SociaVault MCP Server

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation5/5
Every tool has a clearly distinct purpose targeting specific social media platforms and data types (profiles vs. posts/videos). There is no ambiguity—get_facebook_profile, get_instagram_posts, get_reddit_subreddit, etc., are all uniquely scoped by platform and resource.
Naming Consistency5/5
All tools follow a consistent verb_noun pattern with 'get_' prefix, platform name, and resource type (e.g., get_facebook_profile, get_instagram_posts). The naming is perfectly predictable and uniform across all 11 tools.
Tool Count5/5
With 11 tools covering multiple social media platforms (Facebook, Instagram, Reddit, Threads, TikTok, Twitter/X, YouTube), the count is well-scoped and appropriate. Each tool earns its place by addressing a distinct data retrieval need without bloat.
Completeness4/5
The toolset provides comprehensive read-only coverage for profile and post/video data across major social platforms, with no obvious gaps for its retrieval-focused domain. A minor gap is the lack of tools for creating or updating content, but this aligns with a data-fetching server purpose.
Average 2.8/5 across 11 of 11 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 9 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.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
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```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
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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 carries the full burden of behavioral disclosure. 'Get YouTube channel data' implies a read-only operation but doesn't specify if it requires authentication, rate limits, error handling, or what the output format might be. This is a significant gap for a tool with no annotation coverage.
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, efficient sentence with no wasted words. It's front-loaded and to the point, though it could benefit from more detail to improve clarity and completeness.
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 the complexity of retrieving YouTube channel data, the lack of annotations, and no output schema, the description is incomplete. It doesn't explain what data is returned, potential limitations, or behavioral aspects, making it inadequate for effective tool 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?
The input schema has 100% description coverage, with the parameter 'handle' documented as 'YouTube channel handle or @username'. The description adds no additional meaning beyond this, as it doesn't elaborate on parameter usage or constraints. With high schema coverage, 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.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get YouTube channel data' states a clear verb ('Get') and resource ('YouTube channel data'), which is better than a tautology. However, it's vague about what specific data is retrieved (e.g., metadata, videos, statistics) and doesn't distinguish from sibling tools like get_facebook_profile or get_tiktok_profile beyond the platform name. This leaves the purpose somewhat ambiguous.
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 alternatives. It doesn't mention any prerequisites, context for usage, or comparisons to sibling tools (e.g., for social media data retrieval). This lack of guidance makes it unclear when this tool is appropriate.
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 are provided, so the description carries the full burden of behavioral disclosure. It states the action ('Get') but doesn't describe traits like whether authentication is required, rate limits, error handling, or what the output format might be (e.g., JSON with specific fields). For a tool with no annotations, this is a significant gap in transparency.
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 a single sentence 'Get Facebook profile/page data'. It is front-loaded and wastes no words, making it easy to parse. Every word earns its place by specifying the action and target, though it could benefit from more detail.
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 the tool's complexity (a data retrieval tool for a social media platform), lack of annotations, and no output schema, the description is incomplete. It doesn't explain what data is returned, any limitations (e.g., public data only), or behavioral aspects. This leaves the agent with insufficient context to use the tool effectively.
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?
The input schema has 100% description coverage, with the single parameter 'url' documented as 'Facebook profile or page URL'. The description adds no additional meaning beyond this, such as URL format examples or validation rules. According to the rules, with high schema coverage, the baseline is 3 even without param info in the description.
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 Facebook profile/page data' states a verb ('Get') and resource ('Facebook profile/page data'), making the purpose understandable. However, it's vague about what specific data is retrieved (e.g., basic info, posts, followers) and doesn't differentiate from sibling tools like 'get_instagram_profile' beyond the platform name. This is minimal but not specific enough for a higher score.
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 alternatives. It doesn't mention any prerequisites, context for use (e.g., for social media analysis), or exclusions (e.g., not for private profiles). With multiple sibling tools for different platforms, this lack of differentiation leaves the agent without clear usage instructions.
