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cainmaila

gemini-cli-mcp

by cainmaila

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v1.0.1

  • Disambiguation2/5

    executeTask and executePrompt overlap heavily: both accept text input and return results plus metadata, with only vague wording about 'task' versus 'prompt' to distinguish them. executeImageTask and inspectGeminiCli are clearly distinct, but the two execution tools create real selection ambiguity.

    Naming Consistency4/5

    Three tools follow an execute* pattern and one uses inspect*, all in consistent camelCase. The pattern is readable and predictable, with the minor deviation being 'inspectGeminiCli' referring to a product rather than a generic action object.

    Tool Count5/5

    Four tools is well-scoped for a Gemini CLI wrapper: prompt execution, task execution, image generation, and introspection. Each tool earns its place without unnecessary bloat.

    Completeness4/5

    The set covers the primary workflows of running prompts, executing tasks, generating images, and inspecting the CLI environment. Minor gaps exist around configuration or extension management, but the core use cases are well covered.

  • Average 3.4/5 across 4 of 4 tools scored. Lowest: 2.8/5.

    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
  • This repository is licensed under MIT License.

  • 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

  • Behavior2/5

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

    With no annotations, the description carries the full burden of disclosing behavior, but it only promises a final answer and metadata. It does not mention that this invokes the local Gemini CLI, that approvalMode governs file-mutating behavior with a default of auto_edit, or anything about side effects and execution constraints.

    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 is short and mostly front-loaded, but the opening 'AI-friendly task interface' sentence is filler that does not earn its place. The functional sentence is concise, so this is adequate but not exemplary.

    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?

    For a tool with seven parameters, a rich output schema, and sibling tools, the description is too thin: it does not clarify when to use executeTask vs executePrompt/inspectGeminiCli, nor does it mention the underlying Gemini CLI execution model. The schema fills parameter details, but selection and invocation context remain incomplete.

    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 parameters are already documented in the schema. The description itself adds no parameter-level semantics beyond calling the input a 'task description,' which is sufficient only at baseline.

    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 title and description establish a generic task-execution tool: it accepts a task description and returns a final answer plus execution metadata. This is clear enough to distinguish 'task execution' from mere inspection, but it does not explicitly distinguish executeTask from sibling executePrompt, so it falls one step short of a 5.

    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 when-to-use guidance is present. The description never names alternatives like executePrompt or executeImageTask, nor does it state conditions that should route an agent to this tool rather than a sibling. This leaves tool selection to inference.

    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?

    With no annotations, the description carries full responsibility for disclosing behavioral traits. It mentions running a prompt and returning metadata, but omits potential side effects such as code execution, credential requirements, or approval behaviors implied by the approvalMode enum (including 'yolo' and 'auto_edit'). No warnings about destructive or mutating outcomes are given.

    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 19-word sentence that front-loads the verb, resource, and scope. Every word contributes; there is no filler or repetition.

    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?

    Even with complete parameter schema and an output schema, the description is too thin for a tool that wraps an external CLI with potentially risky approval modes. Missing context includes when to prefer it over siblings, prerequisites like having the Gemini CLI installed, and behavioral safety. An agent could call it wrongly or be surprised by side effects.

    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 all five parameters already have individual descriptions. The tool-level description adds no parameter-specific meaning beyond framing the prompt as 'non-interactive', which is not enough to lift above the baseline of 3.

    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 states a specific action ('Runs a non-interactive prompt') and resource ('locally installed Gemini CLI'), and adds a distinctive output ('final result plus execution metadata'). This clearly separates it from executeImageTask and inspectGeminiCli, though overlap with executeTask is not explicitly addressed.

    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 siblings like executeTask or executeImageTask. There are no exclusions, prerequisites, or alternative routing hints; the only implicit signal is 'non-interactive', which is not developed into actionable direction.

    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 carries the full burden of behavioral disclosure. It does reveal that images are saved and that metadata is returned, which is useful, but it omits caveats about external dependencies, failure behavior, or approval modes. Transparency is partial but not absent.

    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 front-loaded sentence with no wasted words. It efficiently communicates the mechanism, the operation, and the output type.

    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?

    The description is adequate for identifying the tool's core purpose, and the output schema covers return details. However, without annotations or usage guidance, and with several sibling tools, the description leaves gaps around when to choose this tool and what side effects to expect beyond saving images.

    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 documents all seven parameters. The description adds no additional parameter-level semantics beyond what the schema provides, which is the baseline case.

    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 states a specific action ('generate images') and a specific resource ('nanobanana extension'), and it also states what is returned ('saved image paths plus execution metadata'). This clearly differentiates it from the generic sibling tools executeTask and executePrompt.

    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 implies use for image-generation tasks through nanobanana, but it gives no explicit when-to-use or when-not-to-use guidance. It does not mention alternatives or exclusions, so the agent must infer the appropriate context.

    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 carries the full burden. 'Lists' suggests a read-only inspection behavior, but it does not explicitly state that nothing is modified, whether any commands are executed, or whether the optional model-reported summary incurs extra cost or latency. It is adequate but not fully transparent.

    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, tight sentence that enumerates the output categories up front and wastes no words. It is easy to scan and immediately actionable.

    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?

    The output schema is present, no parameters are required, and the description clearly enumerates the returned information categories. It could note that timeoutMs applies to each inspection command or clarify the side-effect-free nature, but overall the information is sufficient for an agent to invoke the tool correctly.

    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%; both parameters already have descriptive text in the schema. The tool description only adds a passing reference to the model-reported tool summary and does not meaningfully extend the parameter understanding beyond what the schema already provides.

    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 states a specific verb ('Lists') and clearly identifies the resource scope: Gemini CLI commands, extensions, skills, configured MCP servers, and an optional model-reported tool summary. This fully distinguishes it from the execute* sibling tools, which focus on running tasks.

    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 implies that this tool is for inspection rather than execution, but it never explicitly says when to choose it over the sibling tools or lists any exclusion conditions. An agent would have to infer the intended usage from the verb and resource enumeration.

    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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