unity-physics-spatial

unity-physics-spatial is a skill for Claude Code, Codex from german-krasnikov/unity-biome-mcp. It costs 30 tokens per session (648 once invoked), scanned A, original, MIT.

A set of Unity workflows for configuring Rigidbody and collider components, checking physics, and analysing distances and raycasts. Unity is a game and interactive-app development engine.

In plain words
What is it for?
Adding and configuring rigidbodies and colliders, checking collisions, finding nearby objects, testing visibility with raycasts, validating trigger spacing, and checking NavMesh status.
Why use it?
It helps find missing or incorrect physics components and investigate how objects relate in space.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: reads .claude/ paths.

Good fit Adding and configuring rigidbodies and colliders, checking collisions, finding nearby objects, testing visibility with raycasts, validating trigger spacing, and checking NavMesh status.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/german-krasnikov/unity-biome-mcp/unity-physics-spatial
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add german-krasnikov/unity-biome-mcp --skill unity-physics-spatial
Clone the repo
git clone --depth 1 https://github.com/german-krasnikov/unity-biome-mcp

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for unity-physics-spatial

README.md
[![agentmods](https://agentmods.dev/badge/skills/german-krasnikov/unity-biome-mcp/unity-physics-spatial.svg)](https://agentmods.dev/skills/german-krasnikov/unity-biome-mcp/unity-physics-spatial)
Your own site
<a href="https://agentmods.dev/skills/german-krasnikov/unity-biome-mcp/unity-physics-spatial"><img src="https://agentmods.dev/badge/skills/german-krasnikov/unity-biome-mcp/unity-physics-spatial.svg" alt="Measured on agentmods" height="20"></a>
Per session 30 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 648 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 1 finding, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • medium Agent Snooping · line 9
    Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.
    Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00030 $0.00648
Opus 5 $0.00015 $0.00324
Sonnet 5 $0.00006 $0.00130
Haiku 4.5 $0.00003 $0.00065

Measured 8d ago against content hash 2407feb0a445, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

unity-physics-spatial scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

unity-plugin/ClientSkills/skills/unity-physics-spatial/SKILL.md · 92 lines

How it starts

The opening of the file, as written. The whole thing — 92 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Unity Physics And Spatial Analysis

If it is not already loaded, read .claude/skills/unity-mcp-operations/SKILL.md once. Use scene-authoring tools for component mutation. Enable SCENE for spatial analysis and RUNTIME for Play Mode diagnostics.

Setup

batch(
  commands="""
manage_component path=/Crate type=Rigidbody action=add
manage_component path=/Crate type=BoxCollider action=add
set_property path=/Crate component=Rigidbody prop=mass value=5
set_property path=/Crate component=Rigidbody prop=useGravity value=true
get_component path=/Crate type=Rigidbody
get_component path=/Crate type=BoxCollider
""",
  on_error="stop",
  atomic=True
)
check_colliders(path="/Crate")

For several objects:

configure_objects(config="""
/CrateA Rigidbody.mass=5
/CrateB Rigidbody.mass=8
""")

Spatial Checks

get_spatial_context(path="/Crate", radius=5)
spatial_query(action="nearest", path="/Crate", component="Collider")
spatial_query(action="raycast", path="/Camera", target="/Crate")
validate_triggers(root="/Gameplay", min_distance=2)

navmesh_query is a standalone tool and may report that AI Navigation is not installed:

navmesh_query(action="status")
navmesh_query(action="get_settings")
navmesh_query(action="set_settings", agentRadius=0.4, agentHeight=1.8, agentClimb=0.4, agentSlope=45.0)
navmesh_query(
  action="path",
  from_pos="(0,0,0)",
  to="(12,0,8)"
)

Use sample before path claims when endpoints may be off-mesh. Use get_settings and set_settings to inspect and configure agent types. Treat bake and clear as explicit project mutations, not read-only analysis.

For bounded cleanup or placement regions, preview first:

region_clear(
  vertices="0,0;10,0;10,10;0,10",
  filter="Temporary",
  dry_run=True,
  cap=50
)

Apply only after the preview count and object list match the requested scope.

Rules

  • Read Transform, Rigidbody, and collider data before editing.
  • Confirm Edit Mode versus Play Mode before interpreting physics state.
  • Use bounded runtime waits; never sleep and assume settling completed.
  • Validate negative scale, trigger/Rigidbody relationships, and collider size.
  • Use autofit_collider only after confirming the intended renderer bounds.
  • Treat screenshots as spatial presentation evidence, not collision proof.
  • Read back mass, constraints, trigger state, and bounds after changes.

Read the full file on GitHub · 92 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 8d ago First seen · 92 lines · 30 tokens per session scan A 2407feb0a445

Subscribe to this mod's changes

unity-physics-spatial is a skill published in the GitHub repository german-krasnikov/unity-biome-mcp (29 stars, last pushed today), licensed MIT. It adds 30 tokens to every session and 648 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other skills, from other repositories

roblox-performance

Use when profiling Roblox performance or diagnosing FPS, memory, network, mobile, or hot-path problems.

TabooHarmony/roblox-brain · 24 tokens

jahro-troubleshooting

Diagnoses common Jahro issues using decision trees: commands not appearing, watcher not updating, console not opening, snapshots failing, launch button missing. Use when the user reports something not working, missing, broken, or unexpected with Jahro, or when generated Jahro code doesn't behave as expected.

jahro-console/unity-agent-skills · 65 tokens

jahro-watcher

Analyzes C# fields and properties and generates [JahroWatch] attributes with groups and performance-safe patterns. Use when the user wants to monitor variables at runtime, add watchers, track game state, replace Debug.Log polling, or mentions JahroWatch, real-time inspection, or variable monitoring.

jahro-console/unity-agent-skills · 65 tokens

jahro-production

Configures Jahro lifecycle controls for safe production deployment including JAHRODISABLE, auto-disable, and build validation. Use when the user mentions production builds, release builds, disabling Jahro, shipping, CI/CD, lifecycle controls, or production safety.

jahro-console/unity-agent-skills · 54 tokens

mosaic-shader

Ray — Mosaic Bridge shader expert. Use for ShaderGraph creation, node wiring, HLSL shader writing, shader debugging, and render pipeline shader issues. Use when the user says "create a shader", "ShaderGraph", "Voronoi", "water shader", or "shader is not compiling".

MosaicXR-AI/mosaic-bridge · 66 tokens

godot-auditor

Godot Expert Auditor: Aurelius. Exhaustive never-list enforcement and architectural slap-down for Godot 4.7 projects.

bgrenat/godot-game-dev-studio · 32 tokens