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  "finished": "2026-09-25T16:25:08",
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    "cli": "codex exec --skip-git-repo-check --dangerously-bypass-approvals-and-sandbox -m gpt-6-astra -c model_reasoning_effort=\"xhigh\" --image=/work/generator/workspace/reference_mediterranean_villa.jpg --image=/work/generator/workspace/reference_merchant_manor.jpg --image=/work/generator/workspace/reference_red_roof_farmstead.jpg --image=/work/generator/workspace/reference_root_house.jpg --image=/work/generator/workspace/reference_sandstone_cottage.jpg --image=/work/generator/workspace/reference_stilted_manor.jpg --image=/work/generator/workspace/reference_stilt_water_cabin.jpg --image=/work/generator/workspace/reference_stone_cottage.jpg -- # Task: Shared Procedural Architecture and Validation Library\n\nBuild a reusable Python library for generating and validating furnished Minecraft Java 1.21.1 buildings\nand their immediate sites. Users must be able to write short, high-level client programs that compose the\nlibrary's abstractions to generate a wide variety of complete, attractive, logically sound buildings.\nThe eight `exp8` references below establish the intended architectural range and quality bar.\n\nThe main deliverable is the shared generation and validation library, together with lightweight example\nclients, generated samples and tests. The library may be large and sophisticated. User code must remain\nsmall, readable and architectural: it describes what to build, while the library handles how to realize\nand verify it. Users explicitly control the seed.\n\nDo not introduce a building-family selector, a reference-name dispatch API, or an eight-preset generator.\nThe references are examples from which to derive reusable abstractions, not an enumeration of supported\nbuilding types. A new building should be expressible by a new composition of the public API, without\nadding a named building type or editing the library's core dispatch logic.\n\nMaximize the variety of buildings expressible through these compositions and their seeded parameter\nchoices, while keeping generated samples within the reference distribution and satisfying the quality\nrequirements below. One example invocation produces one dwelling or coherent property, such as a\nfarmhouse with its farmyard. A thin `generate.py` client must preserve the harness contract: running it\nwithout arguments produces `output.litematic`.\n\n## Eight references\n\nExactly one final generator from each named `runs/exp8` run is supplied:\n\n| Reference | Source code | Original reference image |\n| --- | --- | --- |\n| mediterranean-villa | `references/mediterranean-villa/generate.py` | `reference_mediterranean_villa.jpg` |\n| merchant-manor | `references/merchant-manor/generate.py` | `reference_merchant_manor.jpg` |\n| red-roof-farmstead | `references/red-roof-farmstead/generate.py` | `reference_red_roof_farmstead.jpg` |\n| root-house | `references/root-house/generate.py` | `reference_root_house.jpg` |\n| sandstone-cottage | `references/sandstone-cottage/generate.py` | `reference_sandstone_cottage.jpg` |\n| stilt-water-cabin | `references/stilt-water-cabin/generate.py` | `reference_stilt_water_cabin.jpg` |\n| stilted-manor | `references/stilted-manor/generate.py` | `reference_stilted_manor.jpg` |\n| stone-cottage | `references/stone-cottage/generate.py` | `reference_stone_cottage.jpg` |\n\n`references/README.md` records provenance and SHA-256 hashes. These are the exp8 building references,\nnot the ref-1 through ref-8 lodge set. Inspect all eight generators and images before choosing your\nprocedural design. Images establish intended appearance; source code supplies implementation examples.\nHidden sides and interiors must be complete. Text overlays, logos and presentation borders in the images\nare not architectural features to reproduce.\n\nThis distribution contains several distinct architectural families, not one uniform lodge style:\n\n- **Mediterranean villa:** white plaster, blue or turquoise accents, tiled roofs at different heights,\n  offset volumes, upper and lower terraces, open pergolas and a garden pool. The image includes furnished\n  floor plans. Learn their circulation and domestic room relationships without freezing their exact layout.\n- **Merchant manor:** a stone undercroft, an elevated entrance terrace and exterior stair, timber and pale\n  infill above, steep dark roofs, tower or spire accents, and a market stall with trading and storage spaces.\n- **Red-roof farmstead:** a timber farmhouse with a steep red roof and pale trim, dormer or cupola details,\n  a furnished loft, and a composed working plot with a path, well shelter, fields and a small windmill.\n- **Root house:** an organic dwelling integrated into a hill and spreading dark timber roots. Vary the\n  trunk and root silhouette, exposed stone, entrance recess and hollowed room layout. It must read as an\n  inhabited root formation, not a conventional rectangular house with decorative logs attached.\n- **Sandstone cottage:** a broad pale roof with dark timber ridge and eaves, framed walls and a projecting\n  entrance bay, a stair climbing the slope, a partly buried lower floor, and a waterside approach or jetty.\n- **Stilt water cabin:** a compact timber dwelling raised on posts over visible shallow water, a low\n  overhanging gable, a railed deck, steps to a landing and a mooring, with a functional fishing cabin interior.