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get_skeleton_blueprint

Get the recommended physics skeleton bone chain and hierarchy for a character based on type, tail, and leg configuration, including center of mass and ground contact.

Instructions

Get the recommended physics skeleton bone chain for a character.

Args: character_type: 'human', 'anthropo', 'quadruped', or 'cartoon' has_tail: Whether the character has a tail tail_length: 'none', 'short' (<20% body), 'medium' (20-60%), or 'long' (>60%) leg_type: 'plantigrade', 'digitigrade', or 'unguligrade'

Returns the complete bone hierarchy, center of mass placement, and ground contact definition.

Input Schema

NameRequiredDescriptionDefault
has_tailNo
leg_typeNoplantigrade
tail_lengthNonone
character_typeYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.5.0

TDQS

A3.6/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations at all, the description must carry the full behavioral burden. It discloses the return contents (bone hierarchy, center of mass, ground contact), which implies a pure read/lookup with no side effects, but never says so outright and says nothing about defaults or how the recommendation is derived. Useful but not complete for an annotation-free tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The one-line purpose is front-loaded, followed by a compact Args list and a single return sentence — no filler. The Google-style docstring formatting is slightly formal for a tool description but costs little and improves scannability.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

A four-parameter tool with an output schema; the description covers all parameters with concrete value sets, so it is nearly complete. Remaining gaps are the parameter defaults/interaction (tail_length vs. has_tail) and its position relative to sibling rig/locomotion tools.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% and there are no enums in the schema, so the description is doing real work: it enumerates the allowed character_type values, the three leg_type values, and even quantifies tail_length thresholds (<20%, 20–60%, >60% body). It omits the schema defaults (has_tail=false, tail_length='none', leg_type='plantigrade') and any note that tail_length is only meaningful when has_tail is true.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description leads with a specific verb+resource: 'Get the recommended physics skeleton bone chain for a character,' and names the concrete outputs (bone hierarchy, center of mass, ground contact). It does not explicitly distinguish itself from adjacent siblings like get_rig_constraints or classify_character, so it stops short of a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is only implied — an agent can infer this is the lookup to call when it needs bone chains for a character type, but there is no explicit when-to-use, when-not-to-use, or routing to alternatives such as get_rig_constraints or classify_character. No prerequisites or ordering guidance are stated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.