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Variations

Manage variations of an agent and their tool, sub-agent, and memory layer assignments.

List variations
agents.variations.list(agent_id, **kwargs) -> CursorPagination<AgentVariation { metadata, spec, info } >
GET/v1/workspaces/{workspaceId}/agents/{agentId}/variations
Create a new variation
agents.variations.create(agent_id, **kwargs) -> AgentVariation { metadata, spec, info }
POST/v1/workspaces/{workspaceId}/agents/{agentId}/variations
Get a variation by ID
agents.variations.retrieve(id, **kwargs) -> AgentVariation { metadata, spec, info }
GET/v1/workspaces/{workspaceId}/agents/{agentId}/variations/{id}
Delete a variation
agents.variations.delete(id, **kwargs) -> void
DELETE/v1/workspaces/{workspaceId}/agents/{agentId}/variations/{id}
Update a variation
agents.variations.update(id, **kwargs) -> AgentVariation { metadata, spec, info }
PATCH/v1/workspaces/{workspaceId}/agents/{agentId}/variations/{id}
Add an assignment to a variation
agents.variations.add_assignment(variation_id, **kwargs) -> VariationAssignment { id, agent, tool, tool_set }
POST/v1/workspaces/{workspaceId}/agents/{agentId}/variations/{variationId}/assignments
Remove an assignment from a variation
agents.variations.remove_assignment(id, **kwargs) -> void
DELETE/v1/workspaces/{workspaceId}/agents/{agentId}/variations/{variationId}/assignments/{id}
Attach a memory layer to a variation
agents.variations.add_memory_layer(variation_id, **kwargs) -> VariationMemoryLayerAssignment { id, memory_layer, position }
POST/v1/workspaces/{workspaceId}/agents/{agentId}/variations/{variationId}/memory_layer_assignments
Update a variation's memory layer assignment
agents.variations.update_memory_layer(id, **kwargs) -> VariationMemoryLayerAssignment { id, memory_layer, position }
PATCH/v1/workspaces/{workspaceId}/agents/{agentId}/variations/{variationId}/memory_layer_assignments/{id}
Remove a memory layer assignment from a variation
agents.variations.remove_memory_layer(id, **kwargs) -> void
DELETE/v1/workspaces/{workspaceId}/agents/{agentId}/variations/{variationId}/memory_layer_assignments/{id}
ModelsExpand Collapse
class AgentVariation { metadata, spec, info }

AgentVariation resource

metadata: ResourceMetadata { id, account_id, created_at, 6 more }

Standard metadata for persistent, named resources (e.g., agents, tools, prompts)

id: String

Unique identifier for the resource (prefixed ULID, e.g., “agent_01HXK…”)

account_id: String

Account this resource belongs to for multi-tenant isolation (prefixed ULID)

created_at: Time

Timestamp when this resource was created

formatdate-time
name: String

Human-readable name for the resource (e.g., “Customer Support Agent”, “Email Tool”) Required for resources that users interact with directly

profile_id: String

ID of the actor (user or service account) that created this resource

workspace_id: String

Workspace this resource belongs to for organizational grouping (prefixed ULID)

bundle_key: String

Optional bundle ownership key. When set, indicates the resource is managed by a configuration bundle identified by this key. Used by BulkWorkspaceResources.Apply to track which resources belong to which bundle for reconciliation / soft-delete on re-apply.

external_id: String

External ID for the resource (e.g., a workflow ID from an external system)

labels: Hash[Symbol, String]

Arbitrary key-value pairs for categorization and filtering Examples: {“environment”: “production”, “team”: “platform”, “version”: “v2”}

spec: AgentVariationSpec { compaction_config, constraints, description, 6 more }

AgentVariationSpec defines the operational configuration for a variation

compaction_config: AgentVariationSpecCompactionConfig { summarization, tool_result_clearing, trigger_threshold }

CompactionConfig defines how context window compaction behaves for objectives using this variation.

summarization: CompactionConfigSummarizationStrategy { instructions }

SummarizationStrategy configures LLM-powered summarization of older conversation turns.

instructions: String

Custom instructions that guide what the summarizer preserves. Replaces the default summarization prompt entirely. Example: “Preserve all code snippets, variable names, and technical decisions.”

