battery-analyzer-mcp
Server Quality Checklist
Latest release: v0.1.0
- Disambiguation5/5
Each tool has a distinct purpose: two specific calculation methods (Dunn, GITT) plus two listing tools (methods, data files). No ambiguity between them.
Naming Consistency4/5All tool names use snake_case with verb_noun pattern (calculate_, list_). Only minor inconsistency is 'list_data_files_tool' includes the word 'tool', but overall pattern is clear.
Tool Count5/5Four tools is appropriate for a specialized battery analyzer MCP. Not too few, not too many, covering core functionality without bloat.
Completeness4/5Covers listing methods/data and running two major analysis methods. Missing a generic 'run analysis' tool that selects method, but list_battery_methods helps guide the agent. Minor gap.
Average 4/5 across 4 of 4 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 5 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 must carry the full burden. It does not disclose side effects, authentication needs, or whether the tool modifies data. The description focuses on parameters and return value, but lacks behavioral context.
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 well-structured with Args and Returns sections, and the main purpose is front-loaded. It is slightly verbose but every sentence adds value. Could be tightened slightly, but overall good.
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?
The description covers all parameters, default values, and the return format. It references the data folder, which provides context. However, it does not mention prerequisites such as file existence or format, or error handling. Output schema exists, so return details are sufficient.
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 adds substantial meaning. Each parameter is explained with its purpose, default value, and units (e.g., 'Electrode thickness in cm'). The note about '.xlsx added if omitted' adds practical semantics.
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 tool runs the GITT method on an Excel file, specifying the verb 'Run' and the resource 'titration Excel file'. It distinguishes from siblings like 'calculate_dunn' which likely runs a different method.
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 does not provide guidance on when to use this tool versus alternatives such as 'calculate_dunn'. There is no explanation of prerequisites or scenarios where this method is appropriate.
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. It discloses that .xlsx extension is added if omitted and specifies the return structure, but fails to mention error handling, file existence requirements, or whether the tool modifies data.
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 concise yet complete, using a clear docstring format with summary, Args, and Returns sections. Every sentence adds necessary information without redundancy.
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 2 parameters, no annotations, and an output schema (which explains return values), the description covers the basics but lacks details like required file format, error handling, and prerequisite conditions. Could be more robust.
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%, but the description adds meaningful context for both parameters: file_name explains the data folder and automatic .xlsx addition, and max_plot_points explains default and purpose. This adds significant value beyond the bare schema.
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 tool runs the Dunn method on cyclic voltammetry Excel files from a data folder, using a specific verb and resource. It distinguishes itself from siblings like calculate_gitt (for GITT) and list_data_files_tool (for listing files).
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 context (cyclic voltammetry Excel files) but does not explicitly state when to use this tool over alternatives like calculate_gitt or list_battery_methods. No exclusion criteria or when-not-to-use guidance is provided.
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 must disclose behavior. It states 'list', implying a read-only operation, but does not elaborate on data sources or confirm no side effects. With zero parameters and an output schema, the behavior is straightforward but minimally described.
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, clear sentence that front-loads the key information. No unnecessary 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 no parameters, an output schema exists, and the sibling tools are clearly different, the description is complete. It sufficiently informs the agent of the tool's purpose and output.
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?
There are no parameters, so the baseline is 4. The description adds value by specifying that the output includes battery analysis methods and their Excel input formats, which is useful context beyond the empty schema.
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 tool's purpose: listing available battery analysis methods and their expected Excel input formats. It uses a specific verb ('list') and resource ('battery analysis methods'), and it distinguishes from sibling tools like calculate_dunn and list_data_files_tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implicitly indicates usage: to discover available methods and input formats. It does not explicitly state when not to use it or provide alternatives, but the sibling context makes the differentiation clear.
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, and the description does not disclose behavioral traits such as read-only nature or performance implications. For a simple listing tool, minimal transparency is acceptable but not ideal.
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 concise sentence with no wasted words, perfectly front-loaded.
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 no parameters and an output schema, the description sufficiently explains the tool's function. No additional details are necessary.
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?
There are no parameters, so the schema covers 100% of input. The description adds no param info but none is needed; baseline score of 4 is appropriate.
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 verb 'List', specifies the resource '.xlsx input files', and the location 'MCP server data folder'. It is specific and distinguishable from sibling tools like calculate_dunn.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The purpose is self-evident and siblings are different, so usage is clear. However, no explicit when/when-not guidance is provided, which could be improved.
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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