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itoufo

Personal DB MCP Server

by itoufo

get_context

Generates persona-based weighted context, returning optimized Markdown so AI systems can understand and personalize responses for a specific individual.

Instructions

ペルソナベースの重み付きコンテキストを生成。AIがこの人物を理解するための最適化されたMarkdownを返す。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
focusNoフォーカスキーワード (マッチするエントリを1.5xブースト)
personaNoペルソナ名 (default/professional/interview/personal/creative またはカスタム名)
max_tokens_hintNo出力目安トークン数 (デフォルト: 4000)
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses that it returns Markdown and that it's persona-based with weighted boosting (1.5x per schema). However, it doesn't disclose behavior like whether this is read-only, whether it triggers side effects, rate limits, or what 'optimized' means operationally. Moderate transparency with room to add more behavioral detail.

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?

The description is a single, efficient sentence that conveys purpose and output in concise Japanese. It's front-loaded with the core function. Could be slightly more structured but achieves its goal without waste.

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 tool with no output schema, the description should explain what return values look like. It does state 'Markdown' as the output format, which helps, but doesn't describe the structure of that Markdown, how max_tokens_hint affects it, or what happens when no persona matches. Given 0 required params and 100% param coverage, it's adequate but could be more complete about the return content.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

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 adds meaningful context by framing the tool as 'persona-based weighted context' which ties to the persona parameter, and 'optimized Markdown' connects to max_tokens_hint. The focus keyword boosting (1.5x) is described in schema, but the description's 'weighted' concept reinforces the semantic purpose of these parameters. Slight value added over 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 it generates persona-based weighted context and returns optimized Markdown for AI to understand the person. This is a clear verb+resource+output. It distinguishes itself from sibling tools like get_profile or get_persona by emphasizing 'weighted context' and 'optimized Markdown' generation, though it doesn't explicitly name alternatives.

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 it (when AI needs to understand a person via persona-based weighted context) but doesn't explicitly state when NOT to use it or which sibling tools are alternatives. The focus and persona parameters hint at customization use cases, but there's no explicit guidance versus tools like get_profile or list_available_personas.

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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