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LokiMCPUniverse

Hootsuite MCP Server

Server Quality Checklist

67%
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  • Latest release: v0.2.0

  • Disambiguation5/5

    Each tool has a unique purpose: creating posts, listing profiles, listing posts, deleting posts, and fetching analytics. No overlapping functionality.

    Naming Consistency5/5

    All tools follow a consistent verb_noun pattern: create_post, get_social_profiles, get_posts, delete_post, get_analytics.

    Tool Count5/5

    5 tools is well-scoped for a social media posting server, covering essential CRUD and analytics without bloat.

    Completeness4/5

    Covers create, read, delete, and analytics, but lacks an update post tool for editing. Minor gap but core workflows are supported.

  • Average 3.4/5 across 5 of 5 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 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?

    No annotations provided; description mentions scheduling but does not disclose effects, permissions, rate limits, or failure behavior. For a write operation, more context is needed.

    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?

    Concise: one main sentence plus three bullet points. No fluff, but could be more informative in the parameter list.

    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?

    Does not mention return value (though output schema exists), error behavior, or prerequisites. For a tool with 3 params and no annotations, description is 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?

    With 0% schema coverage, the description adds brief parameter explanations (text, social_profile_ids, scheduled_send_time) but lacks constraints (e.g., max length, format). Adds marginal value over bare schema titles.

    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?

    Clearly states 'Create and schedule a social media post on Hootsuite' – specific verb and resource, distinct from siblings (get_social_profiles, get_posts, delete_post, get_analytics).

    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 on when to use vs. alternatives; implicit that it's for creating posts, but no when-not-to or alternative tools mentioned.

    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 must convey behavioral traits. It only states the basic retrieval function and parameters, but does not disclose safety (non-destructive), authentication requirements, rate limits, or pagination behavior.

    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 (two sentences plus a bullet-like list), front-loaded with purpose, and contains no unnecessary words.

    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 two simple parameters and an output schema (assumed present), the description is adequate for basic use. However, it could clarify scope (e.g., for all profiles or a specific one) and whether the result includes metadata like total count.

    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 description coverage is 0%, but the description explains the limit parameter with default and maximum meaning, and the state parameter with example values ('scheduled, published, draft'). This adds significant meaning beyond the schema.

    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 it retrieves 'scheduled and published posts from Hootsuite', which is a specific verb and resource. While it distinguishes from creation/deletion tools, it doesn't explicitly differentiate from analytics or profile tools, but the resource type is clear.

    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 get_analytics or get_social_profiles. There is no mention of context or exclusions.

    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?

    No annotations exist, so description must disclose behavior fully. It states 'Delete' (mutation) and limits to 'scheduled or draft post', which is a key constraint. However, it omits side effects, reversibility, permissions, or output details. Important information missing beyond the basic action.

    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?

    Two sentences, front-loaded with the key action and resource. The arg description is directly relevant. No wasted words; highly efficient.

    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 1-parameter tool with an output schema, the description covers the basics. However, it misses critical context: whether the post must belong to the user, if deletion is permanent, or if the restriction to scheduled/draft is enforced. Not fully complete for safe 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?

    With 0% schema description coverage for post_id, the description adds meaning by stating 'The ID of the post to delete'. This clarifies what the parameter represents. However, it does not add format or validation hints beyond the schema's type string.

    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 action 'Delete' and the resource 'a scheduled or draft post from Hootsuite'. It distinguishes from sibling tools (create_post, get_*) but could be more precise about why only scheduled/draft posts are mentioned.

    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 usage is implied (delete a post) but there is no explicit guidance on when to use or not use this tool, nor alternatives. Since siblings don't include another delete tool, it's acceptable but still lacks explicit when-not guidance.

    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 provided, the description carries the full burden of behavioral disclosure. It only states that the tool 'gets' data, but does not confirm read-only behavior, mention pagination, rate limits, or error scenarios. The agent has minimal insight into side effects or operational nuances.

    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 concise and well-structured with a brief intro and a bulleted 'Args' section. Each sentence adds value, and there is no redundant or extraneous content.

    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 presence of an output schema, the description does not need to explain return values. However, it lacks context on data scope, authorization requirements, or behavior with invalid inputs. It is minimally adequate for a simple query tool but not comprehensive.

    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?

    The description adds meaningful detail beyond the schema: it explains that 'profile_ids' is a list of profile IDs, and specifies the ISO format for dates. This compensates for the 0% schema description coverage, though it could be more precise about the expected format of profile IDs.

    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 tool's purpose: 'Get analytics data for social profiles.' It uses a specific verb ('Get') and resource ('analytics data for social profiles'), and distinguishes itself from sibling tools that deal with posts or social profiles.

    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?

    The description provides no guidance on when to use this tool versus siblings or alternatives. There are no explicit conditions, prerequisites, or exclusions, leaving the agent to infer usage solely from the tool name and description.

    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 burden. It indicates a read-only retrieval but does not mention any limitations or side effects. For a simple list retrieval, the disclosure is adequate but minimal.

    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, concise sentence that directly conveys the tool's purpose without unnecessary words. It is appropriately front-loaded.

    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 zero parameters and the presence of an output schema (not shown but noted), the description is sufficiently complete. It explains what the tool returns without needing to detail the output structure.

    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?

    The tool has no parameters, and the schema coverage is 100%. While the description adds no parameter-specific information, the baseline for zero parameters is 4, as no further clarification is needed.

    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 verb 'Get', the resource 'list of social media profiles', and the context 'connected to Hootsuite'. It effectively distinguishes from sibling tools like create_post or get_analytics.

    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. The description lacks context about scenarios where this tool is preferred.

    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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