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ai-dememory

ai-dememory

by GonzaloTorreras
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

Manual Acceptance Plan

memory.acceptance_plan
Read-only

Retrieve remaining and blocked manual acceptance next actions without recording evidence to identify unresolved tasks and blockers.

Instructions

Return remaining and blocked manual acceptance next actions without recording evidence.

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.acceptance_plan"
  }
}

Input Schema

NameRequiredDescriptionDefault
pr_urlNo
reviewerNo

Output Schema

NameRequiredDescriptionDefault
planYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.0.0

TDQS

A3.7/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the description adds value by clarifying that no evidence is recorded. However, it does not elaborate on other behavioral aspects like pagination or result format, which are likely covered by output schema.

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 a single sentence of 10 words, front-loading the purpose and key behavioral constraint ('without recording evidence'). No wasted words.

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 read-only query tool with two optional parameters, the description covers the key outputs (remaining/blocked actions) and a critical behavioral constraint. It lacks explanation of 'remaining' vs 'blocked' but output schema likely provides structure. Overall adequate but could include usage context.

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 input schema has two parameters with 0% description coverage, and the description provides no additional meaning for them. While parameter names ('pr_url', 'reviewer') are somewhat self-explanatory, the description should clarify their purpose to compensate for the lack of schema documentation.

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 uses a specific verb ('Return') and resource ('remaining and blocked manual acceptance next actions') and explicitly states it does not record evidence, clearly distinguishing it from sibling tools like memory.acceptance_verify which likely records evidence.

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 description implies when to use this tool (when you need to see remaining/blocked actions without recording) but does not explicitly state when not to use it or name alternatives. With many sibling tools, more explicit guidance would help.

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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