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memory_consolidate

Consolidate near-duplicate memories into a single canonical note, marking originals as superseded to shorten the memory bank while preserving the audit trail.

Instructions

Replace a cluster of near-duplicate memories with one canonical note. Every entry matching replaces is marked superseded by new_text, which is stored fresh — the bank gets shorter without losing the audit trail.

Returns: {superseded_count, superseded_texts, new_memory_stored}.

Input Schema

TableJSON Schema

Name	Required	Description
`tags`	No	Labels for the new note.
`source`	No	Source tag for the new note.
`new_text`	Yes	The canonical note that replaces them.
`replaces`	Yes	The memories being folded in; each is matched by exact text or close paraphrase.

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

Changed4 schema fields changedv0.15.0Sep 3, 2026
- addedInput schema / properties / new_text / description
```
Added value: +"The canonical note that replaces them."
```
- addedInput schema / properties / replaces / description
```
Added value: +"The memories being folded in; each is matched by exact text or close paraphrase."
```
- addedInput schema / properties / source / description
```
Added value: +"Source tag for the new note."
```
- addedInput schema / properties / tags / description
```
Added value: +"Labels for the new note."
```
First observedv0.11.0Jul 31, 2026

TDQS

A3.8/5.0

Behavior4/5

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

With no annotations provided, the description carries full responsibility for behavioral disclosure. It clearly states that matched entries are marked superseded, the new text is stored fresh, and the memory bank shrinks without losing the audit trail. This gives the agent a solid model of side effects without overclaiming.

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 compact and front-loaded, with the primary action stated first and no filler. The return shape is included as a separate line, and every sentence adds information relevant to invoking the tool.

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?

For a 4-parameter tool with an output schema and full schema coverage, the description covers the operation, side effects, and return value. It is slightly incomplete only in not explicitly guiding selection among the many closely related memory tools.

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 input schema already documents every parameter. The description adds contextual color ('canonical note', 'stored fresh') but does not need to duplicate parameter-level detail, so the 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 states a specific verb ('Replace') and resource ('a cluster of near-duplicate memories'), making the core purpose immediately clear. It is not a tautology and is distinguishable from related tools like memory_store or memory_forget, though it does not explicitly name a sibling for comparison.

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?

The phrase 'cluster of near-duplicate memories' implies the appropriate context, and the tool clearly is meant for consolidation rather than simple storage. However, it does not explicitly say when to prefer this over siblings like memory_supersede or memory_consolidation_candidates, leaving some routing to inference.

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