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Mipiti
by Mipiti

split_composition_entity

Split an ancestor-owned entity down to selected descendant models, duplicating attached state and soft-deleting the original. Use when an entity is descendant-specific.

Instructions

Push an ancestor-owned entity down to one or more descendants and soft-delete the ancestor's copy. Mutates state across the ancestor + every target descendant.

Inverse of lift_composition_entity. Use when an entity that currently lives on an ancestor is in fact descendant-specific and should be modeled separately per descendant — the operator chooses which descendants take a copy. A new local id is minted on each target; attached state on the ancestor's entity (assertions, jira mappings, risk acceptances, etc.) is duplicated to every target.

The route's model_id IS the ancestor (the entity being split lives on it). Each affected model (ancestor + every target descendant) bumps version and emits a model_refined activity event; a structured split_applied event with the full split_event payload lands on the ancestor. The audit pack surfaces this under split_history.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindYesEntity kind — one of ``"assets"``, ``"attackers"``, ``"components"``.
model_idYesAncestor model id — the entity to split lives here.
server_versionYes
ancestor_local_idYesLocal id of the entity on the ancestor.
target_descendantsYesNon-empty list of descendant model ids that should each take a copy.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

With no annotations provided, the description carries full burden and delivers. It details mutations (soft-delete, duplicate state, new local ids), version bumps, activity events (model_refined, split_applied), and audit tracking (split_history). This is rich behavioral disclosure.

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 three well-organized paragraphs. The first sentence is a clear action summary; the second adds usage context; the third covers technical route details. Every sentence earns its place, with no wasted words.

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?

For a complex mutation tool with no annotations, the description covers purpose, usage, behavioral effects, event emissions, and audit visibility. An output schema exists, so the lack of return-value details is acceptable. This is a thorough and self-sufficient description.

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 coverage is high (80%), so baseline is 3. The description adds value by clarifying that 'model_id IS the ancestor' and that target_descendants 'each take a copy,' plus explains the creation of new local ids and duplication of attached state. This goes beyond the schema's field descriptions.

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 action: 'Push an ancestor-owned entity down to one or more descendants and soft-delete the ancestor's copy.' This clearly identifies the verb, resource, and key side effect. It also distinguishes itself from siblings by explicitly stating it is the 'Inverse of lift_composition_entity.'

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

Usage Guidelines5/5

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

The description provides explicit usage guidance: 'Use when an entity that currently lives on an ancestor is in fact descendant-specific and should be modeled separately per descendant.' It also names the inverse tool (lift_composition_entity) as an alternative, giving a clear when-to-use vs. when-not-to-use context.

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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