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memory_visualize

Visualize stored memories as an interactive HTML graph with semantic clusters, similarity edges, duplicate detection, importance distribution, and growth timeline.

Instructions

Generate an interactive HTML visualization of the memory graph. Shows semantic clusters, similarity edges, duplicate detection, importance distribution, and growth timeline. Returns the HTML as text or writes it to a file path.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
scopeNoScope to visualize (default: all accessible scopes)
thresholdNoCosine similarity threshold for drawing edges between memories (0.0-1.0, default: 0.65)
output_pathNoFile path to write the HTML output. If omitted, returns the HTML content directly.
max_neighborsNoMaximum edges per node (default: 4)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.0.33

TDQS

A3.5/5.0
Behavior3/5

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

No annotations, so the description carries the full burden. It usefully discloses the two output modes (returns HTML text vs. writes to output_path) and the visualized content, which is real behavioral value, but says nothing about read-only safety, whether it mutates state, or performance cost on large graphs.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three tight sentences: purpose, content list, output behavior. Front-loaded and free of filler, though the content enumeration is somewhat list-heavy.

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?

With no output schema, the description correctly covers return semantics (HTML text or file). All four parameters are documented in the schema, and the tool's rendering scope is described, so an agent has what it needs to invoke it correctly.

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 description coverage is 100%, so the schema already documents scope, threshold, output_path, and max_neighbors. The description restates the output_path behavior ('returns the HTML as text or writes it to a file path') but adds no format, default, or constraint detail beyond the schema.

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?

States a specific verb (Generate) and resource (interactive HTML visualization of the memory graph) and enumerates what it renders (clusters, similarity edges, duplicates, importance, timeline). It is clearly distinct from the CRUD siblings, though it never explicitly contrasts itself with them.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is implied by the nature of the tool (inspect/visualize the memory graph), but there is no explicit when-to-use, when-not-to-use, or alternative routing. With siblings all being memory mutations, an agent can infer this is the inspection path, but the description does not say so.

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