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Cherine0205

BioNext-mcp

by Cherine0205
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Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v2.1.0

  • Disambiguation5/5

    Each tool has a clearly distinct purpose: planning analysis (analyze_bioinformatics_task), executing scripts (execute_claude_script), and debugging (debug_workflow). No functional overlap.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun snake_case pattern (e.g., analyze_bioinformatics_task, debug_workflow, execute_claude_script), making them predictable.

    Tool Count5/5

    With only 3 tools, the set is well-scoped for its bioinformatics workflow automation purpose—each tool is essential and not excessive.

    Completeness4/5

    The tools cover planning, execution, and debugging—the core workflow. Minor gap: no explicit data retrieval or result analysis tool, but execution report generation partially addresses this.

  • Average 3.3/5 across 3 of 3 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

  • This repository is licensed under MIT License.

  • This repository includes a README.md file.

  • No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.

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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?

    With no annotations provided, the description bears full responsibility for disclosing behavioral traits. It indicates the tool is analytical ('analyze', 'provide debugging insights'), implying a read-only operation, but does not confirm lack of side effects, required permissions, rate limits, or output format. The minimal disclosure leaves significant ambiguity about its behavior.

    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 sentence that immediately conveys the tool's purpose without any extraneous words. It is front-loaded and efficient, earning its place with no waste.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness2/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    Given the tool has no output schema and no annotations, the description should compensate by explaining what the debugging insights include (e.g., error logs, step traces) or any other behavioral details. The current description is too brief to cover the tool's complexity, leaving users uninformed about the results and operational context.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters3/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    The input schema has 100% description coverage, so both parameters (workflow_id, error_context) are already documented. The description does not add any parameter-specific meaning beyond what the schema provides. Per guidelines, baseline 3 is appropriate since schema handles the burden.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose4/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description clearly states the tool's purpose: 'Analyze workflow execution results and provide debugging insights'. It specifies a verb ('analyze') and a resource ('workflow execution results'), making the core function understandable. However, it does not explicitly distinguish this tool from its siblings (analyze_bioinformatics_task, execute_claude_script), though the names imply different domains.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines2/5

    Does 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, no prerequisites, and no exclusion criteria. It simply states what the tool does without context for decision-making, leaving the agent without direction on when this tool 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 must disclose behavioral traits. It states the tool 'analyzes' and 'creates a plan', implying read-only, but does not specify side effects, permissions, or output format. The instruction to ask Claude for scripts is meta-guidance, not 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.

    Conciseness5/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    The description is extremely concise: two sentences covering purpose and usage flow. Every sentence earns its place with no redundancy. It is front-loaded with the primary action.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness2/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    Given no output schema and three parameters, the description fails to specify what the tool returns (the workflow plan). The agent lacks information on how to use the tool's output. The mention of script generation is helpful but not sufficient to cover return value expectations.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters3/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    Schema coverage is 100%, so the description need not repeat parameter details. The description does not add new semantics beyond the schema's descriptions. Baseline of 3 is appropriate as no value is added.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose4/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description clearly states the tool analyzes user intent and creates a bioinformatics workflow plan. It distinguishes from siblings (debug_workflow, execute_claude_script) by placing itself as the initial planning step. However, it could be more specific about the form of the workflow plan output.

    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 usage context: use this tool first to understand goals and prepare workflow, then generate scripts (≤100 lines), then execute them. It implies the tool is for planning before script generation/execution. Explicit 'when not to use' or alternatives are missing, but the flow is well-defined.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior4/5

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

    Description discloses several behavioral aspects: auto-detection, installation, package management, logging, script length monitoring, and report generation. However, it does not address potential destructive effects of script execution.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness3/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    The description uses bullet points and emojis which are clear but somewhat verbose. Could be more succinct.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness2/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    The tool lacks an output schema, and the description does not explain what the tool returns to the agent (e.g., execution result, path to report). Missing this information for agent decision-making.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters3/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    Schema already provides descriptions for all three parameters. The tool description does not add further parameter semantics beyond what is in the schema.

    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?

    Description clearly states the tool detects and executes Python scripts for bioinformatics tasks, distinguishing it from sibling tools that analyze tasks or debug workflows.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines3/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    Despite listing features, the description does not provide explicit guidance on when to use this tool versus siblings. Usage context is implied but not stated.

    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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