tool_result_clearing: CompactionConfigToolResultClearingStrategy { preserve_recent_results }

ToolResultClearingStrategy configures clearing of older tool result content.

preserve_recent_results: Integer

Number of most recent tool call results to keep intact. Older tool results have their content replaced with “[result cleared]” while preserving the assistant tool call message (function name, arguments). Default: 2

formatint32
trigger_threshold: Float

Trigger threshold as a percentage of the model’s context window (0.0 to 1.0). When input tokens reach this percentage of the model’s limit, compaction triggers. Default: 0.75 (75%)

formatfloat
constraints: AgentVariationSpecConstraints { max_sub_objectives, max_tool_calls }

Execution constraints

max_sub_objectives: Integer

The maximum number of sub-objectives that can be created. 0 means no limit.

formatint32
max_tool_calls: Integer

The maximum number of tool calls that can be made. 0 means no limit.

formatint32
description: String

Human-readable description of what this variation does or when it should be used

enable_episodic_memory: bool

Enable episodic memory for objectives using this variation. When true, the system automatically creates a document namespace for each objective using the objective’s episodic_key as the external_id, allowing the agent to store and retrieve documents specific to that episode.

episodic_memory_ttl: Integer

How long episodic memories should be retained. After this duration, episodic document namespaces can be automatically cleaned up. If not set, episodic memories are retained indefinitely.

model_config: AgentVariationSpecModelConfig { model_id, temperature }

ModelConfig defines the model configuration for a variation

model_id: String

The model identifier in family/model format (e.g., “claude/opus-4.6”, “claude/sonnet-4.5”)

temperature: Float

Sampling temperature for model inference (0.0 to 1.0) Lower values produce more deterministic outputs, higher values increase randomness

formatfloat
progressive_discovery: AgentVariationSpecProgressiveDiscovery { hints, max_tools, rerank_threshold }

ProgressiveDiscovery is used to indicate that the agent should automatically discover tools that are not explicitly assigned to it. Max tools is the maximum number of tools that can be discovered per search. Hints are optional hints for tool search. These are used in conjunction with the context-aware tool search and can help select the best tools for the task.

hints: Array[String]
max_tools: Integer
rerank_threshold: Float

Rerank Threshold is an optional value that instructs whether or not to run a search result through a embedding/reranker process which can improve performance and reduce context bloat when tools reach the configured threshold. If a tool match must exceed 0.8, for example, the tool very closely match the query the tool search performed.

formatfloat
prompt: String

The system prompt for this variation

weight: Integer

Weight for weighted random selection (>= 0). P(v) = v.weight / sum(all_weights). Only used when the agent’s variation_selection_mode is WEIGHTED. A weight of 0 means never auto-selected, but can still be chosen explicitly via variation_id on CreateObjectiveRequest.

formatint32
info: AgentVariationInfo { assignments, created_by, feedback_count, 7 more }

AgentVariationInfo provides read-only summary information about a variation

assignments: Array[VariationAssignment { id, agent, tool, tool_set } ]

All tools, tool sets, and sub-agents assigned to this variation. Populated on reads so clients can render a variation’s full assignment list without calling the add/remove endpoints just to enumerate.

id: String
agent: BareMetadata { id, name }

BareMetadata contains the minimal metadata for a resource: the ID and an optional human-readable name. These are used for reference fields where the full metadata (account scoping, timestamps, labels, external IDs) is not needed — e.g., the tool references inside an agent variation spec or the tools assigned to an objective. Both fields are server-populated; clients provide IDs through sibling fields rather than by constructing a BareMetadata themselves.

id: String
name: String

Human-readable name of the referenced resource, populated by the server on reads for convenience. Absent on references to resources that do not have a name (e.g., objective tasks).

tool: BareMetadata { id, name }

BareMetadata contains the minimal metadata for a resource: the ID and an optional human-readable name. These are used for reference fields where the full metadata (account scoping, timestamps, labels, external IDs) is not needed — e.g., the tool references inside an agent variation spec or the tools assigned to an objective. Both fields are server-populated; clients provide IDs through sibling fields rather than by constructing a BareMetadata themselves.

id: String
name: String

Human-readable name of the referenced resource, populated by the server on reads for convenience. Absent on references to resources that do not have a name (e.g., objective tasks).

