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Server Quality Checklist

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  • Latest release: v1.0.0

  • Disambiguation5/5

    The two tools have clearly distinct purposes: channels_list retrieves a list of channels, while conversations_history fetches messages from a specific channel. There is no overlap in functionality, making it easy for an agent to select the correct tool based on the task.

    Naming Consistency4/5

    Both tools follow a consistent snake_case naming convention, but the patterns differ slightly: channels_list uses a noun_verb format, while conversations_history uses a noun_noun format. This minor deviation prevents a perfect score, but the naming is still readable and mostly consistent.

    Tool Count2/5

    With only 2 tools, this server feels too thin for a Slack integration, as it lacks essential operations like sending messages, managing users, or updating channel settings. The scope is severely limited, making it difficult for agents to perform comprehensive Slack-related tasks.

    Completeness2/5

    The tool surface is significantly incomplete for a Slack domain. While it covers listing channels and retrieving message history, it misses critical operations such as posting messages, creating channels, or handling reactions, which are core to Slack workflows and will likely cause agent failures.

  • Average 3.1/5 across 2 of 2 tools scored.

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

    • 14 of 36 community issues answered or closed in the last 6 months
    • 0 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 failing
  • 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 provided, the description carries the full burden of behavioral disclosure. It only states the action ('Get list') without addressing permissions, rate limits, pagination, or what 'list' entails (e.g., format, completeness). This is inadequate for a tool that likely interacts with a chat system, where such details are critical.

    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 with just three words, front-loaded with the core action. There's no wasted text, making it efficient for quick understanding, though this brevity contributes to gaps in other dimensions.

    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 annotations and no output schema, the description is incomplete. It lacks details on behavioral traits (e.g., safety, performance), output format, and usage context. For a tool with parameters and likely complex interactions in a chat system, this minimal description fails to provide sufficient context for effective agent use.

    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 fully documents both parameters (channel_types and sort). The description adds no parameter-specific information beyond what's in the schema, meeting the baseline score of 3 for high schema coverage without additional value.

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

    Purpose3/5

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

    The description 'Get list of channels' clearly states the verb ('Get') and resource ('channels'), but it's vague about scope and doesn't distinguish from the sibling tool 'conversations_history'. It doesn't specify whether this retrieves all channels, user-accessible channels, or some subset, leaving purpose ambiguous beyond the basic action.

    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 like 'conversations_history'. The description doesn't mention context, prerequisites, or exclusions, leaving the agent to infer usage based solely on the tool name and parameters.

    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 describes pagination behavior and the interaction between 'cursor' and 'limit' parameters, which adds useful context beyond the input schema. However, it doesn't cover other behavioral aspects such as rate limits, authentication requirements, error handling, or what the response format looks like (e.g., structure of returned messages). For a tool with no annotations, this leaves gaps in understanding its full behavior.

    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 a single sentence that efficiently conveys the core functionality and key behavioral detail (pagination). It is front-loaded with the main purpose and avoids unnecessary words. However, it could be slightly more structured by separating the pagination explanation into a second sentence for clarity, but overall it's concise and to the point.

    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's complexity (3 parameters, no output schema, no annotations), the description is moderately complete. It covers the purpose and pagination behavior but lacks details on response format, error conditions, or broader usage context. Without an output schema, the description doesn't explain what the tool returns (e.g., message structure), which is a significant gap. It's adequate for basic understanding but incomplete for full agent usage.

    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%, meaning the input schema already documents all parameters thoroughly. The description adds some semantic context by explaining how pagination works with the cursor and the constraint that 'limit' must be empty when 'cursor' is provided, which clarifies parameter interactions. However, it doesn't provide significant additional meaning beyond what's in the schema descriptions, such as examples or edge cases, so it meets the baseline for high schema coverage.

    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: 'Get messages from the channel by channel_id'. It specifies the resource (messages) and the required parameter (channel_id), making the verb+resource combination explicit. However, it doesn't distinguish this tool from its sibling 'channels_list', which appears to list channels rather than messages, so the differentiation is implied but not explicit.

    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 some usage guidance by explaining pagination with the cursor parameter and noting that 'limit' must be empty when 'cursor' is provided. This gives context for when to use certain parameters. However, it doesn't explicitly state when to use this tool versus alternatives like 'channels_list' or other hypothetical tools, nor does it provide broader context on when this tool is appropriate versus other methods for retrieving messages.

    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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