Social Media Handle Checker

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation5/5
Each tool has a clearly distinct purpose targeting specific platforms (Instagram, Threads, TikTok, X, YouTube) or a comprehensive multi-platform check. There is no overlap or ambiguity between tools, as they are all uniquely scoped by platform.
Naming Consistency5/5
All tools follow a consistent verb_noun pattern with 'check_' prefix and platform-specific suffixes (e.g., check_instagram_handle, check_all_platforms). The naming is uniform, predictable, and easy to understand across the entire set.
Tool Count5/5
With 6 tools, the server is well-scoped for its purpose of checking social media handle availability. It includes individual platform checks and a comprehensive multi-platform tool, which is a reasonable and efficient number for this domain.
Completeness5/5
The tool set provides complete coverage for the domain of social media handle checking. It includes individual checks for all major platforms (YouTube, TikTok, Threads, X, Instagram) and a bulk check tool, leaving no gaps in functionality for this specific purpose.
Average 4/5 across 6 of 6 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
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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. It mentions checking 'availability' but lacks details on behavioral traits like rate limits, authentication needs, error handling, or what 'availability' means (e.g., real-time vs cached results). The description adds minimal context beyond the basic purpose.
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 front-loaded with the core purpose in the first sentence and adds a usage guideline in the second. Both sentences earn their place by providing essential information without redundancy or fluff.
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 no annotations and no output schema, the description adequately covers the purpose and usage but lacks details on behavioral aspects like response format, error cases, or platform-specific nuances. It's complete enough for a simple lookup tool but could benefit from more transparency.
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 parameter 'username' well-documented in the schema. The description adds no additional meaning beyond implying the parameter applies to all platforms, which is already clear from the tool's purpose. Baseline 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.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('check username availability') and resource ('across all supported platforms'), explicitly listing the platforms (YouTube, TikTok, Threads, X, Instagram). It distinguishes from sibling tools by emphasizing 'all at once' versus individual platform checks.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use this tool ('Perfect for comprehensive brand name research'), contrasting with sibling tools that check individual platforms. It implies an alternative approach (using individual tools) without naming them directly.
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. It discloses behavioral traits such as returning information about existing accounts or confirming availability, which is useful. However, it lacks details on error handling, rate limits, authentication needs, or response format, which are important for a tool interacting 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 appropriately sized and front-loaded, consisting of two concise sentences that directly state the tool's purpose and outcome. Every sentence earns its place by providing essential information without redundancy or unnecessary details.
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 moderate complexity (single parameter, no output schema, no annotations), the description is adequate but incomplete. It covers the basic purpose and behavior but lacks details on output structure, error cases, or API constraints, which would enhance completeness 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 input schema already documents the 'username' parameter thoroughly. The description adds no additional meaning beyond what the schema provides (e.g., no examples or edge cases), resulting in a baseline score of 3 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.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Check if an X (Twitter) username is available or already taken') and the resource ('username'), distinguishing it from sibling tools like check_instagram_handle or check_tiktok_handle by specifying the X (Twitter) platform. It avoids tautology by not merely restating the tool name.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context by specifying the X (Twitter) platform, which helps differentiate it from siblings like check_all_platforms or check_instagram_handle. However, it does not explicitly state when to use this tool versus alternatives (e.g., for cross-platform checks) or any exclusions, leaving some ambiguity.
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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It describes the tool's behavior ('returns information about the account if it exists, or confirms availability if it doesn't'), which covers the basic operation. However, it lacks details on potential limitations such as rate limits, authentication needs, or error handling, which would be helpful for a tool interacting with an external service like Instagram.
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 appropriately sized and front-loaded, consisting of two clear sentences that directly state the tool's purpose and return behavior without any unnecessary words. Every sentence earns its place by providing essential information efficiently.
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 the tool's low complexity (one parameter, no output schema, no annotations), the description is reasonably complete. It explains what the tool does and what it returns, which is sufficient for basic understanding. However, without an output schema, it could benefit from more detail on the return format (e.g., what 'information about the account' includes), but this is a minor gap given the simplicity.