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 are provided, so the description carries the full burden of behavioral disclosure. It states 'Get' implies a read operation, but doesn't specify any behavioral traits such as rate limits, authentication needs, pagination, or what happens on errors. For a tool with no annotation coverage, this is a significant gap in transparency.
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-loading the key action and resource. There is no wasted language or redundancy, making it efficient and easy to parse, 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 the tool's complexity (a read operation with one parameter), lack of annotations, and no output schema, the description is incomplete. It doesn't explain what 'posts' entails (e.g., format, limits, sorting) or any behavioral aspects, leaving the agent with insufficient context to use the tool effectively beyond basic parameter input.
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?
The input schema has 100% description coverage, with the parameter 'subreddit' documented as 'Subreddit name (without r/)'. The description adds no additional meaning beyond this, as it doesn't elaborate on parameter usage or constraints. With high schema coverage, the baseline score of 3 is appropriate, as the schema handles the parameter documentation adequately.
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 Reddit subreddit posts' clearly states the verb ('Get') and resource ('Reddit subreddit posts'), making the purpose understandable. However, it lacks specificity about what 'posts' means (e.g., recent, top, all) and doesn't differentiate from sibling tools like 'get_twitter_tweets' beyond platform naming. This makes it vague in scope but not tautological or misleading.
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 alternatives. It doesn't mention any context, prerequisites, or exclusions, and with sibling tools for other social media platforms, there's no indication of when Reddit-specific retrieval is appropriate. This leaves the agent without usage direction.
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 are provided, so the description carries the full burden of behavioral disclosure. It only states the action ('Get') without any details on permissions, rate limits, response format, or error handling. For a read operation with zero annotation coverage, this lacks critical behavioral context, though it doesn't contradict annotations.
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—a single phrase with no wasted words. It's front-loaded with the core action and resource, making it easy to parse quickly. This minimalism is efficient for a simple tool, though it may sacrifice detail.
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 the lack of annotations and output schema, the description is incomplete. It doesn't explain what data is returned (e.g., profile fields, structure) or any behavioral traits. For a tool with one parameter but no structured output information, more context is needed to guide the agent effectively.
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?
The input schema has 100% description coverage, with the 'handle' parameter documented as 'Threads username'. The description adds no additional meaning beyond this, such as format examples or validation rules. With high schema coverage, the baseline score of 3 is appropriate, as the schema already provides adequate parameter semantics.
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 Threads profile data' clearly states the action (get) and resource (Threads profile data), but it's vague about what specific data is retrieved. It distinguishes from siblings like get_threads_posts (which gets posts) but doesn't specify if it returns basic info, stats, or full profile details, leaving the purpose somewhat ambiguous.
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 alternatives. It doesn't mention prerequisites (e.g., needing a valid handle), exclusions, or comparisons to siblings like get_facebook_profile or get_twitter_profile, leaving the agent to infer usage context from the tool name alone.
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 states it 'gets' data, implying a read-only operation, but doesn't specify authentication needs, rate limits, error conditions, or what the return data looks like (e.g., JSON structure). This is a significant gap for a tool with no annotation coverage.
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, efficient sentence with zero wasted words. It's front-loaded and appropriately sized for a simple tool, earning full marks for conciseness.
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 doesn't explain what profile data is returned (e.g., bio, follower count), potential errors, or behavioral traits. For a tool with no structured support, this leaves critical gaps for an AI agent.
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?
The input schema has 100% description coverage, with the 'handle' parameter documented as 'TikTok username'. The description adds no additional meaning beyond this, so it meets the baseline of 3 where the schema does the heavy lifting.
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 TikTok profile data' clearly states the action (get) and resource (TikTok profile data), but it's vague about what specific data is retrieved and doesn't distinguish it from sibling tools like get_tiktok_videos. It's a minimal but functional purpose statement.
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 alternatives like get_tiktok_videos or other profile tools (e.g., get_instagram_profile). There's no mention of prerequisites, context, or exclusions, leaving usage entirely implicit.
