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memory_changes_since

Resume-handoff delta of durable org memory since an opaque cursor.

Returns current-truth rows newer than cursor (oldest-first) plus a new opaque cursor. Use this to continue another session's work; use memory_recall for keyword search. Not a full checkpoint/context pack.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kNoMax durable changes to return (oldest-first)
kindNoOptional durable kind filter (fact|preference|event|note|outreach)
repoNoWorkspace slug filter. When set, only memories tagged for this repo are returned (unlike memory_recall, which boosts).
cursorNoOpaque resume watermark from a previous memory_changes_since call. Clients must persist and return it as-is — do not parse or mint one. Omit to take a bootstrap page of the newest current-truth durable rows and receive a cursor to watch from.
githubNoGitHub owner/repo filter. When set, only memories tagged github:<owner>/<repo> are returned.
pillarNoOptional pillar filter. This feed is memory_items only (semantic / episodic). Other pillars return an empty page.
include_supersededNoWhen true, also return superseded/merged history. Default is current truth only, same as memory_recall.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

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 behavioral burden. It discloses the output ordering (oldest-first), the fact that it returns a new opaque cursor, and the limitation that it is not a full checkpoint. It implies a read operation (returns delta), but does not explicitly state read-only or describe side effects. It adds useful context beyond the schema (e.g., resume-handoff, current-truth), so it is strong but not perfect.

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 three sentences, front-loaded with the core purpose. It packs a clear purpose, return behavior, usage guidance, and a limitation without any fluff. Every sentence contributes to orientation or selection.

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?

The presence of an output schema covers return format. The description covers why and when to use the tool, plus a key limitation. It does not explain the effect of filters (kind, repo, pillar) but those are fully documented in the schema. For a tool of this complexity, this is adequately complete, though it could mention that only memory_items are returned for pillar filtering, which is in the schema but not the description.

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 baseline is 3. The description does not add semantic detail about individual parameters beyond what the schema already provides. It mentions 'opaque cursor' and 'current-truth' conceptually, but these are also covered in the schema descriptions. No extra value added.

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: providing a resume-handoff delta of durable org memory since an opaque cursor, returning current-truth rows newer than the cursor. It explicitly distinguishes itself from memory_recall for keyword search, making its purpose unambiguous to an agent.

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?

It gives direct usage instruction: 'Use this to continue another session's work' and contrasts with 'use memory_recall for keyword search.' It also flags a limitation ('Not a full checkpoint/context pack'), telling the agent when not to use it. This is explicit and actionable.

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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