agentleFS
chapmanjwchapmanjw/minecraft-java-fabric-claude-plugin/skills/build-natural-world/SKILL.md

build-natural-world

Skill9 starsChanged 4 months agoMITView on GitHub

Orchestrates a primarily-natural landscape or region in a live Minecraft Java world — terrain, landforms, biomes, water, natural scenery, named natural wonders, and designed caves. Sequences the terrain leaf skills and threads one shared coherence context (one datum, one continuous recipe, one palette, one biome+scatter plan, one integration pass) so the result reads as one coherent place. Use for canyons, mountains, islands, coastlines, river valleys, forests, cave systems, and recreations of natural wonders. Tier-2 orchestrator.

The file

We split this skill into the rules it gives an agent

2 rules. About 0 are common, 2 are distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈2

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Run the spine (depth-scaled to the request — a small tweak is a shallow pass, the gates never drop):

    line 39
  2. Distinctive:

    After each leaf returns, check it against the shared context before advancing: terrain↔ecology (no forests on cliffs), region↔region (one …

    line 71

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

build-natural-world (Tier-2 orchestrator)

You are a specialty orchestrator: you do not place blocks or author terrain yourself — you run a domain playbook, invoking Tier-3 leaf skills in order and threading the shared coherence context between them so the pieces come together. You run inline (in the main thread) so each leaf still forks independently with its own model. Read ${CLAUDE_PLUGIN_ROOT}/reference/orchestration/coherence.md and ${CLAUDE_PLUGIN_ROOT}/reference/orchestration/workflow-spine.md first — they are the contract you enforce.

What you own (the coherence context)

Derive these once from the actual site and pass them into every leaf:

  • one datum / sea_level — the whole region works to it;
  • one continuous terrain recipe — terrain is ONE sampler-graph recipe.json, never independent regions butted together (regions blend by belt or sparse_convolution_blend); you forbid hand-authored fills;
  • one palette family and one biome + scatter plan for the whole region;
  • one integration plan — the footprint to ground into the surrounding world.

The playbook

Run the spine (depth-scaled to the request — a small tweak is a shallow pass, the gates never drop):

  1. survey-site — read the actual terrain/biomes/datum. Always.
  2. survey-research — if a named/real place (a specific canyon, coastline, wonder), pull ${CLAUDE_PLUGIN_ROOT}/reference/terrain/research.md facts first.
  3. exec-plan — resolve requirements into plan.toon (header carries the coherence context).
  4. shape — invoke the terrain author:
    • generic terrain/scenery → terrain-shape;
    • a recognizable named wonder → terrain-landmark;
    • designed caves/caverns/ravines → terrain-cave. It writes ONE recipe, runs the offline verify gate (GATE A), and emits the terrain phases. HALT and re-author if verify fails.
  5. terrain-ecology — plant communities/density over the finished heightfield+biome (skip for barren/rock-only).
  6. exec-blueprint — reusable mcb:* structure templates (terrain modules, boulders).
  7. exec-worker — execute the plan via the harness (columns/strata/fillbiome/ scatter ops). Verify every phase.
  8. terrain-integrate (GATE B) — ground the region's footprint into the surrounding world (apron erosion, biome blend). Required.
  9. exec-inspect (GATE C) — plan fidelity + quality_contract + the build↔world seam check at eye-level/iso (never top-down alone). On CORRECTIONS, route back to the owning leaf (a seam is a shape problem — never accept a colour patch). Reconcile: ecology must match the heightfield's actual slope/biome.
  10. register — you write mcbuilder:registry (sole writer), recording the recipe.json path + the integration apron.
  11. exec-reflect — drafted lessons; you persist them to memory.

Coherence reconciliation (catch the disjointedness)

After each leaf returns, check it against the shared context before advancing: terrain↔ecology (no forests on cliffs), region↔region (one continuous field), whole↔world (one integration pass). Mismatch → fix the owning leaf and re-run.

Closing a canyon/valley end is a region↔region continuity case, so route it back through the SAME generator that authored the walls — never a different per-column process. A headwall built from per-column random tops or per-column gully/notch reads as a vertical dripping curtain; a smooth formula bowl between rough eroded walls reads as pasted-in. The terrain-shape author closes the end with the same cross-section (walls converge / pinch shut), the same add_fbm sampled at GLOBAL coordinates (identical seeds, so the noise phase aligns at the seam), the same erode_thermal/erode_hydraulic, then the same materializer — see ${CLAUDE_PLUGIN_ROOT}/tools/terrain/close.py (close_belt_end). Reject any close that wasn't produced this way (it's a shape problem, not a colour patch), and clear the OLD structure's full prior extent first — it often reaches past where you think, including beyond the world border if it was force-loaded.

A user visual checkpoint is the gate for hero terrain; under autonomy, the eye-level exec-inspect pass is the minimum substitute. Never judge terrain from a top-down render alone.

Gate any expensive or hard-to-undo pass on an offline preview before it writes to the world: a re-materialize, a large recolor, an end-close, or any pass that has already failed once. Render it offline from the field/model (no world writes), get user sign-off, then place once. One previewed proposal turns a place-render-revert thrash into a single clean placement; it is far cheaper than the round-trip.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.