\n- **Stilted manor:** a recessed stone ground floor, a genuinely overhanging timber upper floor carried by\n  posts and braces, tall windows, a very steep roof, dormers and a cupola, with usable stacked interiors.\n- **Stone cottage:** a small, restrained stone-and-timber dwelling with a simple pale gable, recessed entry,\n  framed windows and planters, a furnished main room and an optional usable loft. Preserve compact examples.\n\nKeep scale, proportions and detail comparable to the relevant references. A compact cottage should remain\ncompact; a manor may be taller and more complex. Preserve the distinction between posts over water and\nposts supporting an overhanging manor, and between an earth-sheltered home and an ordinary masonry cellar.\n\nUse the supplied code as implementation reference. You may reuse and adapt useful geometry routines,\nbut extract a coherent library of parameterized rules and components. All eight references must inform\nthe library's capabilities. Demonstrate their architectural characteristics with lightweight compositions\nof the same public API, and demonstrate new compositions beyond those eight examples.\n\nChoose abstractions that separate architectural intent from geometric implementation. Possible concepts\ninclude sites and terrain relationships, connected volumes, levels, room programs, circulation constraints,\nenvelopes, roof systems, support systems, attachments, material roles and furnishing policies. Users should\ncombine such concepts rather than choose a complete building by name. Specialized geometry algorithms for\nroots, pitched roofs, earth sheltering or stilt supports are appropriate reusable capabilities.\n\nFor example, a client could describe connected volumes on a slope, assign living and workshop spaces,\nrequest a pale pitched roof and a supported waterside deck, then generate and validate with a chosen seed.\nAnother client could compose a recessed masonry base, an overhanging timber level and a steep roof with\nusable attic space. The library must resolve dimensions, joins, supports, openings, stairs, furnishing and\nclearance. These describe API intent, not required class names or a prescribed framework.\n\nCompositions must remain architecturally coherent. Do not require arbitrary feature mixing or put every\nmotif in every sample. Preserve the references' different identities, proportions and scales through\ncomponent rules and constraints, without encoding each whole reference as a hidden fixed-building script.\n\nThese are historical snapshots, not certified correctness examples. Fix any defects you reuse. In\nparticular, MCIO may reorder blockstate properties on reload. Compare parsed block names and property\nmappings using the standard toolset's `blockstates_equivalent` helper when available. Raw string comparison\ncan report `changed on reload` even after a single write. Overwriting a coordinate is valid when its final\nstate is correct. Ignore property order only; changed names, values or explicit property sets must still fail.\n\n## Objective: maximize valid architectural variety\n\nThe quantity to maximize is the number of meaningfully different, valid building types expressible by the\nlibrary's high-level compositions and parameter combinations. Think of the product of the choices across\ndesign parameters, subject to their compatibility constraints. This space may be astronomically large.\nDo not calculate, estimate,\nenumerate, or report its total size. Spend effort expanding the actual generative system instead.\n\nPrioritize diversity in building structure and layout:\n\n- Footprint topology, connected wings, their relative placement and proportions, setbacks and asymmetry.\n- Floor counts, relative wing heights, towers, attics, and the hierarchy of major and minor volumes.\n- Roof topology, ridge directions, pitch and profiles, cross-gables, dormers and their placement.\n- Entrance position, circulation routes, stairs, room subdivision, adjacency and functional allocation.\n- Porches, balconies, pergolas, decks, terraces, market stalls and other compatible extensions.\n- Root and hill envelopes, recessed or overhanging storeys, stilt arrangements and water relationships.\n- Site organization: paths, farmyards, fields, wells, windmills, pools, landings and working outdoor spaces.\n- Terrain relationships, foundations, retaining work, height transitions and the exterior approach.\n\nMaterial families, color choices, weathering, planting and decorative variations also contribute, but have\nlower priority than structure and layout. Preserve harmonious palettes and appropriate detail density.\nDifferent seeds, names, unused parameters, duplicate presets, global rotations or translations alone do\nnot establish additional architectural types. Texture noise on the same building is only minor variety.\nSimply making dimensions unbounded is not useful diversity: retain the references' human scale and quality.\n\nIntroduce parameters that change real geometry and can combine across multiple architectural decisions.\nMake their domains and dependencies explicit. Independent choices multiply variety only when their\ncombinations remain valid. Use conditional domains and geometric constraints for dependent choices rather\nthan pretending every combination is compatible. Broaden the feasible design space instead of claiming\ncombinations the implementation cannot produce.