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

No annotations are provided, so the description carries the full burden. It only mentions the endpoint and request shape but does not disclose safety, side effects, or output behavior. For an image analysis tool, it doesn't clarify whether it's read-only or if there are any limitations.

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

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

The description is extremely concise at two sentences, front-loaded with the action and endpoint. Every word earns its place, with no fluff or repetition.

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

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

Given 16 parameters, no output schema, and minimal schema coverage, the description is inadequate. It does not explain the meaning of most parameters, expected return values, or any constraints. The reference to sdnext_vqa is insufficient for an agent to correctly invoke this tool.

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

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

Schema description coverage is only 6% (only 'image' is described). The description adds no parameter explanations and only references that the request shape is same as sdnext_vqa, which is indirect. With 16 parameters and zero enum guidance, the description fails to compensate for the lack of schema documentation.

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

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

The description clearly states the tool analyzes an image using the VLM 'analyze' task, names the specific endpoint (/sdapi/v1/analyze), and distinguishes it from siblings by noting the request shape matches sdnext_vqa. This is a specific verb+resource+task statement.

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

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

It mentions 'Same request shape as sdnext_vqa,' which hints at similarity and implies that sdnext_vqa might be used for VQA tasks while this is for analysis. However, there is no explicit statement of when to use this vs alternatives or when not to use it.

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

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

With no annotations, the description carries the burden. It is a read-only 'List' operation, which is transparent and unlikely to have side effects. The inclusion of the API endpoint adds useful context. No contradictions.

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

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

The description is a single sentence that immediately states the action, resource, scope, and even the API endpoint. There is no fluff or redundant information.

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

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

For a parameterless list tool with no output schema, the description is complete. It specifies what is listed, the local scope, and the endpoint, covering all necessary aspects without gaps.

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

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

The tool has zero parameters, so the baseline is 4. The description does not need to elaborate on parameter semantics, and it correctly implies no inputs.

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

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

The description clearly states the tool lists local autocomplete/tag list files, using a specific verb ('List') and resource ('autocomplete/tag list files') with scope ('local'). It also distinguishes from the sibling sdnext_autocomplete_remote by emphasizing 'local'.

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

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

The description implies usage for local files and contrasts with remote via 'local', but does not explicitly mention when to prefer this over sdnext_autocomplete_remote or other list tools. Still, the context is clear enough for an agent.

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

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

With no annotations provided, the description carries full burden. It tells the agent this returns file content via GET, which is adequate for a trivial read operation, but it doesn't disclose error behavior (missing file, permission issues) or whether the returned content is raw text vs. parsed structure. Adequate, not rich.

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

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

Two tightly packed elements — a plain-language statement and the canonical endpoint — with zero wasted words. Including the GET path is genuinely useful for API-originated tools.

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

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

For a single-parameter read operation, the description plus a 100%-covered schema covers most needs. However, with no output schema and no mention of return format, the agent cannot predict how to parse the result (list of strings? JSON?). Complete for the input side, lacking on the output side.

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

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

Schema coverage is 100% — the single 'name' parameter is documented with cross-reference to sdnext_autocomplete as its source. The description adds marginal value via the URL template showing {name} as a path segment, but this is baseline behavior for the dimension's rubric.

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

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

Clear verb+resource construction: 'get the content' of a 'local autocomplete/tag-list file'. The endpoint path disambiguates the operation, and the qualifier 'local' distinguishes it from siblings like sdnext_autocomplete_remote. The title and name align cleanly with the described behavior.

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

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

The word 'local' implies a contrast with remote alternatives (sdnext_autocomplete_remote), and the read-only nature is clear, but no explicit when/when-not scenarios or alternative tools are named. Guidance is only implied context, not stated exclusions.

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

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

Beyond the destructiveHint annotation, the description reinforces the destructive action with 'DESTRUCTIVE' and specifies the operation is on a 'local' file, offering additional context about scope. However, it does not detail potential side effects or confirmation requirements.

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

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

The description is concise and well-structured, including the HTTP method, endpoint, and a clear warning. It conveys the essential information without unnecessary verbosity.

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

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

For a simple delete operation with a single parameter, the description is complete. It explains the action, the target, and the destructive nature, which is sufficient for an agent to use the tool correctly without needing additional details.

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

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

The schema already provides a description for the 'name' parameter ('Autocomplete file name to delete'). The tool description does not add further meaning or constraints beyond this, so the baseline score for full schema coverage applies.

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

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

The description clearly states the tool deletes a local autocomplete/tag-list file, specifying the exact HTTP method and endpoint. It is distinct from siblings like autocomplete_download and autocomplete_content.

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

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

The description does not explicitly indicate when to use this tool versus alternatives. It provides no context about when deletion is appropriate or what distinguishes it from other autocomplete-related tools, aside from the obvious destructive nature.

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

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

With no annotations, the description carries the full burden of behavioral disclosure. It only says 'download' and gives the endpoint; it does not mention where the file is saved, whether it overwrites existing files, what response is returned, or any network/authorization considerations.

