Server Quality Checklist

Tool Scores

• get_top_lorasB
  3.2/5.0
  Behavior3/5

  Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

  Annotations already cover key behavioral traits: read-only, non-destructive, idempotent, and open-world. The description adds some context by mentioning the API key requirement for NSFW content and listing example base models, which helps clarify scope. However, it doesn't disclose other behavioral aspects like rate limits, pagination, or error conditions, leaving room for improvement despite the 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 appropriately sized with three sentences that are front-loaded: the first states the core purpose, the second provides examples, and the third adds a key constraint. There's minimal redundancy, and each sentence adds value, though the second sentence could be more structured (e.g., using a list).

  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 (5 parameters, no enums) and rich annotations, the description is partially complete. It covers the purpose and some constraints but lacks details on parameter semantics and behavioral nuances. The presence of an output schema reduces the need to explain return values, but the description doesn't fully compensate for the low schema coverage, leaving gaps in understanding.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters2/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  With 0% schema description coverage for 5 parameters, the description must compensate but falls short. It only explains the 'nsfw' parameter (requiring API key) and implies 'base_model' usage through examples, leaving 'period,' 'sort,' and 'limit' undocumented. This partial coverage doesn't adequately address the schema's gaps, making parameter understanding incomplete.

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

  Purpose4/5

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

  The description clearly states the tool's purpose: 'Get top LoRA models for a specific base model.' It specifies the verb ('Get'), resource ('top LoRA models'), and scope ('for a specific base model'), making the intent unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'get_top_checkpoints' or 'get_top_images,' which likely serve similar ranking functions for different resource types.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines3/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description provides implied usage context by listing example base models (SDXL, Flux, Pony, Illustrious) and mentioning that 'nsfw=true' includes NSFW LoRAs with an API key requirement. However, it lacks explicit guidance on when to use this tool versus alternatives like 'search_models' or 'get_model,' and doesn't specify prerequisites or exclusions beyond the API key note.

  Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

• get_top_checkpointsB
  3.3/5.0
  Behavior3/5

  Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

  Annotations already provide readOnlyHint=true, destructiveHint=false, idempotentHint=true, and openWorldHint=true, covering safety and idempotency. The description adds context about what types of checkpoints it's best for (SDXL, Flux, etc.) and example base models, which helps set expectations. However, it doesn't disclose additional behavioral traits like rate limits, authentication needs, or pagination behavior beyond what annotations provide.

  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 appropriately sized with two sentences. The first sentence states the core purpose, and the second provides usage context with examples. There's no wasted text, and it's front-loaded with the main functionality. However, the second sentence could be slightly more structured for clarity.

  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 moderate complexity (4 parameters, no required ones), rich annotations (covering safety and idempotency), and the presence of an output schema (which handles return values), the description is reasonably complete. It covers purpose and usage context adequately. The main gap is parameter semantics, but overall it provides sufficient context for an agent to understand when and how to use this tool.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters2/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  Schema description coverage is 0%, so the schema provides no parameter documentation. The description mentions 'base_model' implicitly by listing examples (SD 1.5, SDXL 1.0, etc.), but doesn't explain the other three parameters (period, sort, limit) at all. It partially compensates for one parameter but leaves three undocumented, failing to adequately address the coverage gap.

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

  Purpose4/5

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

  The description clearly states the tool's purpose: 'Get top checkpoint models for a specific base model.' It specifies the verb ('Get') and resource ('top checkpoint models'), and distinguishes it from siblings by focusing on checkpoints rather than images, creators, or other model types. However, it doesn't explicitly differentiate from 'get_top_loras' or 'search_models' which might have overlapping functionality.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines3/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description provides implied usage guidance with 'Best for finding SDXL, Flux, Pony, Illustrious checkpoints' and lists example base models. This suggests when to use it (for those specific checkpoint types) but doesn't explicitly state when NOT to use it or name alternatives like 'get_top_loras' for LoRA models or 'search_models' for broader searches. The guidance is helpful but not comprehensive.

  Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

• get_creatorsB
  3.4/5.0
  Behavior3/5

  Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

  Annotations cover key behavioral traits (read-only, non-destructive, idempotent, open-world), so the description adds limited value. It hints at browsing/searching functionality but doesn't disclose additional context like rate limits, authentication needs, or pagination behavior beyond what annotations provide, resulting in adequate but not rich 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 a single, efficient sentence that front-loads the core purpose ('Browse and search model creators on Civitai') with zero wasted words. It's appropriately sized for the tool's complexity, making it easy to parse quickly.

  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 (3 optional parameters), rich annotations (covering safety and behavior), and the presence of an output schema (which handles return values), the description is reasonably complete. It states the purpose clearly but could improve by adding usage guidelines or parameter hints to fully compensate for the lack of schema descriptions.

  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, the schema provides no parameter details, but the description doesn't compensate by explaining parameters like 'query', 'limit', or 'page'. It mentions 'browse and search', which loosely relates to 'query', but lacks specifics on usage or semantics, aligning with the baseline for high schema coverage scenarios despite the low coverage here.

  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 ('Browse and search') and resource ('model creators on Civitai'), making the tool's purpose immediately understandable. However, it doesn't distinguish this tool from sibling tools like 'search_models' or 'get_tags' that might also involve browsing/searching different resources, missing explicit differentiation.

  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 'search_models' or 'get_tags'. It mentions 'browse and search' but doesn't specify contexts, prerequisites, or exclusions, leaving the agent with minimal usage direction.

  Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

• get_download_urlB
  3.4/5.0
  Behavior3/5

  Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

  Annotations already cover key behavioral traits (read-only, non-destructive, idempotent, open-world), so the description's burden is lower. It adds value by specifying that the URL is 'authenticated', which isn't captured in annotations, but doesn't elaborate on authentication requirements, rate limits, or response format. No contradiction with annotations is present.

  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. It's front-loaded with the core action and resource, making it highly efficient and easy to parse.

  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 simplicity (one parameter), rich annotations (covering safety and behavior), and the presence of an output schema (which handles return values), the description is reasonably complete. It could improve by clarifying the parameter or distinguishing from siblings, but it provides enough context for basic 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 0%, so the schema provides no parameter details. The description mentions 'model version' but doesn't explain what 'version_id' represents, its format, or valid ranges. It adds minimal semantics beyond the schema, but with only one parameter, the baseline is higher.

  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 ('authenticated download URL for a model version'), making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_download_info' or 'get_model_version', which might provide related but different information.

  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 such as 'get_download_info' or 'get_model_version'. It lacks context about prerequisites, timing, or exclusions, leaving the agent to infer usage based on tool names alone.

  Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

• get_model_versionA
  3.5/5.0
  Behavior3/5

  Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

  Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, and openWorldHint=true, covering safety and idempotency. The description adds value by listing return details ('download URLs, trigger words, base model, files, example images'), which helps anticipate output. However, it doesn't disclose additional behavioral traits like rate limits, auth needs, or error conditions beyond what annotations provide.

  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, followed by a concise list of return details. Both sentences earn their place by providing essential information without waste. It's appropriately sized for a simple lookup tool.

  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), rich annotations, and presence of an output schema, the description is mostly complete. It covers the purpose and return details, though it lacks usage guidelines. The output schema likely documents return values, so the description doesn't need to explain them in depth, but more context on when to use this tool would improve completeness.

  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%, with one parameter 'version_id' of type integer, but the description compensates by explaining its role: 'by version ID.' This adds semantic meaning beyond the schema, clarifying that 'version_id' identifies a specific model version. Since there's only one parameter, the description effectively covers it, earning a baseline 4.

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

  Purpose4/5

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

  The description clearly states the tool's purpose: 'Get details about a specific model version by version ID.' It specifies the verb ('Get details'), resource ('model version'), and key identifier ('version ID'). However, it doesn't explicitly differentiate from sibling tools like 'get_model_version_by_hash' or 'get_model_version_mini', which likely serve similar purposes with different identifiers or detail levels.

  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 such as 'get_model_version_by_hash' (which might use a hash instead of ID) or 'get_model_version_mini' (which might return less detail), nor does it specify prerequisites or exclusions. Usage is implied by the purpose but lacks explicit context.

  Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

• get_model_version_by_hashA
  3.5/5.0
  Behavior3/5

  Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

  Annotations already cover key behavioral traits (read-only, non-destructive, idempotent, open-world), so the description adds value by specifying the hash types supported (SHA256, AutoV2, CRC32, BLAKE3). However, it doesn't provide additional context like error handling, performance, or authentication needs beyond the 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 a single, efficient sentence with zero waste—every word contributes to clarifying the tool's purpose and parameter usage. It's appropriately sized and front-loaded with the core action.

  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 simple input schema (one parameter), rich annotations, and presence of an output schema, the description is reasonably complete. It covers the lookup mechanism and hash types, though it could benefit from mentioning when to use this over sibling tools or clarifying the expected output format.

  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?

  With 0% schema description coverage and only one parameter, the description compensates well by explaining that the 'hash' parameter accepts multiple file hash types (SHA256, AutoV2, CRC32, BLAKE3), adding meaningful semantics beyond the bare schema. This is crucial for correct tool invocation.

  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 ('Find') and resource ('model version') with a specific lookup mechanism ('by its file hash'), making the purpose unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'get_model_version' or 'get_model_version_mini', which likely have different lookup criteria.

  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 when this hash-based lookup is preferred over other methods (e.g., by ID or name) or reference sibling tools like 'get_model_version' for comparison, leaving usage context unclear.

  Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

• get_trail_statsA
  3.5/5.0
  Behavior3/5

  Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

  Annotations already provide comprehensive hints (read-only, non-destructive, idempotent, open-world), so the description's burden is reduced. It adds useful context about what the tool returns ('summary statistics') and parameter usage, but doesn't disclose additional behavioral traits like rate limits, authentication needs, or what specific statistics are included.

  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 every sentence earning its place. The first sentence states the core purpose, and the next two efficiently explain parameter usage without any wasted words.

  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 has comprehensive annotations and an output schema exists, the description provides adequate context for a read-only statistical tool. It explains what the tool does and parameter semantics well, though it could benefit from mentioning what types of statistics are included or linking to the output schema.

  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?

  With 0% schema description coverage, the description fully compensates by explaining both parameters: 'requester' filters by workflow/task ID and 'since' uses ISO 8601 timestamps to count entries after a specific time. This adds crucial semantic meaning beyond the bare 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 the verb ('Get') and resource ('summary statistics from the TRAIL content log'), making the purpose specific and understandable. However, it doesn't explicitly differentiate this tool from its sibling 'get_trail', which appears to be a related tool for accessing trail data rather than statistics.

  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_trail' or other sibling tools. It mentions parameters but doesn't explain the context or scenarios where this statistical summary would be preferred over raw trail data access.

  Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

• get_tagsA
  3.6/5.0
  Behavior3/5

  Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

  Annotations provide comprehensive hints (readOnly, non-destructive, idempotent, openWorld), so the description's burden is lower. It adds value by mentioning the search functionality and tag usage in filters, but doesn't disclose additional behavioral traits like rate limits, authentication needs, or pagination details beyond what annotations cover. No contradiction with annotations exists.

  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 two short sentences that are front-loaded and waste no words. Every sentence earns its place by stating the core purpose and a practical usage tip, making it efficient and well-structured.

  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 (read-only search with annotations), 3 parameters, and the presence of an output schema, the description is reasonably complete. It covers the main action and a use case, though it could benefit from more detail on parameter interactions or result format, but the output schema mitigates this gap.

  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 and 3 parameters (query, limit, page), the description adds no specific meaning about parameters beyond implying a 'query' for searching. However, the schema provides defaults and types, and the existence of an output schema reduces the need for param details in the description. This meets the baseline for adequate but not compensatory coverage.

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

  Purpose4/5

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

  The description clearly states the tool's purpose as 'Browse and search model tags' and mentions a secondary use case ('Use tags in search_models filter'), which provides specific verb+resource context. However, it doesn't explicitly differentiate from sibling tools like 'search_models' or 'get_enums', which might have overlapping functionality, preventing 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 Guidelines3/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description implies usage by mentioning 'Use tags in search_models filter', suggesting a context for when tags retrieved here might be applied. However, it lacks explicit guidance on when to use this tool versus alternatives (e.g., 'search_models' for direct model searches or 'get_enums' for other metadata), and no exclusions or prerequisites are stated.

  Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

• get_image_generation_dataA
  3.7/5.0
  Behavior4/5

  Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

  Annotations already provide read-only, non-destructive, idempotent, and open-world hints. The description adds valuable behavioral context beyond this: it specifies the tool filters to 'only returns images that have generation metadata' and explains the purpose of the 'exclude_used' parameter (skip already-used images). This enhances understanding of the tool's behavior without contradicting annotations.

  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 appropriately concise with four sentences. It front-loads the core purpose, adds focused details, and explains key parameters efficiently. There's minimal waste, though the example values for 'requester' could be slightly more integrated into the flow.

  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 complexity (5 parameters, 1 required), annotations cover safety aspects, and an output schema exists (so return values are documented elsewhere), the description is reasonably complete. It explains the tool's specialized focus and key parameters, though it could better differentiate from siblings and cover all parameters more thoroughly.

  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 0%, so the schema provides no parameter documentation. The description partially compensates by explaining 'exclude_used: true = skip already-used images' and 'requester: who is requesting (e.g. "pikabu", "telegram").' However, it doesn't cover 'model_id', 'sort', or 'limit', leaving three of five parameters without semantic explanation in the description.

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

  Purpose4/5

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

  The description clearly states the tool's purpose: 'Get full generation parameters from top images of a model.' It specifies the resource (top images of a model) and the action (extract generation parameters). However, it doesn't explicitly distinguish this from sibling tools like 'get_top_images' or 'get_model_images', which likely return different data about images.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines3/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description implies usage context by stating it's 'focused on extracting the best prompts, settings, and LoRA combinations' and 'only returns images that have generation metadata.' This suggests it should be used when detailed generation data is needed. However, it doesn't explicitly state when to use this tool versus alternatives like 'get_top_images' or provide clear exclusions.

  Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

• browse_imagesA
  3.9/5.0
  Behavior4/5

  Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

  Annotations already declare this as read-only, non-destructive, idempotent, and open-world. The description adds valuable behavioral context beyond annotations: it explains that 'Previews are cached locally for viewing via Read tool' and mentions the 'exclude_used' parameter to 'skip images/videos already in history (avoid duplicates).' These are practical implementation details not captured in annotations.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness3/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is appropriately sized for a tool with 21 parameters, but the structure could be improved. It starts with the core purpose, then lists parameters in bullet-point style without clear grouping. While all information is relevant, it could be more front-loaded with the most critical usage information before diving into parameter details.

  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 complexity (21 parameters, 0% schema coverage) and the presence of annotations and output schema, the description provides substantial context. It covers most parameters in detail and includes implementation notes about caching and requester usage. However, it doesn't explain the relationship between certain parameters (like model_id vs base_model) or provide guidance on parameter combinations.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters5/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  With 0% schema description coverage for 21 parameters, the description carries the full burden of explaining parameter semantics. It provides detailed explanations for 16 parameters (sort, nsfw, content_type, browsing_level, tag, base_model, tools, techniques, has_meta, made_on_site, originals_only, remixes_only, exclude_used, requester) including examples and usage notes, far exceeding the baseline expectation.

  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: 'Browse AI-generated images/videos on Civitai.' It specifies the resource (images/videos) and platform (Civitai), but doesn't explicitly differentiate from sibling tools like 'get_top_images' or 'get_model_images' which might have overlapping functionality.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines3/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description provides some usage context by listing filtering options and stating 'Always specify [requester] when fetching content for another MCP tool.' However, it doesn't explicitly state when to use this tool versus alternatives like 'get_top_images' or 'search_models', nor does it provide clear exclusions or prerequisites for usage.

  Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

• get_model_imagesA
  4.2/5.0
  Behavior4/5

  Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

  Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, and openWorldHint=true. The description adds valuable context about what information is returned (full generation params) and the purpose ('Learn how to use a model well'), which goes beyond the annotations. No contradiction with 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 efficiently structured with three sentences that each add value: purpose statement, return details, and parameter explanations. No wasted words, and key information is 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 the existence of an output schema (which handles return values), good annotations, and the description's coverage of parameter semantics, this is mostly complete. The main gap is lack of explicit usage guidelines versus sibling tools.

  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?

  With 0% schema description coverage, the description compensates well by explaining the semantics of 'exclude_used' and 'requester' parameters. It clarifies what 'exclude_used: true' means and provides an example for 'requester'. However, it doesn't explain 'model_id' or 'limit' parameters.