\n\nThe public API must support both explicit architectural decisions and bounded seeded choices for\nunspecified or intentionally variable decisions. A lightweight client should be able to define a design\nspace, not merely one fixed building with random texture. Seeded generation must exercise structural\nchoices within that client's declared constraints; it must not silently discard explicit user intent.\nDocument sampling domains and compatibility rules. The example collection must explore the breadth of\nthe eight references and new coherent combinations, without relying on a family-selection switch.\n\n## Public API and lightweight client code\n\n- Provide an importable Python package with a documented public API for design composition, seeded\n  generation, validation and export. Calling it must not require the harness CLI or reference scripts.\n- Users express architectural intent: spatial relationships, room functions, scale or proportion ranges,\n  roof and support rules, site conditions and desired extensions. Avoid requiring absolute block coordinates,\n  voxel placement loops, blockstate manipulation, geometry repair or NBT handling in ordinary client code.\n- Put substantive planning, constraint resolution, geometry, furnishing and correctness checks in the\n  shared library. Client programs should mostly declare a design and call generation, validation and export.\n  Do not hide long building-specific implementations in example helper files and call the entrypoint thin.\n- Keep client code genuinely lightweight, but do not code-golf or impose an arbitrary line-count target.\n  Favor a few understandable architectural declarations with sensible defaults over huge configuration\n  dumps, opaque serialized plans or a parameter list that exposes every internal implementation detail.\n- A short call that selects a prebuilt house is not sufficient abstraction. The API must let users compose\n  new spatial arrangements and combine reusable capabilities without rewriting geometry or validators.\n- Validation is a reusable public library capability, not assertions embedded in the example clients.\n  It must inspect a generated build and its relevant design constraints and return useful diagnostics,\n  including failed rules and affected components or locations. Support validation of reloaded exports\n  with explicit design metadata where needed; do not rely on hardcoded coordinates for individual examples.\n- Make extension points clear: adding a reusable component or rule should integrate with shared planning,\n  spatial reservations and validation. Choose abstractions that actually serve the supplied and novel\n  examples; an elaborate framework with weak generated results does not satisfy the task.\n\n## Program design\n\nDo not optimize for library code length or worry about how many files or lines its implementation needs.\nWrite as much shared implementation as the result requires, while keeping user programs high-level and\nlightweight. Judge success by the generated buildings' quality, correctness and diversity across seeds.\nThe code must still follow procedural design principles and remain extensible:\nuse reusable rules, parameterized geometry, explicit constraints and clear module responsibilities so new\nbuilding types and features can combine with existing ones. More code is acceptable when it improves the\nresults, but a growing collection of hardcoded buildings or seed-specific exceptions is not a procedural\nsolution. Do not sacrifice output quality to keep the implementation short.\n\nUseful architectural patterns to consider, combine or adapt:\n\n- A compiler-style pipeline: a high-level user specification and seed -> a resolved building plan ->\n  structural geometry -> Minecraft blocks -> validation and export. Keep architectural intent, planning\n  decisions and block placement separate, and retain enough metadata for diagnostics and reproduction.\n- A constrained building grammar: compose main volumes, wings, towers, roof systems and extensions through\n  parameterized rules with compatibility conditions, drawing design patterns from all eight references.\n- A compositional architectural API or small embedded DSL: clients describe relationships and constraints,\n  while reusable rules infer the detailed geometry. Support both concrete choices and bounded variation.\n- A shared component protocol: reusable roofs, root envelopes, supports and terrain adapters declare their\n  inputs, attachment interfaces and validity rules, so users can combine capabilities without selecting a\n  whole-building family or duplicating fixed-building scripts.\n- A room and circulation graph: plan room adjacency and vertical connections alongside the exterior massing,\n  then realize and verify those connections in actual geometry.\n- Parameterized components with connection interfaces: roofs, stairs, porches and towers declare their\n  attachment points, occupied space, support requirements and clearance needs.\n- A shared spatial reservation system: protect passages, doorways, windows and stair headroom so later\n  roof, furnishing and decoration passes cannot obstruct them.