; the ORDERING does not. Check it with rank correlation over every pair. **Measured on a shipped world:** two surfaces agreed at **+0.747**, while a third sat at **−0.647** and **−0.603** against both of them. That third surface had been written without reference to who was actually busy. Six months of recording, five surfaces, found by hand while answering a question about whether the environment was saleable. **Check dispersion BEFORE correlating.** A surface where everybody did the same amount of work has no ordering, and correlating against it reads a coin flip as a finding. The first version of that check reported nine inverted pairs, five of them against a surface with a Gini of 0.059 — every person billing between 976 and 1083 entries. A flat surface is the worse defect of the two: no task keyed on who carries the work can be built on it at all. **Weight by work, not by rows.** Counting timesheet ROWS gave a Gini of 0.011; summing the SECONDS in them gave 0.059. Rows measure filing habits. ## Fidelity is measured, not asserted Commit distribution bands derived from published benchmarks for the domain — volumes, distribution shapes with anti-uniformity tests, concentration coefficients, seasonality, cross-surface correlation — and measure each world against them. Report three outcomes, not two. **ABSENT — the surface that metric measures does not exist in the world yet — is a finding, not a skip**, and the ABSENT column is the build worklist. Folding absent into pass hides everything you have not built; folding it into fail hides everything you have. ## Scale Longer histories are not automatically richer. What makes a long history worth generating is that it produces relations a short one cannot: things that recur, escalate, get handed over, lapse, and get corrected. If six months of generation produces six copies of one month, the extra cost bought nothing a task can grade.