  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' and resource 'example images generated with a specific model', distinguishing it from sibling tools like 'browse_images' or 'get_top_images' by specifying it's model-specific example images with full generation parameters.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines3/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description implies usage context ('Learn how to use a model well') but doesn't explicitly state when to use this tool versus alternatives like 'get_top_images' or 'browse_images'. No exclusions or clear alternatives are provided.

  Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

• get_modelA
  4.3/5.0
  Behavior3/5

  Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

  Annotations already provide readOnlyHint=true, destructiveHint=false, idempotentHint=true, and openWorldHint=true, covering safety and idempotency. The description adds value by listing return fields (e.g., description, versions, files), which gives context on output structure, but does not disclose additional behavioral traits like rate limits or authentication needs beyond 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 front-loaded with the core purpose in the first sentence, followed by a concise list of return fields. Every sentence earns its place by adding value without redundancy, making it efficient and well-structured for quick understanding.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness5/5

  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), rich annotations covering safety and behavior, and the presence of an output schema (which handles return value documentation), the description is complete enough. It provides purpose, parameter context, and output overview without needing to duplicate structured data.

  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 input schema has 0% description coverage, but the description compensates by specifying that the parameter is 'model_id' and it's used to get info 'by ID'. This adds meaning beyond the schema's type definition, though it doesn't detail format constraints or examples. With only one parameter, the baseline is high, and the description provides adequate semantic context.

  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 detailed info') and resource ('about a specific model by ID'), making the purpose explicit. It distinguishes from siblings like 'search_models' (which returns multiple models) and 'get_model_version' (which focuses on a specific version rather than the full model).

  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 when detailed information about a single model is needed, as opposed to 'search_models' for multiple models. However, it does not explicitly state when NOT to use this tool or provide clear alternatives beyond the sibling list, such as distinguishing from 'get_model_version' for version-specific data.

  Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

• get_model_version_miniA
  4.4/5.0
  Behavior4/5

  Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

  The description adds valuable behavioral context beyond annotations by specifying that it's 'faster' than the sibling tool and suitable for 'download/compatibility checks', which helps the agent understand performance characteristics and typical use cases. Annotations cover safety (readOnlyHint, destructiveHint) and reliability (idempotentHint, openWorldHint), so the description appropriately supplements rather than contradicts them, though it doesn't detail rate limits or auth needs.

  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, consisting of two sentences that efficiently convey the tool's purpose, key features, performance comparison, and usage guidelines without any wasted words. Every sentence adds critical value, making it front-loaded and easy to parse.

  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), rich annotations (covering safety and reliability), and the presence of an output schema (which handles return values), the description is largely complete. It effectively explains the tool's role and differentiation. However, it could slightly improve by hinting at the output structure or error cases, though the output schema mitigates this need.

  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 does not provide any information about the 'version_id' parameter beyond what the input schema specifies (type: integer, required). With 0% schema description coverage, the description fails to compensate by explaining what 'version_id' represents or how to obtain it, leaving a gap in parameter understanding. However, the baseline is 3 since the schema covers the parameter's structure minimally.

  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 ('Quick check for a model version') and resources ('availability, size, hashes, generation support'), and explicitly distinguishes it from its sibling 'get_model_version' by noting it's 'Faster than get_model_version'. This provides clear differentiation and a comprehensive scope of what information is retrieved.

  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 explicitly states when to use this tool ('Use for download/compatibility checks') and when not to use it by comparing it to an alternative ('Faster than get_model_version'), providing clear guidance on its intended context versus other options. This directly addresses the need for distinguishing between similar tools.

  Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

• get_download_infoA
  4.5/5.0
  Behavior4/5

  Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

  The annotations already provide excellent behavioral information (read-only, non-destructive, idempotent, open-world). The description adds valuable context beyond annotations: it explains what happens when version_id is unspecified (uses latest), describes the ComfyUI path auto-mapping feature, and mentions authentication handling in generated commands. No contradiction with annotations exists.

