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mind_consolidate

Preview memory consolidation by counting exact duplicates, near-duplicates, and cold entries. Run this dry-run check before the destructive CLI command with --apply.

Instructions

Preview what mgimind consolidate would do: count of exact duplicates, near-duplicates, and cold (old + unused) entries. Always dry-run on the MCP surface; destructive consolidation stays on the CLI where the user types --apply explicitly. Use this when the user asks 'how much duplicate memory do I have?' or before suggesting they run the CLI command.

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": "mind_consolidate"
  }
}

Input Schema

Name	Required	Description	Default
`library`	No	Scope to one library (omit for all)

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Oct 20, 2026

TDQS

A4.4/5.0

Behavior4/5

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

With no annotations, the description carries the full behavioral burden, and it does disclose the critical trait: the tool is always dry-run on the MCP surface and will never mutate memory. It does not discuss cost on large libraries or how scope affects the counts, so it stops just short of full coverage.

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?

Three tight sentences, front-loaded with what is counted, then the safety/dry-run guarantee, then the invocation trigger. No redundancy and every sentence carries information.

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?

No output schema exists, and the description partially compensates by naming the three count categories returned. For a single optional-parameter read tool this is nearly sufficient; only the exact shape/threshold definition of 'cold' is left unspecified.

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?

There is one optional parameter with 100% schema description coverage ('Scope to one library (omit for all)'), so the schema already carries the semantics. The description adds no further meaning about argument form or default scoping, matching the baseline for high-coverage single-parameter tools.

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?

Names a specific verb (preview) and enumerates exactly what is measured: counts of exact duplicates, near-duplicates, and cold (old + unused) entries. It also positions itself against the CLI `mgimind consolidate` path, so an agent can tell this apart from a destructive consolidation tool without opening the schema.

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

Usage Guidelines5/5

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

Gives explicit trigger conditions ('Use this when the user asks how much duplicate memory do I have?') and a sequencing cue ('before suggesting they run the CLI command'), plus an explicit exclusion – destructive consolidation lives on the CLI with `--apply`. Nothing about when to reach for this vs. alternatives is left to inference.

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