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aurasoph

klone-mcp

by aurasoph
OverviewSchemaRelated ServersScoreDiscussions
Python
Local

Server Quality Checklist

58%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v0.1.0

  • Disambiguation5/5

    The two tools serve completely distinct purposes: one writes files verbatim, the other executes shell commands. There is no ambiguity or overlap.

    Naming Consistency5/5

    Both tools follow the same 'klone_verb_noun' pattern using snake_case, making the naming predictable and consistent.

    Tool Count5/5

    With only two tools, the server is minimal but effective. The 'run' tool can execute arbitrary shell commands, covering a wide range of operations, so the count is well-scoped for the domain.

    Completeness5/5

    The tool surface covers the core needs for cluster interaction: file writing and command execution. Missing operations like file reading or deletion are easily accomplished via the run tool, making the set complete for the inferred domain.

  • Average 4.5/5 across 2 of 2 tools scored.

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

    • No community issues in the last 6 months
    • 1 commit 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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  • This repository includes a README.md file.

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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

  • Behavior4/5

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

    No annotations provided, so description carries full burden. Discloses stdin-based piping, no size limit, no shell interpretation. Missing details on error handling and permissions, but overall transparent.

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

    Conciseness4/5

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

    Front-loaded with purpose, then technical detail, then usage guidance. Every sentence adds value, though slightly lengthy. Well-structured.

    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?

    Two parameters, no annotations, output schema exists but description does not mention return format. Missing constraints like directory support or overwrite behavior. Adequate but incomplete.

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

    Parameters4/5

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

    Schema has 0% description coverage; description adds meaning: 'path' is a file path, 'content' is exact bytes. Explains that shell metacharacters are not interpreted, which goes beyond 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 'Create or overwrite a file on klone with the given content', specifying verb and resource. It distinguishes itself from sibling 'klone_run' by detailing file-writing use cases.

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

    Usage Guidelines5/5

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

    Explicitly states when to use (SLURM scripts, configs, small data) and when not to (very large data: use rsync/scp). Also provides prerequisite guidance for SLURM scripts.

    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?

    No annotations are provided, so the description carries the full burden. It discloses that the command is run by the remote shell (so pipes and redirects work), that it returns stdout, and that timeout controls wait time. It does not mention stderr handling, exit codes, or potential security risks, but for a command execution tool, this is fairly transparent.

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

    Conciseness4/5

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

    The description is relatively long but well-structured: it starts with a clear purpose sentence, then provides operational details in a logical flow, and ends with an orientation note. It could be more concise, but the length is justified by the amount of useful information. Front-loading is good.

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

    Completeness4/5

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

    Given that there are only 2 parameters, no annotations, but an output schema (not shown), the description covers purpose, usage guidelines, parameter details, and orientation. It does not explain the output schema, but that is handled by the schema itself. It is comprehensive for a shell command execution tool.

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

    Parameters5/5

    Does 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 explains `cmd` as being run by the remote shell with support for shell syntax, and `timeout` as controlling wait time in seconds with a default of 60 and a note to bump for expensive queries. This adds significant meaning beyond the bare 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?

    The description begins with a clear verb+resource: 'Run a shell command on klone and return its stdout.' This distinguishes it from the sibling tool 'klone_put_file', which handles file transfer. It precisely states 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 Guidelines5/5

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

    The description provides extensive guidance: it explains that `cmd` supports pipes and redirects, lists typical use cases (SLURM, job inspection), warns against long-running work and suggests using `sbatch` instead, and explains the `timeout` parameter with a suggestion to bump for expensive queries. It also recommends reading a quickstart doc for orientation. This explicitly tells when and when not to use the tool.

    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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