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 but offers minimal information. It states what the tool does ('Get Instagram posts') but doesn't describe how it behaves—e.g., whether it requires authentication, has rate limits, returns recent or all posts, includes metadata, or handles errors. This leaves significant gaps for a tool that likely interacts with an external API.
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 and front-loaded with a single, clear sentence that directly states the tool's function. There is no wasted language or unnecessary elaboration, making it efficient and easy to parse, though this conciseness comes at the cost of completeness 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 the complexity of interacting with Instagram's API (implied by the tool's function) and the lack of annotations and output schema, the description is incomplete. It doesn't address behavioral aspects like authentication needs, rate limits, or return format, which are critical for effective tool use. The description alone is insufficient for an agent to understand the full context of invoking this tool.
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?
The description adds no parameter-specific information beyond what the input schema provides. Since schema description coverage is 100% (the 'handle' parameter is documented as 'Instagram username'), the baseline score of 3 applies. The description doesn't elaborate on parameter usage, such as format requirements or examples, but the schema adequately covers the essentials.
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 with a specific verb ('Get') and resource ('Instagram posts from a user'), making it immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_instagram_profile' or 'get_threads_posts', which would require mentioning it retrieves posts specifically rather than profile information or content from other platforms.
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 alternatives. It doesn't mention sibling tools like 'get_instagram_profile' for profile data instead of posts, or 'get_threads_posts' for similar content from a different platform. There are no explicit when/when-not instructions or prerequisites, leaving usage context implied at best.
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 are provided, so the description carries full burden for behavioral disclosure. 'Get Instagram profile data' implies a read-only operation but doesn't specify authentication requirements, rate limits, data freshness, or what happens with invalid handles. For a tool accessing external APIs with no annotation coverage, this leaves significant behavioral questions unanswered.
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 at just four words, front-loading the essential purpose with zero wasted words. Every word earns its place, making it immediately scannable and understandable despite its brevity.
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 no annotations, no output schema, and accessing external social media data, the description is insufficiently complete. It doesn't explain what profile data is returned (basic info, statistics, media), authentication needs, rate limits, or error handling. The context signals show this is a simple single-parameter tool, but the external API nature requires more disclosure than provided.
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?
The input schema has 100% description coverage with 'handle' clearly documented as 'Instagram username'. The description doesn't add any parameter semantics beyond what the schema provides (no format examples, character limits, or validation rules). With complete schema coverage, the baseline score of 3 is appropriate as the description doesn't compensate but doesn't need to.
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 'Get Instagram profile data' clearly states the verb ('Get') and resource ('Instagram profile data'), making the purpose immediately understandable. However, it doesn't differentiate this tool from its sibling 'get_instagram_posts' which also retrieves Instagram data, nor does it specify what aspects of a profile are retrieved (bio, followers, etc.).
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 alternatives. With siblings like 'get_instagram_posts' and 'get_tiktok_profile' available, there's no indication whether this is for basic profile info versus posts, or how it differs from other social media profile tools. No exclusions or prerequisites are 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 provided, the description carries full burden for behavioral disclosure but offers minimal information. It states what the tool does but doesn't cover critical aspects like whether it's read-only, rate limits, authentication needs, pagination, error handling, or what format the posts are returned in. For a tool with zero annotation coverage, this is inadequate.
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, efficient sentence with zero wasted words. It's front-loaded with the core functionality ('Get posts from a Threads user'), making it immediately clear. Every word earns its place, achieving optimal conciseness.
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 the lack of annotations and output schema, the description is incomplete. It doesn't explain what 'posts' entail (e.g., content, metadata, media), how many are returned, or any behavioral traits. For a tool that likely involves network calls and data retrieval, more context is needed to guide the agent effectively.
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 the single parameter 'handle' documented as 'Threads username'. The description adds no additional parameter semantics beyond what the schema provides (e.g., format examples, validation rules). The baseline score of 3 is appropriate since the schema does the heavy lifting.