tool_set: BareMetadata { id, name }

BareMetadata contains the minimal metadata for a resource: the ID and an optional human-readable name. These are used for reference fields where the full metadata (account scoping, timestamps, labels, external IDs) is not needed — e.g., the tool references inside an agent variation spec or the tools assigned to an objective. Both fields are server-populated; clients provide IDs through sibling fields rather than by constructing a BareMetadata themselves.

id: String
name: String

Human-readable name of the referenced resource, populated by the server on reads for convenience. Absent on references to resources that do not have a name (e.g., objective tasks).

created_by: Profile { metadata, spec }

A profile identifies a user or non-human principal (such as an API key) at the account level. Profiles are account-scoped and can be granted access to multiple workspaces.

metadata: AccountResourceMetadata { id, account_id, name, 3 more }

AccountResourceMetadata is used to represent a resource that is associated to an account but not to a workspace.

id: String

Unique identifier for the resource (prefixed ULID, e.g., “apikey_01HXK…”)

account_id: String

Account this resource belongs to for multi-tenant isolation (prefixed ULID)

name: String

Human-readable name for the resource (e.g., “Customer Support Agent”, “Email Tool”) Required for resources that users interact with directly

profile_id: String
external_id: String

External ID for the resource (e.g., a workflow ID from an external system)

labels: Hash[Symbol, String]

Arbitrary key-value pairs for categorization and filtering Examples: {“environment”: “production”, “team”: “platform”, “version”: “v2”}

spec: ProfileSpec { type, email, name }

Configuration for a profile.

type: :PROFILE_TYPE_UNSPECIFIED | :PROFILE_TYPE_USER | :PROFILE_TYPE_API_KEY | :PROFILE_TYPE_SYSTEM

Whether this profile represents a human user, an API key, or a system principal.

formatenum
One of the following:
:PROFILE_TYPE_UNSPECIFIED
:PROFILE_TYPE_USER
:PROFILE_TYPE_API_KEY
:PROFILE_TYPE_SYSTEM
email: String

Email address of the profile. Required and unique within an account for user profiles.

name: String

Display name (e.g., “Bobby Tables”).

feedback_count: Integer

Total number of objective feedbacks received for this variation

formatint32
memory_layer_assignments: Array[VariationMemoryLayerAssignment { id, memory_layer, position } ]

Read-only list of memory layer assignments for this variation, returned in ascending position (bottom → top). Capped at 10 entries.

id: String

Assignment row id — handle for removing the assignment. Distinct from the referenced memory layer’s id.

memory_layer: BareMetadata { id, name }

BareMetadata contains the minimal metadata for a resource: the ID and an optional human-readable name. These are used for reference fields where the full metadata (account scoping, timestamps, labels, external IDs) is not needed — e.g., the tool references inside an agent variation spec or the tools assigned to an objective. Both fields are server-populated; clients provide IDs through sibling fields rather than by constructing a BareMetadata themselves.

id: String
name: String

Human-readable name of the referenced resource, populated by the server on reads for convenience. Absent on references to resources that do not have a name (e.g., objective tasks).

position: Integer

Position in the variation’s baseline stack. Lower values sit lower; the highest-position assignment is on top of the variation’s baseline. Gaps are fine — only relative position matters. Positions must be unique within a variation; a request that would collide with an existing assignment’s position is rejected with InvalidArgument.

formatint32
memory_layer_count: Integer

Count of memory layer assignments.

formatint32
model: ResourceMetadata { id, account_id, created_at, 6 more }

Standard metadata for persistent, named resources (e.g., agents, tools, prompts)

id: String

Unique identifier for the resource (prefixed ULID, e.g., “agent_01HXK…”)

account_id: String

Account this resource belongs to for multi-tenant isolation (prefixed ULID)

created_at: Time

Timestamp when this resource was created

formatdate-time
name: String

Human-readable name for the resource (e.g., “Customer Support Agent”, “Email Tool”) Required for resources that users interact with directly

profile_id: String

ID of the actor (user or service account) that created this resource

workspace_id: String

Workspace this resource belongs to for organizational grouping (prefixed ULID)

bundle_key: String

Optional bundle ownership key. When set, indicates the resource is managed by a configuration bundle identified by this key. Used by BulkWorkspaceResources.Apply to track which resources belong to which bundle for reconciliation / soft-delete on re-apply.

