Test FastMCP
Server Quality Checklist
Latest release: v0.1.0
- Disambiguation5/5
Each tool has a clearly distinct mathematical operation: addition, division, multiplication, and subtraction. There is no overlap in purpose, and the descriptions make it immediately obvious which tool to use for each basic arithmetic operation.
Naming Consistency5/5All tool names follow a consistent pattern of simple, single-word verbs describing the mathematical operation (add, divide, multiply, subtract). There is no mixing of naming conventions or styles, making the set highly predictable and readable.
Tool Count5/5With exactly four tools covering the four basic arithmetic operations, this server is perfectly scoped for its purpose. Each tool earns its place with no redundancy or missing core functionality, making it an ideal minimal set for arithmetic calculations.
Completeness5/5For a server focused on basic arithmetic, this tool set is complete with full coverage of addition, subtraction, multiplication, and division. There are no gaps in the core operations, and agents can perform all fundamental calculations without dead ends.
Average 3.9/5 across 4 of 4 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 of behavioral disclosure. While it correctly describes the mathematical operation, it doesn't address important behavioral aspects like error handling (e.g., overflow, underflow), performance characteristics, or whether this is a pure function. For a tool with no annotation coverage, this represents 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is perfectly structured and concise. It begins with a clear purpose statement, then provides organized sections for Args and Returns. Every sentence earns its place - the first sentence states the operation, the Args section documents parameters, and the Returns section specifies the output. No wasted words or redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (basic arithmetic operation), 2 parameters, and the existence of an output schema (which handles return value documentation), the description is reasonably complete. It covers the operation, parameters, and return value. However, it could benefit from mentioning sibling tools for context and addressing potential edge cases like integer overflow, which would make it fully complete for this mathematical tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description fully compensates by clearly explaining both parameters in the Args section: 'a: First integer' and 'b: Second integer'. It adds essential meaning beyond the bare schema by specifying the order of operation ('subtract the second integer from the first') and clarifying which parameter is subtracted from which. This is exactly what's needed when schema coverage is low.
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 with a specific verb ('subtract') and resource ('the second integer from the first'), making it immediately understandable. It distinguishes from siblings by specifying the subtraction operation rather than addition, multiplication, or division. However, it doesn't explicitly mention the sibling tools or how it differs from them beyond the mathematical operation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'add', 'divide', or 'multiply'. It simply states what the tool does mathematically without any context about appropriate use cases, prerequisites, or comparisons to sibling tools. The agent must infer usage from the mathematical operation alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but only states the basic operation. It doesn't disclose behavioral traits like error handling (e.g., division by zero), performance characteristics, or any constraints beyond what's implied by the operation itself.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded with the core purpose in the first sentence. The Args and Returns sections are structured efficiently with no wasted words, making it easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity and the presence of an output schema (which handles return values), the description is mostly complete. It covers purpose and parameters adequately, though it lacks error-handling details which would be helpful for a division operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It adds clear meaning by specifying 'a' as the dividend and 'b' as the divisor, which goes beyond the schema's generic titles ('A', 'B'). However, it doesn't detail constraints like non-zero divisor or integer-specific behavior.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Divide') with the resource ('first integer by the second'), and distinguishes from sibling tools (add, multiply, subtract) by specifying division rather than other arithmetic operations.
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 for integer division but doesn't explicitly state when to use this vs. alternatives like 'multiply' or 'subtract'. It provides basic context (dividing integers) but lacks explicit guidance on exclusions or comparisons to sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. While it states the basic operation, it doesn't disclose important behavioral traits like overflow handling, performance characteristics, error conditions, or whether it's idempotent. The description is minimal beyond stating the core function.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is perfectly structured and front-loaded with the core purpose, followed by clear parameter and return value sections. Every sentence earns its place with zero wasted words, making it easy to scan and understand.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (basic arithmetic), 2 parameters, and the presence of an output schema (which handles return value documentation), the description is reasonably complete. It covers the essential what and how, though additional behavioral context would be beneficial for a production tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description compensates by clearly explaining both parameters ('First integer' and 'Second integer'). It adds meaningful semantic context beyond the bare schema, though it doesn't specify constraints like range limits or special values.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Multiply two integers together') and identifies the resource (integers). It distinguishes from sibling tools (add, divide, subtract) by specifying multiplication rather than other arithmetic operations.
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 for integer multiplication but doesn't explicitly state when to use this tool versus alternatives like 'add' or 'divide'. No guidance is provided about edge cases, limitations, or prerequisites for use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It discloses the basic behavior (addition operation) and return value, but lacks details on error handling, integer overflow behavior, or performance characteristics that would be useful for an agent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is perfectly structured and front-loaded with the core purpose, followed by clear sections for arguments and return value. Every sentence earns its place with zero wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (basic arithmetic operation), 2 parameters, and the presence of an output schema that handles return values, the description is complete enough for an agent to understand and use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It provides clear semantic meaning for both parameters ('First integer', 'Second integer') beyond what the bare schema offers, though it doesn't specify constraints like range or special values.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('Add') and resource ('two integers together'), clearly distinguishing this tool from its siblings (divide, multiply, subtract) by specifying the exact mathematical operation performed.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use this tool ('Add two integers together') and implicitly distinguishes it from alternatives by naming the operation, making it clear this is for addition versus division, multiplication, or subtraction provided by sibling tools.
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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