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 'username' parameter well-documented in the schema. The description does not add any additional meaning or context beyond what the schema provides (e.g., it doesn't explain format constraints or examples), so it meets the baseline score of 3 for high schema coverage without extra value.
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 with a specific verb ('Check') and resource ('Instagram username'), specifying what it does ('check if... available or already taken') and what it returns ('information about the account if it exists, or confirms availability if it doesn't'). It distinguishes from siblings by focusing on Instagram specifically, unlike other platform-specific tools like check_tiktok_handle or check_x_handle.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use this tool by specifying it checks Instagram usernames, suggesting it should be used for Instagram-related queries. However, it does not explicitly state when not to use it or name alternatives (e.g., using check_all_platforms for broader checks or other siblings for different platforms), leaving some guidance implicit rather than explicit.
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?
With no annotations provided, the description carries the full burden. It discloses the tool's behavior by explaining the two possible return outcomes, but doesn't mention potential rate limits, authentication requirements, or error conditions. It adequately describes the core functionality but lacks operational details.
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 two concise sentences that efficiently convey the tool's purpose and behavior. Every word contributes value, with no redundant information or unnecessary elaboration.
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?
For a single-parameter lookup tool with no output schema, the description provides sufficient context about what information will be returned. However, it doesn't specify the format or structure of the returned information, which would be helpful given the absence of an output schema.
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, already documenting the single 'username' parameter with format details. The description doesn't add any parameter-specific information beyond what the schema provides, 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.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('check') and resource ('Threads username'), specifying what information is returned for both available and taken usernames. It distinguishes this tool from sibling tools by explicitly mentioning 'Threads' rather than other platforms like Instagram or TikTok.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context by stating what the tool returns (account info if exists, availability confirmation if not), which helps understand when to use it. However, it doesn't explicitly mention when to choose this tool over sibling alternatives like check_all_platforms or when not to use it.
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. It discloses the tool's behavior by stating it returns information about the channel if it exists or confirms availability if it doesn't, which covers the basic outcome. However, it lacks details on error handling, rate limits, authentication needs, or response format, leaving gaps in behavioral context.
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 concise and front-loaded, consisting of two clear sentences that directly explain the tool's purpose and outcome. Every sentence adds value without redundancy, making it efficient and easy to understand.
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 the tool's low complexity (1 parameter, no output schema, no annotations), the description is reasonably complete. It explains what the tool does and the possible outcomes. However, without an output schema, it could benefit from more detail on return values, such as the structure of channel information or availability confirmation.
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 'The YouTube handle to check (with or without @ prefix)'. The description does not add meaning beyond this, as it doesn't provide additional syntax, format details, or examples. 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.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('check if a YouTube channel handle is available or already taken') and the resource ('YouTube channel handle'), distinguishing it from sibling tools that check handles on other platforms like Instagram, Threads, TikTok, and X. It explicitly mentions what the tool does rather than just restating the name.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context by specifying it's for checking YouTube channel handles, which helps differentiate it from sibling tools that check handles on other platforms. However, it does not explicitly state when to use this tool versus alternatives or provide exclusions, such as whether it works for custom URLs or only specific handle formats.
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. It describes the core behavior (checking availability and returning account info or confirmation) but lacks details about rate limits, authentication requirements, error conditions, or response format. It's adequate but has clear gaps.
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 well-structured in two sentences: the first states the purpose, and the second explains the outcomes. Every word earns its place with zero waste.
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 the tool's low complexity (1 parameter, no annotations, no output schema), the description is reasonably complete for its purpose. It covers what the tool does and the possible outcomes, though it could benefit from more behavioral details like response format or error handling.
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 parameter 'username' fully documented in the schema. The description adds no additional parameter semantics beyond what the schema provides, so it meets the baseline of 3 for high schema coverage.
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 with specific verbs ('check', 'returns') and resource ('TikTok username'), distinguishing it from sibling tools that check other platforms. It explicitly mentions what happens in both cases (account exists vs. available).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implicitly provides excellent usage guidance by specifying 'Check if a TikTok username is available or already taken,' making it clear when to use this tool (for TikTok-specific checks) versus the sibling tools that check other platforms like Instagram, X, or YouTube.
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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