\n- Local constraint solving or bounded candidate refinement: resolve difficult layout and roof interactions\n  at the planning level before committing to detailed block placement.\n\nThese are suggestions, not a required framework or a checklist of abstractions. Choose a structure that\nsupports a broad, coherent design space and makes quality across samples easier to achieve and extend.\n\n## Library and harness contract\n\n- `python generate.py` is a lightweight example client that uses the public library API to generate,\n  validate and export one region to `output.litematic` using a documented default seed.\n- `python generate.py --seed INTEGER --output PATH` generates a reproducible sample at the requested path.\n- Every example client lets the user supply a seed and uses the same shared generation and validation API.\n  The default client does not need to represent the entire design space by itself; the library and its\n  composable API must support the breadth demonstrated across clients.\n- Record each sample's client or design specification, seed and resolved architectural choices so the\n  result can be inspected and reproduced. Document parameter domains and how users express relationships,\n  constraints and seeded variation in their own code.\n- Use seeded randomness for every random decision. The same seed and configuration must reproduce the\n  same geometry and schematic bytes in the same environment. Follow the toolset's deterministic export rules.\n- Derive bounds from the chosen design, including roofs, terrain, trees and other exterior features. Keep\n  parameter domains and resource limits explicit and configurable. Never silently clip a building.\n- Generation must work for arbitrary seeds in the documented seed domain, without seed-specific patches,\n  manual repairs or a list of handpicked successful seeds. Reject invalid explicit parameter combinations\n  with a clear explanation. For a supported, satisfiable client specification, the library's sampler must\n  produce valid configurations within that specification's constraints.\n- Resolve compatibility during planning and construction. If retries are needed, bound them and provide\n  a valid deterministic recovery strategy. Do not hang, emit broken buildings, or silently fall back to the\n  same fixed building for most seeds. Do not silently change the user's architectural requirements to\n  recover from failure; reject contradictory specifications with actionable diagnostics.\n- Reused implementation should live in the delivered library modules. Running the finished clients must\n  not depend on dispatching to the eight reference scripts or downloading additional assets.\n\n## Quality required for every sample\n\nTreat architectural quality and correctness as constraints on the design space, not costs to trade away\nfor more parameter values. Every admitted combination and every sampled build must satisfy them.\n\nArchitecture and aesthetics\n\n- Preserve the relevant references' recognizable architecture, balanced proportions and composed\n  silhouettes. Frame, infill, foundation, roof, roots and terrain materials must have coherent roles.\n- Join wings, roofs and extensions intentionally. Roof intersections must be weather-tight, with sensible\n  eaves and no accidental holes or protrusions through occupied rooms.\n- Align openings and framing with usable rooms. Keep a clear entrance, believable supports and continuous\n  foundations. Balance exterior detail, planting and negative space.\n- Give all enclosed usable levels and rooms purposes and complete furnishings: sleeping, living, cooking,\n  storage, work or other functions appropriate to that dwelling. Layout must respond to the sampled building.\n- Compose the whole property: farmyard elements, market spaces, terraces and docks need appropriate space,\n  access and visual hierarchy. An open pergola is distinct from an enclosed roof; a windmill needs clear\n  space for its sails; roots and earth must leave a usable, sealed interior. Site features must adapt to\n  the plan rather than occupying identical fixed coordinates in every sample.\n\nGeometry and usability\n\n- Use valid vanilla Java 1.21.1 blocks and blockstates, entirely within the schematic bounds.\n- Every room and occupied level is reachable from the exterior entrance through a continuous walkable\n  route. Maintain at least two blocks of headroom, including over stair treads and at transitions.\n- Stairs or ladders must be usable and supported. Exterior paths and stairs must connect actual ground to\n  the entrance. For water sites, provide an accessible landing and a continuous usable deck route to the\n  door. Terrain, terraces, supports and foundations must meet without floating joins. Stilt supports must\n  reach the waterbed or ground, overhangs must be supported, and water or hillside material must not invade rooms.\n- Doors have matching upper and lower halves. Beds have adjacent matching heads and feet. Respect facing,\n  attachment and support requirements for all multi-block furnishings and decorations.\n- Keep circulation, doors and windows clear of furniture, roofs, chimneys and later decoration passes.\n- Enclosed interiors must be weather-tight, with deliberate glazed windows and complete doors. Intentional\n  open porches, balconies and exterior spaces remain distinct from enclosed rooms.\n- Light every room near its usable floor, and provide coherent exterior lighting along the approach and\n  around important features.