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stflj2022

mcp-memvid

by stflj2022

memvid_save_context

Save conversation context to recover from interruptions by storing a summary, topics, and project paths for later restoration.

Instructions

保存当前对话上下文(用于意外中断后恢复)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topicsNo当前讨论的主题列表
summaryYes当前对话摘要(1-2句话)
projectsNo当前处理的项目路径或名称

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.5/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. The description only says 'save' (保存), which implies a mutating write operation, but does not disclose whether repeated saves overwrite previous context, whether the action is reversible, what storage limits exist, or what the effect on existing state is. There is no mention of side effects or return behavior. This is a significant transparency gap for a state-changing tool.

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 concise sentence that conveys the core purpose and usage context without any fluff. It is front-loaded with the action and resource. It earns every word and is appropriately sized for the tool's simplicity.

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

Completeness3/5

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

For a save-context tool with 3 parameters (1 required) and no output schema, the description provides the essential purpose. However, given the absence of annotations and the tool's mutating nature, it would benefit from more context about what gets saved, whether it appends or replaces, and whether there is any confirmation. Still, the tool is simple enough that an agent can infer typical behavior, so a middle score is appropriate.

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% — every parameter (topics, summary, projects) already has a descriptive comment in the input schema. The tool description adds no additional meaning or usage hints for the parameters. Per the rubric, baseline is 3 when coverage is high, and the description does not enhance parameter understanding beyond the schema.

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 action ('保存' = save) on a specific resource ('当前对话上下文' = current conversation context), with the purpose '用于意外中断后恢复' (for recovery after unexpected interruption). This clearly identifies what the tool does and, implicitly, why it exists. It does not explicitly name sibling alternatives, but the purpose distinguishes it from search/compact/list tools in the sibling list.

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

Usage Guidelines4/5

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

The description provides a clear usage context: it is for saving context to recover after an unexpected interruption. This tells the agent when to use this tool. However, it does not state when *not* to use it or explicitly mention alternatives like memvid_quick_save or memvid_store, which may overlap. The guidance is adequate but lacks explicit exclusions.

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