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list_pending_revisions

Read-onlyIdempotent

Lists memories awaiting human approval or dismissal when a newer revision is proposed. Use to review pending revisions and identify which items need acceptance.

Instructions

List memories awaiting human accept/dismiss because a newer version was proposed (Protected tier supersede). Use when the user asks 'what revisions are pending', 'show me memories awaiting approval'. Each item carries target_source_id (the memory being revised; pass this to accept_revision only after the user explicitly approves that item) and revision_content for display. Review acceptance is local-only; accept_revision is unavailable over remote HTTP MCP. Optional limit caps results (default 50, max 500).

Input Schema

NameRequiredDescriptionDefault
limitNoMaximum rows to return. Server defaults to 50, clamps to 500.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.19.3

TDQS

A4.4/5.0
Behavior5/5

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

Annotations already cover read-only safety, and the description adds operational context they cannot: acceptance is local-only and accept_revision is unavailable over remote HTTP MCP, plus default 50 / max 500 result capping. These are exactly the kinds of constraints an agent needs before routing a user toward an approval flow.

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?

Front-loaded with purpose, then usage triggers, then return-item fields, then pagination — a sensible order. It is one dense paragraph, and the parenthetical accept_revision caveat is slightly wordy, but no sentence is filler.

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

Completeness5/5

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

With no output schema, the description compensates by naming the fields each item carries (target_source_id, revision_content) and explaining how target_source_id feeds the next step. Pagination limits and remote-HTTP limitations are also covered, leaving no obvious gap for a zero-required-param list tool.

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% and the single `limit` param is fully documented there, including the default and clamp. The description's 'default 50, max 500' merely restates the schema rather than adding format or interaction detail, so baseline 3 applies.

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 and resource ('List memories awaiting human accept/dismiss because a newer version was proposed') plus the mechanism ('Protected tier supersede'), which separates it in meaning from list_pending, list_pending_imports, and list_refinements. It never names those siblings explicitly, so the differentiation is inferential rather than declared.

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 concrete user-utterance triggers ('what revisions are pending', 'show me memories awaiting approval') and spells out the downstream workflow rule: pass target_source_id to accept_revision only after the user explicitly approves that item. It also names accept_revision and the accept/dismiss alternatives, so the when-to-use and when-not-to-act boundary is explicit.

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