# Context Strategy Object

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 — This section is still being developed and may change.


Represents a context management strategy configuration with its properties and capabilities.

## Properties

**`id`** string

Unique identifier for the context strategy. Format: `ctx_` followed by alphanumeric characters.

**`name`** string

Human-readable name for the context strategy (e.g., "Full Context", "Auto Management").

**`description`** string

Detailed description of what the strategy does and when to use it.

**`mode`** string

The strategy identifier used in configuration. Values: `full`, `auto`, `saver`, `off`.

**`capabilities`** object

Configuration capabilities and limitations of this strategy.

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**`contextRetention`** string

How context is retained. Values: `complete`, `intelligent`, `minimal`, `none`.

**`performance`** string

Performance characteristics. Values: `high_memory`, `balanced`, `low_memory`, `minimal`.

**`recommendedFor`** array of strings

Recommended use cases for this strategy. Example: `["complex_analysis", "research", "general_use"]`.

**`tradeoffs`** object

Advantages and disadvantages of using this strategy.

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**`advantages`** array of strings

List of benefits. Example: `["maximum_context", "best_reasoning"]`.

**`disadvantages`** array of strings

List of drawbacks. Example: `["higher_cost", "slower_responses"]`.

**`isDefault`** boolean

Whether this is the default context strategy for new assistants.

**`createdAt`** integer

Unix timestamp (seconds) when the strategy was created.

**`updatedAt`** integer

Unix timestamp (seconds) when the strategy was last updated.

## Returns

A [ApiResponse](#apiresponse) object containing the API response data.

## Example Context Strategy

Full Context Strategy

```json
{
  "id": "ctx_full_context",
  "name": "Full Context",
  "description": "Maintains the entire conversation history for maximum continuity and complex reasoning tasks.",
  "mode": "full",
  "capabilities": {
    "contextRetention": "complete",
    "performance": "high_memory",
    "recommendedFor": ["complex_analysis", "research", "deep_reasoning"],
    "tradeoffs": {
      "advantages": ["maximum_context", "best_reasoning", "complete_history"],
      "disadvantages": ["higher_cost", "slower_responses", "memory_intensive"]
    }
  },
  "isDefault": false,
  "createdAt": 1728057600,
  "updatedAt": 1728057600
}
```

Auto Strategy

```json
{
  "id": "ctx_auto_management",
  "name": "Auto Management",
  "description": "Intelligent context management that adapts to conversation complexity and relevance.",
  "mode": "auto",
  "capabilities": {
    "contextRetention": "intelligent",
    "performance": "balanced",
    "recommendedFor": ["general_use", "mixed_workloads", "production"],
    "tradeoffs": {
      "advantages": ["balanced_performance", "adaptive", "cost_effective"],
      "disadvantages": ["less_predictable", "may_drop_context"]
    }
  },
  "isDefault": true,
  "createdAt": 1728057600,
  "updatedAt": 1728057600
}
```

Saver Strategy

```json
{
  "id": "ctx_minimal_saver",
  "name": "Minimal Saver",
  "description": "Minimal context retention optimized for cost and speed in simple interactions.",
  "mode": "saver",
  "capabilities": {
    "contextRetention": "minimal",
    "performance": "low_memory",
    "recommendedFor": ["simple_queries", "high_volume", "cost_sensitive"],
    "tradeoffs": {
      "advantages": ["lowest_cost", "fastest", "efficient"],
      "disadvantages": ["limited_context", "poor_complexity", "stateless"]
    }
  },
  "isDefault": false,
  "createdAt": 1728057600,
  "updatedAt": 1728057600
}
```