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total-agent-memory

total-agent-memory

by vbcherepanov
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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memory_graph_index

Idempotent

Reindex CLAUDE.md rules and skills into the knowledge graph after modifying CLAUDE.md or adding new skills.

Instructions

Reindex CLAUDE.md rules and skills into the knowledge graph. Run after modifying CLAUDE.md or adding new skills.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "memory_graph_index"
  }
}

Input Schema

NameRequiredDescriptionDefault
targetNoall

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.8/5.0
Behavior3/5

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

Annotations already indicate the tool is idempotent and not destructive. The description adds the maintenance context (run after changes) and clarifies that it updates the knowledge graph, but it doesn't disclose any side effects beyond reindexing. Given the annotation coverage, this is acceptable but minimal additional behavioral disclosure.

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-loaded with the core action and followed by the trigger condition. There is no redundancy or filler; every word earns its place.

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

Completeness3/5

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

For a simple tool with one optional parameter and no output schema, the description covers the action and when to run it. However, it omits any explanation of the parameter, which means an agent might not realize it can target subsets. Given the default 'all', a full reindex is achievable without parameters, but the omission limits flexibility.

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

Parameters2/5

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

The schema has 0% description coverage, and the description does not mention the 'target' parameter or its possible values (all, claude_md, skills, rules). While the enum values are somewhat self-explanatory, the description fails to explain how they map to the reindex scope, leaving an agent to infer the parameter's role. This is a significant gap that the description should compensate for.

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 a specific action: 'Reindex CLAUDE.md rules and skills into the knowledge graph.' It names the verb (reindex), the resource (CLAUDE.md rules and skills), and the destination (knowledge graph), and it includes a trigger condition. This distinguishes it from sibling reindex tools like memory_rebuild_fts and memory_rebuild_embeddings, which target different indexes.

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 explicitly says 'Run after modifying CLAUDE.md or adding new skills,' which is a clear, actionable trigger. It does not mention alternatives or exclusions, but the context is sufficient for an agent to know when this tool is appropriate, especially given the knowledge-graph specificity.

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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