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gesslar

FluffOS MCP Server

by gesslar
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Server Quality Checklist

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

  • Latest release: v1.0.0

  • Disambiguation5/5

    The two tools have clearly distinct purposes: disassemble focuses on showing compiled bytecode for debugging, while validate checks for compilation errors and success/failure. There is no overlap or ambiguity between these functions.

    Naming Consistency5/5

    Both tools follow a consistent 'fluffos_verb' naming pattern (fluffos_disassemble and fluffos_validate), using the same prefix and verb-based structure. This makes them predictable and easy to identify.

    Tool Count2/5

    With only 2 tools, the server feels thin for a FluffOS/LPC development environment. While disassembly and validation are useful, typical development workflows would benefit from additional tools like code execution, file management, or debugging support, making this set under-scoped.

    Completeness2/5

    The server covers only disassembly and validation, leaving significant gaps for a FluffOS development tool. Missing are core operations like running LPC code, editing files, managing projects, or advanced debugging features, which limits agents' ability to handle comprehensive development tasks.

  • Average 3.4/5 across 2 of 2 tools scored.

    See the Tool Scores section below for per-tool breakdowns.

    • No community issues in the last 6 months
    • 22 commits in the last 12 weeks
    • Last stable release on
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI is passing

  • This repository is licensed under BSD Zero Clause License.

  • This repository includes a README.md file.

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Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

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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 the tool is 'useful for debugging and understanding how code compiles,' which gives some behavioral context about its purpose. However, it doesn't disclose important behavioral traits like whether this is a read-only operation, what permissions are needed, whether it modifies the file, error handling, or output format details.

    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 appropriately sized and front-loaded. The first sentence clearly states the core functionality, and the second sentence adds valuable context about when to use it. Both sentences earn their place with zero waste.

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

    Completeness3/5

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

    Given the tool has 1 parameter with 100% schema coverage and no output schema, the description provides adequate but minimal context. It explains what the tool does and its use cases, but for a tool with no annotations and no output schema, it should ideally provide more behavioral details about what the disassembly output looks like or any limitations.

    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 schema description coverage is 100%, with the single parameter 'file' well-documented in the schema. The description doesn't add any parameter-specific information beyond what the schema provides. With high schema coverage, the baseline score of 3 is appropriate as the description doesn't compensate but doesn't need to.

    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: 'Disassemble an LPC file to show compiled bytecode using lpcc.' It specifies the verb (disassemble), resource (LPC file), and method (using lpcc). However, it doesn't explicitly differentiate from the sibling tool 'fluffos_validate', which appears to be a different operation.

    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?

    The description provides implied usage context: 'Useful for debugging and understanding how code compiles.' This suggests when to use the tool, but doesn't explicitly state when not to use it or mention alternatives. No comparison to the sibling tool 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?

    With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the validation outcome ('success/failure and any compilation errors'), which is useful context beyond basic functionality. However, it doesn't address important behavioral aspects like error handling, performance characteristics, or whether this operation has side effects.

    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 perfectly concise with two sentences that each earn their place: the first states the core functionality, and the second describes the return value. There's zero waste or redundancy, and it's appropriately front-loaded with the main purpose.

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

    Completeness3/5

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

    For a single-parameter validation tool with no annotations and no output schema, the description provides adequate but minimal information. It covers what the tool does and what it returns, but doesn't address potential complexities like what constitutes validation success versus failure, error message formats, or limitations of the validation process.

    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 description coverage is 100%, so the schema already fully documents the single 'file' parameter. The description doesn't add any additional meaning about the parameter beyond what the schema provides, such as file format requirements or validation scope limitations. The baseline of 3 is appropriate when the schema does all the parameter documentation work.

    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?

    The description clearly states the specific action ('validate an LPC file') and resource ('using the FluffOS driver's symbol tool'), distinguishing it from the sibling tool 'fluffos_disassemble' which implies a different operation. It provides a complete verb+resource+scope statement.

    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?

    No guidance is provided on when to use this tool versus alternatives. While the sibling tool name suggests a different function, the description doesn't explicitly state when to choose validation over disassembly or other potential options. There's no mention of prerequisites or context for usage.

    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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  • Confirm that the MCP server is working as expected.
  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

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