mcp-server
Server Quality Checklist
Latest release: v0.1.0
- Disambiguation2/5
web_search and roll_dice are clearly distinct, but YOUR_TOOL_NAME has an uninformative name and description, making its purpose ambiguous. This creates potential confusion and misselection.
Naming Consistency1/5web_search and roll_dice follow a verb_noun pattern, but YOUR_TOOL_NAME does not, breaking consistency. The mixing of a proper pattern with a placeholder-like name makes naming chaotic.
Tool Count3/5With only 3 tools, the count is within a reasonable range, but the presence of a placeholder-like tool suggests the set is not thoughtfully curated. The count itself is not excessive or too small, but the composition is questionable.
Completeness2/5The tool set lacks a clear domain, combining web search and dice rolling with an unspecified tool. This makes it impossible to determine if the surface is complete, and obvious gaps exist for any coherent workflow.
Average 2.1/5 across 3 of 3 tools scored. Lowest: 1.1/5.
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
- Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, and the description offers no behavioral details such as side effects, permissions, rate limits, or return behavior. The description is an empty placeholder, so the agent gets no transparency about what happens when the tool is invoked.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5Is the description appropriately sized, front-loaded, and free of redundancy?
While the text is extremely short, this is not conciseness but under-specification. A single placeholder sentence conveys no information, similar to the 'process' example. There is no structure, no front-loading, and no useful content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has one parameter, no output schema, and no annotations, the description needs to carry all contextual weight. It provides nothing, making the tool completely opaque to an AI agent. The context is entirely missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has one required parameter 'query' with type string and no description, yielding 0% schema description coverage. The description does not compensate by explaining the parameter's meaning, format, or acceptable values, leaving the agent completely uninformed about how to fill the parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose1/5Does the description clearly state what the tool does and how it differs from similar tools?
The description is the literal placeholder 'YOUR_TOOL_DESCRIPTION', which does not state any verb, resource, or functionality. It fails to distinguish this tool from siblings like web_search or roll_dice, providing zero information about what the tool does.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. There is no mention of context, prerequisites, or circumstances that would favor this tool, leaving the agent with no basis for tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must disclose behavioral traits. It only says 'Roll the dice,' which is a direct restatement of the tool name and adds no depth about random generation, validation, error handling, or return format. This is effectively a tautology with no added transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no waste, which is positive. However, it is under-specified: it front-loads little useful information and does not structure any context for the parameters. It cannot be considered 'appropriately sized' because it omits essential detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with two parameters, no output schema, and no annotations, the description is severely inadequate. It does not explain dice notation, the meaning of num_rolls, or any behaviors/limitations. Even the sibling context (web_search) offers no help in situating this tool, making the description insufficient for reliable tool invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. 'Given notation' loosely aligns with the 'notation' parameter but fails to define its format or semantics. The 'num_rolls' parameter is entirely absent from the description, leaving its purpose unexplained. Overall, minimal added meaning beyond the schema titles.
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 states a clear verb ('Roll') and resource ('dice'), indicating the tool's primary action. However, it does not specify what 'notation' means (e.g., standard dice notation like '2d6'), which leaves some ambiguity. It is distinct from the sibling web_search, but not explicitly differentiated.
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?
No guidance is provided on when to use this tool vs alternatives. The sibling list includes web_search, but the description gives no context for when dice rolling is appropriate or any exclusions. Users are left to infer usage from the name 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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It only says 'search the web' without explaining what the tool returns, any limitations (e.g., freshness, pagination), or side effects. This lack of detail leaves the agent uncertain about the tool's behavior beyond the obvious.
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 a single sentence, ten words long, and front-loaded with the core action. There is no wasted text or redundancy. It is appropriately concise for a simple tool, and every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is low-complexity with one parameter and no output schema. The description fails to explain the return value, result format, or any constraints/edge cases. Since there is no output schema, the description should cover what the agent can expect after invocation, but it does not. This makes the description incomplete for an agent to use correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has one parameter 'query' with a string type, and the description mentions 'the given query,' which is redundant. Since schema description coverage is 0%, the description should add meaning about the query format, examples, or constraints, but it does not. The parameter is self-explanatory, but the description adds no extra value.
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 function: 'Search the web for information about the given query.' It uses a specific verb ('search') and resource ('web'), and the query is self-evident. While it doesn't explicitly distinguish from siblings, the only sibling is 'roll_dice,' which is clearly unrelated, so no differentiation is needed.
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: use this tool when you need web information. However, it provides no explicit guidance on when to prefer this tool over alternatives, when not to use it, or any prerequisites. There is no mention of exclusions or comparison with the sibling tool, so it remains at an implied level.
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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