external_id: String

External ID for the resource (e.g., a workflow ID from an external system)

labels: Hash[Symbol, String]

Arbitrary key-value pairs for categorization and filtering Examples: {“environment”: “production”, “team”: “platform”, “version”: “v2”}

score: Float

Thompson Sampling score: posterior mean of Beta(ts_alpha, ts_beta). Range [0, 1] where 0.5 = neutral, >0.5 = positive, <0.5 = negative.

formatfloat
sub_agent_count: Integer

Number of sub-agents assigned to this variation

formatint32
tool_count: Integer

Number of individual tools assigned to this variation

formatint32
tool_set_count: Integer

Number of tool sets assigned to this variation

formatint32
class AgentVariationInfo { assignments, created_by, feedback_count, 7 more }

AgentVariationInfo provides read-only summary information about a variation

assignments: Array[VariationAssignment { id, agent, tool, tool_set } ]

All tools, tool sets, and sub-agents assigned to this variation. Populated on reads so clients can render a variation’s full assignment list without calling the add/remove endpoints just to enumerate.

id: String
agent: BareMetadata { id, name }

BareMetadata contains the minimal metadata for a resource: the ID and an optional human-readable name. These are used for reference fields where the full metadata (account scoping, timestamps, labels, external IDs) is not needed — e.g., the tool references inside an agent variation spec or the tools assigned to an objective. Both fields are server-populated; clients provide IDs through sibling fields rather than by constructing a BareMetadata themselves.

id: String
name: String

Human-readable name of the referenced resource, populated by the server on reads for convenience. Absent on references to resources that do not have a name (e.g., objective tasks).

tool: BareMetadata { id, name }

BareMetadata contains the minimal metadata for a resource: the ID and an optional human-readable name. These are used for reference fields where the full metadata (account scoping, timestamps, labels, external IDs) is not needed — e.g., the tool references inside an agent variation spec or the tools assigned to an objective. Both fields are server-populated; clients provide IDs through sibling fields rather than by constructing a BareMetadata themselves.

id: String
name: String

Human-readable name of the referenced resource, populated by the server on reads for convenience. Absent on references to resources that do not have a name (e.g., objective tasks).

tool_set: BareMetadata { id, name }

BareMetadata contains the minimal metadata for a resource: the ID and an optional human-readable name. These are used for reference fields where the full metadata (account scoping, timestamps, labels, external IDs) is not needed — e.g., the tool references inside an agent variation spec or the tools assigned to an objective. Both fields are server-populated; clients provide IDs through sibling fields rather than by constructing a BareMetadata themselves.

id: String
name: String

Human-readable name of the referenced resource, populated by the server on reads for convenience. Absent on references to resources that do not have a name (e.g., objective tasks).

created_by: Profile { metadata, spec }

A profile identifies a user or non-human principal (such as an API key) at the account level. Profiles are account-scoped and can be granted access to multiple workspaces.

metadata: AccountResourceMetadata { id, account_id, name, 3 more }

AccountResourceMetadata is used to represent a resource that is associated to an account but not to a workspace.

id: String

Unique identifier for the resource (prefixed ULID, e.g., “apikey_01HXK…”)

account_id: String

Account this resource belongs to for multi-tenant isolation (prefixed ULID)

name: String

Human-readable name for the resource (e.g., “Customer Support Agent”, “Email Tool”) Required for resources that users interact with directly

profile_id: String
external_id: String

External ID for the resource (e.g., a workflow ID from an external system)

labels: Hash[Symbol, String]

Arbitrary key-value pairs for categorization and filtering Examples: {“environment”: “production”, “team”: “platform”, “version”: “v2”}

spec: ProfileSpec { type, email, name }

Configuration for a profile.

type: :PROFILE_TYPE_UNSPECIFIED | :PROFILE_TYPE_USER | :PROFILE_TYPE_API_KEY | :PROFILE_TYPE_SYSTEM

Whether this profile represents a human user, an API key, or a system principal.

formatenum
One of the following:
:PROFILE_TYPE_UNSPECIFIED
:PROFILE_TYPE_USER
:PROFILE_TYPE_API_KEY
:PROFILE_TYPE_SYSTEM
email: String

Email address of the profile. Required and unique within an account for user profiles.