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 verb ('Get') and resource ('posts from a Threads user'), making the purpose immediately understandable. It distinguishes from siblings like 'get_threads_profile' which retrieves profile information rather than posts. However, it doesn't specify scope (e.g., recent posts, all posts) which prevents a perfect score.
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 about when to use this tool versus alternatives. The description doesn't mention prerequisites, limitations, or comparisons to sibling tools like 'get_threads_profile' for profile data or 'get_instagram_posts' for similar functionality on another platform. This leaves the agent with minimal context for tool selection.
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 states the action but doesn't describe traits like whether this is a read-only operation, rate limits, authentication needs, or what the output format might be. This leaves significant gaps for an agent to understand how to invoke it correctly.
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, efficient sentence with no wasted words. It is appropriately sized and front-loaded, clearly stating the tool's purpose without unnecessary elaboration.
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 the lack of annotations and output schema, the description is incomplete. It doesn't address behavioral aspects like safety, performance, or return values, which are crucial for an agent to use this tool effectively in a social media context with potential complexities.
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?
The input schema has 100% description coverage, with the single parameter 'handle' documented as 'TikTok username'. The description adds no additional meaning beyond this, so it meets the baseline of 3 where the schema does the heavy lifting.
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 verb 'Get' and the resource 'TikTok videos from a user', making the purpose understandable. However, it doesn't distinguish this tool from its sibling 'get_tiktok_profile', which might retrieve user metadata instead of videos, leaving room for ambiguity.
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_tiktok_profile' or other social media tools. The description implies usage for TikTok videos but lacks context on prerequisites, limitations, or comparisons with siblings.
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 are provided, so the description carries full burden for behavioral disclosure. It states what the tool does but doesn't describe how it behaves: no information about authentication requirements, rate limits, error handling, response format, or whether it's a read-only operation. For a tool with zero annotation coverage, this is inadequate.
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 at just three words, front-loading the essential information with zero wasted words. It efficiently communicates the core purpose without unnecessary elaboration.
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 insufficiently complete. It doesn't explain what data is returned, authentication needs, rate limits, or error conditions. For a tool that presumably makes external API calls, this leaves critical operational context undocumented.
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 the single parameter 'handle' clearly documented as 'Twitter username' in the schema. The description adds no additional parameter information beyond what the schema provides, which is acceptable given the high schema coverage but doesn't enhance understanding.
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 verb ('Get') and resource ('Twitter/X profile data'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'get_twitter_tweets' or other social media profile tools, which would require more specificity for a perfect score.
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 alternatives. With sibling tools like 'get_twitter_tweets' and other social media profile tools available, there's no indication of when this is the appropriate choice or what distinguishes it from similar tools.
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 but offers minimal insight. It implies a read operation ('Get') but doesn't specify whether it's safe, if it requires authentication, what the return format is, or any constraints like rate limits or data recency. This leaves significant gaps for an agent to understand how the tool behaves.
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, clear sentence with no wasted words, making it highly concise and front-loaded. It directly communicates the core function without unnecessary elaboration, which is efficient for an agent's quick understanding.
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 no annotations and no output schema, the description is incomplete. It doesn't explain what 'tweets' are returned (e.g., count, format, or fields), any behavioral traits like pagination or errors, or how it integrates with sibling tools. Given the complexity of social media data retrieval, more context is needed for effective 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?
The input schema has 100% description coverage, with the 'handle' parameter documented as 'Twitter username'. The description adds no additional semantic context beyond this, such as format examples (e.g., '@username' or plain 'username') or usage notes. Given the high schema coverage, a baseline score of 3 is appropriate as the schema does the heavy lifting.
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 ('Get tweets') and target resource ('from a Twitter/X user'), making the purpose understandable. It distinguishes from sibling tools like 'get_twitter_profile' by focusing on tweets rather than profile data. However, it lacks specificity about what 'get' entails (e.g., recent tweets, all tweets, or a limited set).
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. It doesn't mention prerequisites (e.g., authentication), limitations (e.g., rate limits or data availability), or how it differs from similar tools like 'get_instagram_posts' or 'get_threads_posts' in terms of functionality or context.
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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