Keyboard Shortcuts MCP Server
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
With only one tool, there is no possibility of ambiguity or confusion between tools. The single tool 'get_shortcuts' has a clear, distinct purpose that cannot be mistaken for any other functionality within this server.
Naming Consistency5/5The single tool name 'get_shortcuts' follows a clear verb_noun pattern (get + shortcuts). With only one tool, consistency is inherently perfect as there are no other names to compare or conflict with.
Tool Count2/5A single tool is generally too few for a server's purpose, especially one focused on keyboard shortcuts which could benefit from operations like listing available OS/applications, updating shortcuts, or searching by category. The scope feels thin and incomplete with just one query tool.
Completeness2/5The server is severely incomplete for a keyboard shortcuts domain. While 'get_shortcuts' provides query functionality, there are obvious gaps: no ability to list supported systems/applications, create custom shortcuts, update existing ones, or manage shortcut sets. This will limit agent workflows significantly.
Average 3.2/5 across 1 of 1 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
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How is the quality score calculated?
The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).
Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.
Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).
Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.
Tool Scores
- 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. It mentions using 'Claude Opus to intelligently search,' which adds some context about the AI-driven behavior, but it fails to disclose critical traits like rate limits, authentication needs, response format, or potential errors. For a tool with no annotation coverage, this is a significant gap in behavioral transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded, consisting of two sentences that efficiently convey the tool's purpose and method. Every sentence adds value without redundancy, though it could be slightly more structured (e.g., separating functional and behavioral aspects).
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (4 parameters, no annotations, no output schema), the description is moderately complete. It covers the core functionality and method but lacks details on output format, error handling, or operational constraints. Without an output schema, the description should ideally hint at return values, which it doesn't, leaving gaps in contextual understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, meaning the input schema fully documents all parameters. The description adds minimal value beyond the schema by mentioning 'natural language queries' and 'intelligently search,' which aligns with the 'query' parameter but doesn't provide additional syntax or format details. The baseline score of 3 is appropriate given the high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Query keyboard shortcuts for a specific OS, desktop environment, and/or application.' It specifies the verb 'query' and the resource 'keyboard shortcuts,' and mentions the intelligent search capability using Claude Opus. However, with no sibling tools, the differentiation aspect is not applicable, preventing a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage by stating it handles 'natural language queries' and targets specific OS/application contexts, but it lacks explicit guidance on when to use this tool versus alternatives (e.g., other search methods). With no sibling tools, there's no comparison, but it doesn't provide exclusions or prerequisites, leaving room for improvement.
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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