Artifex MCP
Server Quality Checklist
Latest release: v1.0.2
- Disambiguation5/5
Each tool has a clearly distinct purpose: generate_image creates images, while auth_status, auth_login, auth_logout handle different aspects of authentication (status, instructions, and logout), and quota_status checks rate limits. There is minimal potential for confusion due to clear descriptions.
Naming Consistency4/5Tool names generally follow a pattern: action tools like generate_image and auth_login/logout use verb_noun, while status tools use domain_status (auth_status, quota_status). The only minor inconsistency is that generate_image lacks a domain prefix unlike the auth/quota tools, but the convention is still readable and predictable.
Tool Count5/5With 5 tools, the server is well-scoped for image generation. It provides essential functionality: generation, authentication management, and quota checking, without unnecessary bloat.
Completeness4/5The core image generation workflow is covered, alongside authentication and quota monitoring. A notable gap is the lack of a tool to list available models/providers, which would help users understand the 'model' parameter for generate_image, but it is a minor omission.
Average 3.6/5 across 5 of 5 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- 0 of 1 community issues answered or closed in the last 6 months
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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, the description carries the full burden of disclosure. It says 'get instructions' but doesn't explicitly state that this operation is read-only, makes no state changes, or what the response format is. The name 'auth_login' could mislead an agent into expecting an active login action.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, no filler, front-loaded with the core action. Exceptionally concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with a single optional parameter and no output schema, the description is minimal. It lacks context about how instructions are returned (e.g., a URL, steps), how the provider parameter affects the instructions, or the relationship to other auth tools. Adequate but with gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers the lone parameter (provider) with options and default, so the baseline is 3. The tool description adds minimal semantic value beyond the schema, just indicating the provider is for image generation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool provides authentication instructions for an image generation provider, using a specific verb ('get') and resource. It distinguishes from siblings like auth_status (check status) and auth_logout (end session) by focusing on instructions, though it doesn't mention what form the instructions take.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 auth_status or auth_logout. The description doesn't mention prerequisites (e.g., need an account) or alternative scenarios, leaving the agent to infer usage.
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 fails to mention side effects like file creation or modification (implied by output_path), authentication requirements (despite auth sibling tools), or return values. The brief description provides minimal 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, immediately states the main purpose, and includes useful provider context without fluff. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 8 parameters, no output schema, and no annotations, the description is too sparse. It does not explain what the tool returns (e.g., saved file paths) or mention editing capability via input_image. For a mutation tool that likely creates files, this is a significant gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description adds a small hint about using the model parameter in provider:model format, but this is already covered in the schema's model parameter description. No additional semantic value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Generate images using AI' with a specific verb and resource, clearly distinguishing it from sibling auth/quota tools. It also mentions multiple providers and the model parameter format, reinforcing its function.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly implies usage for image generation, and the sibling tools are all auth/quota related, so there is no ambiguity about when to use this tool. However, it does not explicitly discuss alternatives or exclusions, which keeps it from a 5.
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. 'Check authentication status' implies a read-only, non-mutating operation, but it doesn't disclose what the status entails, potential error conditions, or whether it makes network calls. Minimal behavioral disclosure, though the operation type is clear.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
One sentence, direct, and front-loaded. No filler or redundant phrasing. The description is immediately understandable and appropriately sized for the tool's simplicity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple status-check tool with no output schema, the description is adequate but doesn't explain the return format or what 'status' conveys, which an agent might need to interpret results. Given the tool's simplicity and full schema coverage, it's minimally viable but leaves interpretive gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already fully documents the only parameter (provider) with description and default (100% coverage), so the description adds little parameter-level meaning beyond the domain context 'image generation provider'. Baseline 3 is appropriate when schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description explicitly states the action ('check') and resource ('authentication status for an image generation provider'), clearly distinguishing it from sibling tools like auth_login/auth_logout which perform auth changes. The verb+resource structure is specific and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit when-to-use guidance or alternatives are mentioned, but the context ('for an image generation provider') implies it is the status check companion to auth_login/auth_logout. The description doesn't state exclusions or conditions for use, so it's implied rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Since no annotations are provided, the description carries the burden of disclosing behavior. It explicitly states the destructive side effect of deleting stored credentials, which is the key behavioral trait. It could add more detail about session revocation or irreversibility, but the core effect is clearly disclosed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, focused sentence that starts with the primary action and includes the key object and context. No filler or redundant information, making it highly concise and effective.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one optional parameter and no output schema, the description provides sufficient context: it defines the action, the affected resource, and the domain (image generation provider). It could mention the default provider, but that is already in the schema. Overall, the description is complete for the tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides full coverage for the only parameter (provider) with options and default. The description does not add additional semantic detail beyond the schema, so a baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function with specific verbs ('log out', 'delete stored credentials') and identifies the resource ('an image generation provider'). It distinguishes itself from sibling tools like auth_login and auth_status by focusing on the logout/deletion action.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 auth_status or auth_login. The description does not mention exclusions, prerequisites, or typical scenarios, leaving the agent to infer usage from the tool name and basic action.
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, the description carries full burden for behavioral disclosure. It correctly implies a read-only operation ('Check' rather than mutate), but does not disclose authentication requirements, possible error conditions, or what the returned status data represents. Minimal but adequate for a simple status check.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no filler. Every word contributes meaning, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one optional parameter, no nested objects, no output schema), the description is nearly sufficient. However, it omits what the response will contain (e.g., numeric limits, reset times), which would help the agent interpret the result. It's adequate but not comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% because the sole parameter 'provider' is documented with allowed options and default. The description adds no extra meaning beyond the schema, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Check') and clearly identifies the resource ('rate limit and quota status') and scope ('for an image generation provider'). It distinguishes itself from sibling tools like generate_image (which generates) and auth tools (which handle authentication).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context—checking rate limits and quotas for a provider—but does not explicitly state when to use it versus alternatives or mention exclusions. It's clear enough for typical use (e.g., before generating an image), but lacks explicit 'when not to use' guidance.
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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