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stevepridemore

Graph-Memory

Re-embed Entities

graph_reembed
Idempotent

Regenerate semantic-search embeddings for entities. Fill missing embeddings by default; force full re-embed after changing the embed-text recipe.

Instructions

Regenerate semantic-search embeddings for entities. By default only fills missing embeddings (idempotent, fast). With force=true, re-embeds every entity — use after changing the embed-text recipe (e.g. when richer fields are added). At ~10ms per entity, full re-embed of a few hundred nodes finishes in seconds.

Input Schema

NameRequiredDescriptionDefault
forceNoRe-embed every entity, even ones that already have an embedding. Default false.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.2.2
  2. Removedv0.1.4
  3. First observedv1.0.0

TDQS

A4.7/5.0
Behavior5/5

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

The description adds value beyond the idempotentHint annotation by explaining that the default is idempotent and fast, and providing a time estimate (~10ms per entity). It also clarifies the effect of force=true, giving the agent a clear behavioral model.

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 consists of two concise sentences, front-loading the primary purpose and efficiently conveying the key details about behavior and performance. No unnecessary 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 simple tool with a single parameter and no output schema, the description covers the purpose, default vs. forced behavior, use case, and performance estimate. It is complete and self-contained.

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?

The input schema already describes the parameter with a default and a brief description. The tool's description adds meaningful context by explaining when to set force=true (after recipe changes), which goes beyond the schema's description.

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 clearly states the tool's action ('Regenerate semantic-search embeddings for entities') and specifies the default behavior (only missing embeddings) versus the forced re-embed mode. This distinguishes it from other sibling tools by focusing on a specific operation.

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 context for when to use force=true ('after changing the embed-text recipe'), indicating a clear usage scenario. However, it does not mention when to avoid the tool or compare it to alternatives among siblings.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.