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rekog-labs

Counting MCP Server

by rekog-labs
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Server Quality Checklist

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

  • Latest release: v0.0.1

  • Disambiguation5/5

    With only one tool, there is no possibility of confusing it with another tool. The tool's purpose is clearly defined as counting occurrences of a specific character in text.

    Naming Consistency5/5

    The single tool name 'count-characters' follows a clear verb_noun pattern. Since there is only one tool, naming consistency is trivially maintained.

    Tool Count4/5

    One tool is slightly below the typical 3-15 range, but it is reasonable for a server dedicated to a single specific function. The narrow scope justifies having just one tool.

    Completeness5/5

    For the domain of counting character occurrences, the tool fully covers the intended operation with no dead ends. The server does exactly what its name and description indicate.

  • Average 3.3/5 across 1 of 1 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

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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 fully disclose behavioral traits, but it only states the basic counting operation. It does not clarify case sensitivity, whether the 'character' parameter must be a single character, or how multi-character strings are handled. These gaps could lead to incorrect invocation.

    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 with zero filler, front-loading the action and the target. Every word earns its place.

    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 simple two-parameter tool, the schema covers parameter meanings, but there is no output schema and no explicit statement of the return value or edge-case behavior. The description is adequate for the straightforward case but leaves subtle behavior (case sensitivity, multi-character input) undefined.

    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%, with both 'text' and 'character' documented in the input schema. The description adds no further semantic detail beyond the schema, so the baseline score of 3 is appropriate.

    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 uses a specific verb ('counts') and names the resource ('occurrences of a specific character in text'), making the tool's purpose unambiguous. Even though no sibling tools are listed, the operation is clearly differentiated from any general text manipulation tool.

    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?

    There is no guidance on when to use this tool versus alternatives, and no usage context is provided. The description is a bare statement of functionality with no mention of intended scenarios, limitations, or exclusions.

    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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