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Glama

ハッシュタグジェネレーター

hashtag-generator

キーワードからSNS用ハッシュタグを自動生成。TikTok/Instagram/X対応 (Browser-based tool)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Added

TDQS

A4.2/5.0
Behavior3/5

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

With no annotations, the description carries the full transparency burden. It adds the useful context that this is a browser-based tool, which clarifies execution mode. However, it does not disclose other behavioral details such as how input is provided (e.g., via UI), whether any network calls are involved, or what the output format looks like. It is not misleading but is incomplete.

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, front-loaded sentence that conveys purpose, platforms, and execution context without any filler. Every element earns its place, and the parenthetical 'Browser-based tool' is compact and informative.

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 zero-parameter, browser-based generation tool with no output schema, the description covers the essential aspects: what it does, for which platforms, and how it runs. While it doesn't detail the user interaction flow, the simplicity of the tool makes this level of description sufficient. It is not overburdened with unnecessary information.

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?

The tool has zero parameters, so the baseline is 4. The description conceptually mentions 'keywords' as the input, which adds semantic meaning beyond the empty schema. There is no parameter list to elaborate, so this is appropriate.

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 that the tool generates SNS hashtags from keywords, and explicitly names supported platforms (TikTok/Instagram/X), which distinguishes it from sibling tools like youtube-tag-generator. The verb '自動生成' (auto-generate) plus resource 'ハッシュタグ' makes the purpose unambiguous.

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 clear context for when to use the tool: when needing hashtags for TikTok, Instagram, or X. It does not explicitly mention alternative tools or when not to use it, but the platform limitation is a strong contextual guide. Since no alternatives are named, it doesn't quite reach the 'explicit when/when-not' bar.

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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TDQS

B3.1/5.0
Disambiguation2/5

Multiple tools have overlapping purposes, such as bg-remover, bg-remover-pro, pro-matting, and takumi all performing background removal, and upscaler/upscaler-pro being redundant. With 202 tools, an agent may easily select the wrong one despite detailed descriptions.

Naming Consistency4/5

Most tools use a consistent kebab-case format with descriptive names like pdf-compress, image-resizer, and tax-return-calc. Exceptions like 'takumi', 'pro-matting', and '-pro' suffixes (bg-remover-pro, upscaler-pro) are minor deviations relative to the total.

Tool Count1/5

202 tools is an extreme mismatch for an MCP server, far exceeding the typical 3-15 well-scoped range. The sheer volume makes it unwieldy for an agent to efficiently navigate and select the right tool.

Completeness4/5

The tool set provides extensive coverage across many domains, including PDF operations (20+ tools), image editing, financial calculations, e-commerce fee estimation, and YouTube utilities. Minor gaps exist in cross-tool integration, but the breadth is highly comprehensive for the apparent purpose.

Resources