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Memory Graph Context

memorix_graph_context

Construct a focused memory graph context packet for the current project. Returns high-signal memories, entities, relations, and risks as background context for task-specific memory grounding.

Instructions

Build a compact, prompt-ready memory graph context packet for the current project. Use this for broad memory overview questions, project memory graph questions, or task-specific memory grounding. Returns high-signal memories, entities, relations, and risks as background context, not instructions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax high-signal memories to include (default: 5)
queryYesCurrent task or topic to build memory graph context for
formatNoOutput format. "prompt" is agent-ready; "summary" is a compact human overview.prompt
Behavior3/5

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

With no annotations provided, the description carries the full burden. It states the output is 'background context, not instructions,' hinting at non-executable nature, but does not explicitly disclose read-only, non-destructive behavior, authorization needs, or rate limits. The behavioral transparency is adequate but could be more explicit.

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 two sentences, front-loading the primary action and then efficiently covering usage and return type. Every sentence is informative with no redundancy, achieving excellent conciseness.

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

Completeness4/5

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

Given three parameters with full schema coverage and no output schema, the description adequately covers the output as background context. It could mention prerequisites (e.g., an active project) or error conditions, but the core information is present.

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

Parameters3/5

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

Schema coverage is 100%, so the description adds minimal value beyond the schema. It mentions return types (high-signal memories, entities, relations, risks) but does not elaborate on parameter format or constraints beyond what is in the schema. Baseline 3 is appropriate.

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

Purpose4/5

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

The description clearly states the tool builds a 'compact, prompt-ready memory graph context packet' for the current project, and lists specific use cases like 'broad memory overview questions' and 'task-specific memory grounding.' However, it does not explicitly differentiate this from sibling tools like memorix_context_pack, leaving some ambiguity.

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 explicit use cases ('broad memory overview questions, project memory graph questions, task-specific memory grounding'), giving clear guidance on when to use the tool. It lacks when-not-to-use guidance or explicit mention of alternative tools, but the context is sufficient for an agent.

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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