name: String

Display name (e.g., “Bobby Tables”).

feedback_count: Integer

Total number of objective feedbacks received for this variation

formatint32
memory_layer_assignments: Array[VariationMemoryLayerAssignment { id, memory_layer, position } ]

Read-only list of memory layer assignments for this variation, returned in ascending position (bottom → top). Capped at 10 entries.

id: String

Assignment row id — handle for removing the assignment. Distinct from the referenced memory layer’s id.

memory_layer: BareMetadata { id, name }

BareMetadata contains the minimal metadata for a resource: the ID and an optional human-readable name. These are used for reference fields where the full metadata (account scoping, timestamps, labels, external IDs) is not needed — e.g., the tool references inside an agent variation spec or the tools assigned to an objective. Both fields are server-populated; clients provide IDs through sibling fields rather than by constructing a BareMetadata themselves.

id: String
name: String

Human-readable name of the referenced resource, populated by the server on reads for convenience. Absent on references to resources that do not have a name (e.g., objective tasks).

position: Integer

Position in the variation’s baseline stack. Lower values sit lower; the highest-position assignment is on top of the variation’s baseline. Gaps are fine — only relative position matters. Positions must be unique within a variation; a request that would collide with an existing assignment’s position is rejected with InvalidArgument.

formatint32
memory_layer_count: Integer

Count of memory layer assignments.

formatint32
model: ResourceMetadata { id, account_id, created_at, 6 more }

Standard metadata for persistent, named resources (e.g., agents, tools, prompts)

id: String

Unique identifier for the resource (prefixed ULID, e.g., “agent_01HXK…”)

account_id: String

Account this resource belongs to for multi-tenant isolation (prefixed ULID)

created_at: Time

Timestamp when this resource was created

formatdate-time
name: String

Human-readable name for the resource (e.g., “Customer Support Agent”, “Email Tool”) Required for resources that users interact with directly

profile_id: String

ID of the actor (user or service account) that created this resource

workspace_id: String

Workspace this resource belongs to for organizational grouping (prefixed ULID)

bundle_key: String

Optional bundle ownership key. When set, indicates the resource is managed by a configuration bundle identified by this key. Used by BulkWorkspaceResources.Apply to track which resources belong to which bundle for reconciliation / soft-delete on re-apply.

external_id: String

External ID for the resource (e.g., a workflow ID from an external system)

labels: Hash[Symbol, String]

Arbitrary key-value pairs for categorization and filtering Examples: {“environment”: “production”, “team”: “platform”, “version”: “v2”}

score: Float

Thompson Sampling score: posterior mean of Beta(ts_alpha, ts_beta). Range [0, 1] where 0.5 = neutral, >0.5 = positive, <0.5 = negative.

formatfloat
sub_agent_count: Integer

Number of sub-agents assigned to this variation

formatint32
tool_count: Integer

Number of individual tools assigned to this variation

formatint32
tool_set_count: Integer

Number of tool sets assigned to this variation

formatint32
class AgentVariationSpec { compaction_config, constraints, description, 6 more }

AgentVariationSpec defines the operational configuration for a variation

compaction_config: AgentVariationSpecCompactionConfig { summarization, tool_result_clearing, trigger_threshold }

CompactionConfig defines how context window compaction behaves for objectives using this variation.

summarization: CompactionConfigSummarizationStrategy { instructions }

SummarizationStrategy configures LLM-powered summarization of older conversation turns.

instructions: String

Custom instructions that guide what the summarizer preserves. Replaces the default summarization prompt entirely. Example: “Preserve all code snippets, variable names, and technical decisions.”

tool_result_clearing: CompactionConfigToolResultClearingStrategy { preserve_recent_results }

ToolResultClearingStrategy configures clearing of older tool result content.

preserve_recent_results: Integer

Number of most recent tool call results to keep intact. Older tool results have their content replaced with “[result cleared]” while preserving the assistant tool call message (function name, arguments). Default: 2

formatint32
trigger_threshold: Float

Trigger threshold as a percentage of the model’s context window (0.0 to 1.0). When input tokens reach this percentage of the model’s limit, compaction triggers. Default: 0.75 (75%)

formatfloat
constraints: AgentVariationSpecConstraints { max_sub_objectives, max_tool_calls }