\n\n## Validate the system across its design space\n\nDo not validate only the default client or the easiest composition. Choose a finite, diverse seed corpus\nand targeted client specifications that cover every major architectural capability, domain boundaries and\ndifficult component interactions.\nExpand or repair the generator when these reveal failures. This is sampled and targeted validation, not\nan exhaustive enumeration of the parameter space or proof that all combinations were tested.\n\n- Write `test/test_*.py` tests for the public API and shared validators: determinism, bounds, valid states,\n  support and multi-block consistency, room and level reachability, headroom, envelope integrity and clear\n  openings. Exercise the same library through multiple independent lightweight clients.\n- Verify that validators reject deliberately broken geometry, such as blocked stairs, unsupported features\n  and mismatched door halves, with meaningful diagnostics. Passing checks on valid examples alone does not\n  show that the validation library detects defects.\n- Demonstrate API composition by adding new lightweight clients after the shared abstractions are in place,\n  combining existing capabilities into buildings beyond the eight references without changing library code.\n  Check that these clients need no custom geometry routines, validator copies or block-level repairs.\n- Check actual placed or reloaded geometry. Declared room connections or planned stairs alone do not prove\n  the final blocks are traversable after roofs and furnishing have been placed.\n- Compare round trips semantically, ignoring property order while detecting changed names or properties.\n- Check structural diversity in the sampled corpus using actual massing, roof or room-layout signatures.\n  Include variation across seeds of one client specification and across distinct client compositions.\n  Different client names alone are not evidence of procedural variation. Exclude material noise and\n  incidental vegetation from structural signatures. Distinct seeds or file hashes alone do not prove\n  architectural variety. Report only observed\n  sample diversity, never a speculative total number of possible buildings.\n- Supply a lightweight client composition demonstrating the architectural characteristics of each of the\n  eight references, with at least two seeds per client producing meaningful structural or layout changes.\n  Also include novel compositions using the same library. Cover compact and large examples, difficult roof\n  joins, roots around rooms, buried floors, stilt supports and indoor/outdoor circulation with targeted cases.\n- Render a representative spread covering all eight references and novel compositions from multiple\n  exterior views, with cutaways for interior circulation and furnishing. Inspect the images and fix visible problems. Do not\n  present only cherry-picked successful builds while leaving reproducible failures unresolved.\n- Keep tests bounded and repeatable. Temporary test artifacts belong under `test/` and must be cleaned up.\n\n## Deliverables\n\nAll inside `/work/generator/workspace`:\n\n- An importable Python package: the shared procedural generation and validation library. Choose a clear\n  package name and module structure. Keep the public architectural API separate from implementation details.\n- `generate.py`: a lightweight default client using that public API, rerunnable from a clean directory with\n  the library available as documented. The standard toolset seeds a writable `generate.py` with placement,\n  export and reload helpers; move reusable implementation into the library as needed.\n- `examples/`: lightweight, runnable client programs demonstrating all eight reference architectures and\n  additional new compositions. Each accepts a user-controlled seed. They must demonstrate the actual public\n  abstractions rather than call hidden whole-building presets. Provide batch generation instructions.\n- `output.litematic`: the default client's default-seed build. This exact path remains the harness contract.\n- `GENERATOR.md`: library quickstart, public API, short client examples, parameter domains and dependencies,\n  seed and sampling behavior, validation API and diagnostics, extension points and design rationale.\n  Explain how the eight references motivated reusable abstractions and how users compose new buildings\n  without modifying the library. Include validation commands and known limitations. Do not compute the\n  total combination count.\n- `samples/`: a finite, representative collection of generated builds, with client/specification, seed and\n  resolved parameters recorded in a manifest. Provide a rerunnable command or script for the sample batch.\n- `test/test_*.py`: passing tests covering the public library, shared validators and varied client compositions.\n- `previews/`: labeled exterior renders and cutaways for representative samples.\n\nSpend the budget on the shared library, clear abstractions, lightweight clients, valid architectural\ndiversity, renders and tests. Do not spend it enumerating parameter products. State plainly what is\ncomplete and what remains unfinished.\n\nEnvironment, available libraries and rendering tools are described in the workspace `AGENTS.md`.",
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