  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 perfectly front-loaded with the core purpose in the first sentence. Each subsequent sentence adds essential information about default behavior, special parameter handling, and output format. There's zero wasted text - every sentence earns its place.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness5/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  Given the tool's moderate complexity, rich annotations covering safety and behavior, and the existence of an output schema (which means return values don't need explanation), the description is complete enough. It covers the tool's purpose, key parameter behaviors, and output characteristics while letting structured fields handle the rest.

  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?

  With 0% schema description coverage, the description carries full burden for parameter semantics. It explains the purpose of version_id (defaults to latest if unspecified) and comfyui_path (auto-maps to correct ComfyUI directory). However, it doesn't explain model_id at all, leaving one of the three parameters undocumented in the description.

  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 ('Get download URLs', 'Generates ready-to-paste download commands') and resources ('for a model'). It distinguishes from sibling tools like 'get_download_url' by specifying additional functionality (curl/PowerShell commands, ComfyUI path mapping, authentication handling).

  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 provides clear context about when to use this tool (to get download URLs with commands for a model) and includes some usage guidance ('If version_id not specified, uses latest version'). However, it doesn't explicitly state when NOT to use it or mention alternatives like 'get_download_url' from the sibling list, which appears to be a simpler version.

  Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

• get_top_imagesA
  4.5/5.0
  Behavior4/5

  Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

  The description adds valuable behavioral context beyond what annotations provide. While annotations declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, and openWorldHint=true, the description reveals that 'Previews cached locally for Read tool' and explains the purpose of 'exclude_used' to 'avoid duplicate posts.' This provides practical implementation details that help the agent understand caching behavior and duplicate avoidance.

  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 efficiently structured with bullet-like formatting that clearly presents each parameter and its semantics. While comprehensive, every sentence serves a purpose in explaining parameters or behavioral context. It could be slightly more front-loaded by moving the caching note earlier, but overall it's well-organized and avoids unnecessary verbiage.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness5/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  Given the tool's complexity (16 parameters, 0% schema coverage) and the presence of annotations and output schema, the description provides complete contextual information. It fully documents all parameters, explains key behavioral aspects like caching and duplicate avoidance, and provides usage context. The output schema existence means the description doesn't need to explain return values, making this description comprehensive for the agent's needs.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters5/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  With 0% schema description coverage for 16 parameters, the description carries the full burden of explaining parameter semantics. It successfully documents all 16 parameters by listing them with clear explanations of their purposes, acceptable values, and usage contexts (e.g., 'browsing_level: "PG", "PG-13", "R", "X", "XXX" (comma-separated)' and 'requester: who is requesting... Always specify for publishing workflows').

  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 top images/videos from Civitai — best for finding great prompts.' It specifies the exact resource (images/videos from Civitai) and distinguishes itself from sibling tools like 'browse_images' or 'search_models' by focusing on 'top' content with specific ranking criteria.

  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 provides clear context for when to use this tool ('best for finding great prompts') and mentions 'publishing workflows' for the requester parameter. However, it doesn't explicitly state when NOT to use it or name specific alternative tools from the sibling list, such as 'browse_images' or 'search_models', for different use cases.

  Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

• mark_trailA
  4.5/5.0
  Behavior4/5

  Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

  The description adds valuable context beyond annotations: it specifies the log's purpose ('content log') and example actions (e.g., fetched, failed), which annotations don't cover. Annotations indicate it's non-destructive, non-read-only, idempotent, and closed-world, but the description doesn't contradict these. It could improve by mentioning rate limits or auth needs, but it provides useful behavioral 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 front-loaded with the core purpose in the first sentence, followed by a bullet-like list of parameters with clear explanations. Every sentence earns its place by providing essential details without redundancy, making it efficient and well-structured for quick understanding.

  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 moderate complexity (6 parameters, 3 required) and the presence of an output schema (which handles return values), the description is nearly complete: it covers purpose, parameters, and usage context. It could slightly improve by mentioning the output schema's role or error handling, but it provides sufficient guidance for an agent to invoke the tool correctly.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters5/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  With 0% schema description coverage, the description fully compensates by explaining all 6 parameters: it defines each parameter's purpose (e.g., 'content_id: content ID in format...', 'action: what happened'), indicates optionality ('optional'), and provides examples (e.g., 'civitai:image:12345', 'prompthub-daily'). This adds significant meaning beyond the bare schema.