Execution constraints

max_sub_objectives: Integer

The maximum number of sub-objectives that can be created. 0 means no limit.

formatint32
max_tool_calls: Integer

The maximum number of tool calls that can be made. 0 means no limit.

formatint32
description: String

Human-readable description of what this variation does or when it should be used

enable_episodic_memory: bool

Enable episodic memory for objectives using this variation. When true, the system automatically creates a document namespace for each objective using the objective’s episodic_key as the external_id, allowing the agent to store and retrieve documents specific to that episode.

episodic_memory_ttl: Integer

How long episodic memories should be retained. After this duration, episodic document namespaces can be automatically cleaned up. If not set, episodic memories are retained indefinitely.

model_config: AgentVariationSpecModelConfig { model_id, temperature }

ModelConfig defines the model configuration for a variation

model_id: String

The model identifier in family/model format (e.g., “claude/opus-4.6”, “claude/sonnet-4.5”)

temperature: Float

Sampling temperature for model inference (0.0 to 1.0) Lower values produce more deterministic outputs, higher values increase randomness

formatfloat
progressive_discovery: AgentVariationSpecProgressiveDiscovery { hints, max_tools, rerank_threshold }

ProgressiveDiscovery is used to indicate that the agent should automatically discover tools that are not explicitly assigned to it. Max tools is the maximum number of tools that can be discovered per search. Hints are optional hints for tool search. These are used in conjunction with the context-aware tool search and can help select the best tools for the task.

hints: Array[String]
max_tools: Integer
rerank_threshold: Float

Rerank Threshold is an optional value that instructs whether or not to run a search result through a embedding/reranker process which can improve performance and reduce context bloat when tools reach the configured threshold. If a tool match must exceed 0.8, for example, the tool very closely match the query the tool search performed.

formatfloat
prompt: String

The system prompt for this variation

weight: Integer

Weight for weighted random selection (>= 0). P(v) = v.weight / sum(all_weights). Only used when the agent’s variation_selection_mode is WEIGHTED. A weight of 0 means never auto-selected, but can still be chosen explicitly via variation_id on CreateObjectiveRequest.

formatint32
class AgentVariationSpecCompactionConfig { summarization, tool_result_clearing, trigger_threshold }

CompactionConfig defines how context window compaction behaves for objectives using this variation.

summarization: CompactionConfigSummarizationStrategy { instructions }

SummarizationStrategy configures LLM-powered summarization of older conversation turns.

instructions: String

Custom instructions that guide what the summarizer preserves. Replaces the default summarization prompt entirely. Example: “Preserve all code snippets, variable names, and technical decisions.”

tool_result_clearing: CompactionConfigToolResultClearingStrategy { preserve_recent_results }

ToolResultClearingStrategy configures clearing of older tool result content.

preserve_recent_results: Integer

Number of most recent tool call results to keep intact. Older tool results have their content replaced with “[result cleared]” while preserving the assistant tool call message (function name, arguments). Default: 2

formatint32
trigger_threshold: Float

Trigger threshold as a percentage of the model’s context window (0.0 to 1.0). When input tokens reach this percentage of the model’s limit, compaction triggers. Default: 0.75 (75%)

formatfloat
class AgentVariationSpecConstraints { max_sub_objectives, max_tool_calls }
max_sub_objectives: Integer

The maximum number of sub-objectives that can be created. 0 means no limit.

formatint32
max_tool_calls: Integer

The maximum number of tool calls that can be made. 0 means no limit.

formatint32
class AgentVariationSpecModelConfig { model_id, temperature }

ModelConfig defines the model configuration for a variation

model_id: String

The model identifier in family/model format (e.g., “claude/opus-4.6”, “claude/sonnet-4.5”)

temperature: Float

Sampling temperature for model inference (0.0 to 1.0) Lower values produce more deterministic outputs, higher values increase randomness

formatfloat
class AgentVariationSpecProgressiveDiscovery { hints, max_tools, rerank_threshold }

ProgressiveDiscovery is used to indicate that the agent should automatically discover tools that are not explicitly assigned to it. Max tools is the maximum number of tools that can be discovered per search. Hints are optional hints for tool search. These are used in conjunction with the context-aware tool search and can help select the best tools for the task.

