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read_graph

Retrieve the complete knowledge graph with memories, relations, and decay scores. Paginate through results, filter by status, and access graph statistics in one request.

Instructions

Read the entire knowledge graph of memories and relations.

Returns the complete graph structure including all memories (with decay scores), all relations between memories, and statistics about the graph.

Pagination: Results are paginated to help you navigate large knowledge graphs. Use page and page_size to retrieve specific portions of the graph. If searching for specific memories or patterns, increment page to see more results.

Args: status: Filter memories by status - "active", "promoted", "archived", or "all". include_scores: Include decay scores and age in results. limit: Maximum number of memories to return (1-10,000). page: Page number to retrieve (1-indexed, default: 1). page_size: Number of memories per page (default: 10, max: 100).

Returns: Dictionary with paginated graph including: - memories: List of memories for current page - relations: All relations (not paginated, for graph structure) - stats: Graph statistics - pagination: Metadata (page, page_size, total_count, total_pages, has_more)

Examples: # Get first page of active memories read_graph(status="active", page=1, page_size=10)

# Get next page
read_graph(status="active", page=2, page_size=10)

# Larger page for overview
read_graph(status="active", page=1, page_size=50)

Raises: ValueError: If status is invalid or limit is out of range.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNo
limitNo
statusNoactive
page_sizeNo
include_scoresNo

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 responsibility for behavioral disclosure. It richly explains pagination, the relationship between page and page_size, the fact that relations are not paginated, error conditions (ValueError), and the optional inclusion of decay scores and age. This goes well beyond a simple read operation.

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 well-structured with clear sections (description, pagination, args, returns, examples, raises) and front-loaded with a one-sentence purpose. Despite its length, every section adds value and the formatting makes it easy to scan.

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?

The description covers all aspects needed for correct invocation: parameters, pagination behavior, return structure, and error handling. Even though an output schema exists (so return explanation isn't required), the description goes further by detailing the keys returned, which is helpful for an agent.

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% parameter description coverage, so the description fully compensates by explaining each parameter's meaning, allowed values, ranges, and defaults. It also provides examples showing parameter combinations.

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 'Read the entire knowledge graph of memories and relations,' a specific verb and resource that clearly distinguishes it from sibling tools like search_memory or cluster_memories. It also explicitly lists what is returned, reinforcing the tool's scope.

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 provides clear context for use, including pagination examples and a note to increment pages to see more results. However, it does not explicitly name alternatives (e.g., search_memory) or state when not to use this tool, so it falls short of a 5.

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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