  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 ('Write an entry') and resource ('TRAIL content log'), distinguishing it from sibling tools like 'get_trail' (which reads) and 'get_trail_stats' (which aggregates). It provides a concrete example of the content_id format, making the purpose unambiguous and differentiated.

  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 for logging content-related events (e.g., fetched, selected, posted) in a workflow context, as suggested by 'requester: workflow/task ID'. However, it does not explicitly state when to use this tool versus alternatives like 'mark_as_used' or other logging methods, nor does it provide exclusions or prerequisites.

  Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

• search_modelsA
  4.5/5.0
  Behavior4/5

  Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

  Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, and openWorldHint=true, covering safety and idempotency. The description adds valuable behavioral context: it explains the dual backend implementation (Meilisearch vs REST API), pagination behavior via 'cursor', and authentication requirements for certain filters ('requires API key'). No contradictions with annotations.

  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 well-structured with clear sections: purpose, backend details, filter options, and tips. Most sentences add value (e.g., explaining backend differences, listing enums, providing usage tips). It could be slightly more concise by avoiding repetition (e.g., 'REST API only' appears multiple times).

  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 complexity (20 parameters, 0% schema coverage) and presence of annotations and output schema, the description is mostly complete. It covers purpose, usage, key parameters, and behavioral details. The output schema handles return values, so the description doesn't need to explain them. Minor gaps remain in parameter documentation.

  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?

  With 0% schema description coverage for 20 parameters, the description compensates well by explaining key parameters: it lists allowed values for 'types', 'base_model', 'sort', 'period', and 'allow_commercial_use', and clarifies usage of 'cursor', 'ids', 'favorites', and 'hidden'. However, it doesn't cover all 20 parameters (e.g., 'nsfw', 'limit', 'page'), leaving some gaps.

  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: 'Search for AI models on Civitai with flexible filters.' It specifies the resource (AI models on Civitai) and the action (search with filters), distinguishing it from siblings like 'get_model' (for known IDs) and 'get_top_checkpoints' (specific type without search).

  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 usage guidance: 'Use get_model if you know the ID' (alternative tool), 'text search works best via Meilisearch' (optimization tip), and 'Set favorites=true or hidden=true to filter your own models (requires API key, REST API)' (prerequisites). It also distinguishes between Meilisearch and REST API use cases.

  Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

• get_trailA
  4.6/5.0
  Behavior4/5

  Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

  The annotations already declare this as read-only, non-destructive, idempotent, and open-world. The description adds valuable behavioral context beyond annotations: it specifies the tool returns entries 'newest first' and explains pagination behavior with 'limit' and 'offset' parameters. It also clarifies the filtering capabilities for various log attributes. No contradiction with annotations exists.

  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 perfectly structured: a clear purpose statement followed by a bullet-like list of parameter explanations. Every sentence earns its place - the first sentence establishes purpose, and each parameter explanation adds essential filtering context. No wasted words or redundancy.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness5/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  Given this is a query tool with comprehensive annotations (read-only, non-destructive, etc.) and an output schema exists, the description provides complete context. It explains the tool's purpose, usage scenarios, behavioral details (sorting order, pagination), and full parameter semantics. The combination of description and structured data gives the agent everything needed to use this tool correctly.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters5/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  With 0% schema description coverage, the description carries the full burden of explaining parameters. It provides excellent semantic context for all 7 parameters: explaining what each filters by, giving examples (like 'civitai:image:' prefix for content_id), clarifying data types (string or list for action), and explaining special values (0 = all for limit). This fully compensates for the schema coverage gap.

  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: 'Query the TRAIL content log' with the specific verb 'query' and resource 'TRAIL content log'. It distinguishes from siblings by specifying it's for checking 'what content was fetched, selected, posted, or skipped' - none of the sibling tools appear to serve this logging/audit function.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines4/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description provides clear context for when to use the tool: 'Use to check what content was fetched, selected, posted, or skipped.' This gives the agent specific scenarios for usage. However, it doesn't explicitly state when NOT to use it or mention alternatives like 'get_trail_stats' (a sibling tool that might provide aggregated statistics instead of detailed logs).

  Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

• get_current_userA
  4.7/5.0
  Behavior4/5

  Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

  Annotations already indicate this is a safe, read-only, idempotent operation (readOnlyHint: true, destructiveHint: false, idempotentHint: true). The description adds valuable context beyond annotations: it specifies the authentication requirement ('requires CIVITAI_API_KEY') and hints at the return values, which is useful for understanding the tool's purpose. No contradictions with 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 front-loaded with the core purpose, followed by return details and usage guidance in just two sentences. Every sentence adds value: the first explains what the tool does and prerequisites, the second clarifies the output and primary use case. No wasted words.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness5/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  Given the tool's simplicity (0 parameters, annotations covering safety, and an output schema exists), the description is complete. It covers the purpose, authentication needs, return values, and usage context, providing all necessary information for an agent to select and invoke it correctly without over-explaining.

  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 input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately focuses on the tool's purpose and usage without redundant parameter details, earning a high score for adding semantic value where parameters are absent.

  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 ('Get info about'), the target resource ('currently authenticated user'), and distinguishes it from siblings by focusing on user authentication verification rather than browsing or retrieving content like images, models, or tags. It explicitly mentions the required API key, adding context.

  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: 'to verify API key is valid.' This directly addresses the primary use case and distinguishes it from sibling tools that retrieve data (e.g., browse_images, get_model) without authentication checks. No alternatives are named, but the context is clear.

  Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

• get_enumsA
  4.7/5.0
  Behavior4/5

  Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

  Annotations already indicate read-only, non-destructive, idempotent, and open-world behavior. The description adds value by specifying the scope ('currently supported') and the specific enums returned, which provides context beyond annotations. However, it doesn't detail response format or potential rate limits, keeping it from a perfect score.

  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, followed by a specific list of enums and a clear usage guideline. Every sentence earns its place by adding essential information without redundancy, making it efficient and well-structured.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness5/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  Given the tool's simplicity (0 parameters, rich annotations, and an output schema), the description is complete. It explains what the tool does, why to use it, and what it returns, covering all necessary context without needing to detail parameters or output structure, which are handled elsewhere.

  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?

  With 0 parameters and 100% schema description coverage, the baseline is high. The description adds no parameter information (as there are none), but it effectively compensates by explaining the output's purpose and content, which is valuable given the tool's role in metadata discovery.

  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 ('Get all valid enum values') and resource ('Civitai API filters'), with explicit enumeration of the five filter types (ModelType, BaseModel, etc.). It distinguishes from siblings by focusing on metadata discovery rather than data retrieval or manipulation, unlike tools like get_model or search_models.

  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 explicitly states when to use this tool: 'Use this to discover currently supported model types and base models.' This provides clear context for usage (discovery of valid values) and implies alternatives (e.g., use other tools like search_models for actual filtering once values are known).

  Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

• mark_as_usedA
  4.8/5.0
  Behavior4/5

  Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

  Annotations indicate this is a non-destructive, idempotent, non-read-only operation. The description adds valuable context beyond annotations: it clarifies the tool's purpose is to record usage events (not modify images themselves) and provides real-world examples of usage scenarios. No contradiction with annotations exists.

  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 efficiently structured: a clear purpose statement followed by bullet-like explanations of each parameter. Every sentence adds value without redundancy. It's front-loaded with the core usage guideline and purpose.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness5/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  Given the tool has an output schema (so return values are documented elsewhere), annotations covering key behavioral traits, and the description fully explaining all parameters and usage context, this description is complete. It provides everything needed for an agent to understand when and how to use this tool.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters5/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  With 0% schema description coverage, the description fully compensates by explaining all 5 parameters: 'image_ids' (Civitai image IDs that were used), 'action' (TRAIL action like 'posted'), 'requester' (workflow identifier), 'context' (optional note), and 'trace_id' (pipeline correlation). Each parameter's purpose and format is clearly described.

  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 ('Mark images/videos as used') and the resource ('images/videos'), with concrete examples of when this occurs ('after sending to Pikabu, Telegram, etc.'). It distinguishes this tool from sibling tools like 'browse_images' or 'get_model_images' by focusing on updating usage status rather than retrieval.

  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: 'Call this AFTER successfully publishing content to another platform.' It also distinguishes usage from sibling tools by specifying this is for marking usage, not for retrieval or searching operations like 'search_models' or 'get_trail'.

  Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.