hints: Array[String]
max_tools: Integer
rerank_threshold: Float

Rerank Threshold is an optional value that instructs whether or not to run a search result through a embedding/reranker process which can improve performance and reduce context bloat when tools reach the configured threshold. If a tool match must exceed 0.8, for example, the tool very closely match the query the tool search performed.

formatfloat
class CompactionConfigSummarizationStrategy { instructions }

SummarizationStrategy configures LLM-powered summarization of older conversation turns.

instructions: String

Custom instructions that guide what the summarizer preserves. Replaces the default summarization prompt entirely. Example: “Preserve all code snippets, variable names, and technical decisions.”

class CompactionConfigToolResultClearingStrategy { preserve_recent_results }

ToolResultClearingStrategy configures clearing of older tool result content.

preserve_recent_results: Integer

Number of most recent tool call results to keep intact. Older tool results have their content replaced with “[result cleared]” while preserving the assistant tool call message (function name, arguments). Default: 2

formatint32
class VariationAssignment { id, agent, tool, tool_set }

A read-only reference to a single tool, tool set, or sub-agent attached to a variation. Read the full set of assignments via AgentVariationInfo.assignments; mutations go through the dedicated add/remove assignment endpoints.

The id identifies the assignment itself (not the referenced resource) and is the handle used to remove the assignment. It is returned by the add endpoint and present on every entry in AgentVariationInfo.assignments.

id: String
agent: BareMetadata { id, name }

BareMetadata contains the minimal metadata for a resource: the ID and an optional human-readable name. These are used for reference fields where the full metadata (account scoping, timestamps, labels, external IDs) is not needed — e.g., the tool references inside an agent variation spec or the tools assigned to an objective. Both fields are server-populated; clients provide IDs through sibling fields rather than by constructing a BareMetadata themselves.

id: String
name: String

Human-readable name of the referenced resource, populated by the server on reads for convenience. Absent on references to resources that do not have a name (e.g., objective tasks).

tool: BareMetadata { id, name }

BareMetadata contains the minimal metadata for a resource: the ID and an optional human-readable name. These are used for reference fields where the full metadata (account scoping, timestamps, labels, external IDs) is not needed — e.g., the tool references inside an agent variation spec or the tools assigned to an objective. Both fields are server-populated; clients provide IDs through sibling fields rather than by constructing a BareMetadata themselves.

id: String
name: String

Human-readable name of the referenced resource, populated by the server on reads for convenience. Absent on references to resources that do not have a name (e.g., objective tasks).

tool_set: BareMetadata { id, name }

BareMetadata contains the minimal metadata for a resource: the ID and an optional human-readable name. These are used for reference fields where the full metadata (account scoping, timestamps, labels, external IDs) is not needed — e.g., the tool references inside an agent variation spec or the tools assigned to an objective. Both fields are server-populated; clients provide IDs through sibling fields rather than by constructing a BareMetadata themselves.

id: String
name: String

Human-readable name of the referenced resource, populated by the server on reads for convenience. Absent on references to resources that do not have a name (e.g., objective tasks).

class VariationMemoryLayerAssignment { id, memory_layer, position }

VariationMemoryLayerAssignment attaches a single MemoryLayer to a variation at a given position in the variation’s baseline memory stack. A variation has at most one assignment per memory_layer_id.

Variations only support whole-layer attachments — entry pinning is an objective-level capability.

id: String

Assignment row id — handle for removing the assignment. Distinct from the referenced memory layer’s id.

memory_layer: BareMetadata { id, name }

BareMetadata contains the minimal metadata for a resource: the ID and an optional human-readable name. These are used for reference fields where the full metadata (account scoping, timestamps, labels, external IDs) is not needed — e.g., the tool references inside an agent variation spec or the tools assigned to an objective. Both fields are server-populated; clients provide IDs through sibling fields rather than by constructing a BareMetadata themselves.

id: String
name: String

Human-readable name of the referenced resource, populated by the server on reads for convenience. Absent on references to resources that do not have a name (e.g., objective tasks).

position: Integer

Position in the variation’s baseline stack. Lower values sit lower; the highest-position assignment is on top of the variation’s baseline. Gaps are fine — only relative position matters. Positions must be unique within a variation; a request that would collide with an existing assignment’s position is rejected with InvalidArgument.

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