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AnkusDrive

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Python
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Feature Instantiate

feature_instantiate
Destructive

Stamp a registered feature template onto a host body using named references, validating inputs and resolving geometry before building the feature with interfaces and intent.

Instructions

Stamp a registered FEATURE TEMPLATE onto a host body at reference geometry supplied BY NAME (PowerCopy/UDF, issue #139) — e.g. a mounting_boss onto a published seat frame, or a bolt_pattern onto an f_ face tag. Validates {refs, inputs} at the door, resolves each reference against the host's CURRENT geometry (an f_ tag / interface name that doesn't resolve fails loudly), then runs the deterministic build — geometry + publish_interface + declare_intent.

template: registered template name (feature_list to browse). host: the handle of the body to stamp onto. refs: reference inputs by name — an interface name, an f_/e_ tag, or a literal {origin, z_axis?, x_axis?} frame, per the template's declared ref kinds. inputs: scalar parameters (typed + unit-bearing + range-checked).

Returns {template, schema, host, refs, inputs, handle, name, interfaces, intent}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
hostYes
refsNo
inputsNo
templateYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.8/5.0
Behavior5/5

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

Beyond the destructiveHint annotation, it reveals validation at the door, resolution against current geometry, loud failure on unresolved references, and the deterministic build steps: geometry + publish_interface + declare_intent. This gives an agent a solid model of side effects and failure behavior.

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

Conciseness5/5

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

The description is front-loaded with the core action, uses compact per-parameter definitions, and ends with an explicit return shape. The examples and issue reference add contextual value without padding.

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

Completeness5/5

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

With no output schema and bare schema property definitions, the description still covers every parameter, the return object, error behavior, and the overall workflow. It provides enough detail to invoke the tool correctly with minimal ambiguity.

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

Parameters5/5

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

The input schema has 0% description coverage, but the description fully compensates by defining each parameter: template as a registered name, host as a body handle, refs as named interfaces/tags/frames, and inputs as typed, unit-bearing, range-checked scalars.

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

Purpose5/5

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

The description opens with a specific verb and resource: 'Stamp a registered FEATURE TEMPLATE onto a host body at reference geometry supplied BY NAME'. It gives concrete examples and clearly differentiates instantiation from related siblings like feature_list and feature_validate.

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

Usage Guidelines4/5

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

The description clearly explains the intended workflow: browse templates via feature_list, supply a registered template name and host handle, and provide references/inputs. It does not explicitly list exclusions, but the context is specific enough to guide tool selection.

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

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