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

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

The description is a single concise sentence that includes the action, resource, source, and endpoint. There is no filler or redundant information.

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

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

The tool is simple with one well-documented parameter, but the absence of an output schema and annotations leaves gaps about the download result and side effects. The description is adequate but not fully complete for an agent deciding whether and how to invoke it.

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

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

Schema coverage is 100%, and the parameter description already explains that 'name' comes from sdnext_autocomplete_remote. The tool description adds 'remote source' context but provides little additional meaning beyond the schema.

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

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

The description clearly states the action ('Download'), the resource ('autocomplete/tag-list file'), and the source ('remote'), plus the exact endpoint. This distinguishes it from sibling tools like sdnext_autocomplete_remote (which lists remote files) and sdnext_autocomplete_delete (which deletes files).

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

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

The description clearly indicates this tool fetches a remote autocomplete file, and the parameter hint ('from sdnext_autocomplete_remote') implies it should be used after listing remote sources. However, it does not explicitly state when not to use it or name alternatives.

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

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

No annotations are provided, so the description must disclose behavioral traits on its own. It does add the GET HTTP method, implying a read-only operation, and mentions 'update status' as part of the result. However, it does not explain what 'update status' means, whether a network call to a remote server is required, or what failure modes might occur.

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

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

The description is a single, focused sentence that includes the HTTP endpoint and the key output characteristic. Every part of the sentence earns its place, and there is no padding or redundant restating of the title.

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

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

Given the low complexity (zero parameters, no output schema), the description is largely sufficient: it names the resource, the action, and the key output field ('update status'). The only gap is that it does not describe the shape of the returned list or define 'update status', but this is a minor omission for such a simple tool.

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

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

The tool has zero parameters, and the schema is empty with 100% coverage by virtue of having no properties. Per the rubric, zero-parameter tools receive a baseline of 4, and the description does not need to compensate for missing parameter documentation.

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

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

The description uses a specific verb ('List') and a specific resource ('remote autocomplete files') and adds the distinguishing detail 'with update status' plus the exact endpoint. This differentiates it from sibling tools like sdnext_autocomplete_download or sdnext_autocomplete_delete.

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

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

The description clearly implies when to use the tool (when you need a listing of remote autocomplete files), but it provides no explicit guidance about when not to use it or which sibling alternative might be better suited. For a simple zero-parameter listing tool, this is minimally viable but not genuinely helpful.

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

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

No annotations are provided, so the description carries the full burden. It mentions the output format and API endpoint but does not disclose behavioral traits such as whether the operation is read-only, performance implications, or if it requires authentication. The GET method is implied from the endpoint but not explicitly explained.

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

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

The description is extremely concise: one sentence that includes the purpose, format, and endpoint. It is front-loaded with the core action and efficiently packed without wasted words.

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

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

The tool is simple with one required parameter and no output schema. The description covers the basic purpose and format, but lacks details on how the 'folder##F##file' lines are structured, whether it includes subfolders, or how to handle empty results. However, for a simple listing tool, it is reasonably complete given the schema coverage.

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

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

Schema description coverage is 100% (the folder parameter is described as 'Folder path (from sdnext_browser_folders)' in the schema). The description adds the output format context but does not add new parameter semantics beyond the schema. Baseline 3 is appropriate.

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

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

The description states 'List files in an output folder' with a specific format and API endpoint, clearly indicating the action and resource. It distinguishes from sibling tools like sdnext_browser_folders (lists folders) and sdnext_delete_file (file deletion). However, it does not explicitly contrast with these siblings, so it misses the top score.

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

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

The description implies usage by listing files in a folder with a folder path parameter. It does not explicitly state when to use this tool versus alternatives, but the context is clear from the tool name and description. No exclusions or specific scenarios are mentioned.

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

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

No annotations are provided, but the description mentions it is a GET endpoint, which lightly indicates a read-only operation. It doesn't describe output details or error behavior, but with no params and a simple list, this is acceptable.

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

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

The description is a single, concise sentence that includes the endpoint path. It is front-loaded with the main purpose and has zero wasted words.

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

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

Given it's a simple zero-parameter list tool with no output schema, the description is sufficient for basic use. It doesn't explain what the labels look like or the exact return shape, but for a simple listing operation, that's not critical.

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

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

The tool has no parameters, and the schema coverage is 100% with zero properties. The description adds clarity on what the output contains (folders with labels), which is useful beyond the empty schema.

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

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

The description states 'List output/gallery folders with labels' — a specific verb (list) and resource (output/gallery folders) with scope. It distinguishes from sibling tools like sdnext_browser_files or sdnext_storage, which handle files or storage stats.

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

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

It implies use for retrieving folder listings but doesn't explicitly state when to use vs alternatives (e.g., browser_files for files). Since there is no sibling tool for folders, the context is somewhat clear, but no explicit when/when-not is provided.

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

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

The description does not disclose the output format (e.g., binary, URL), side effects, or the role of the 'exif' boolean parameter. Without annotations, this lack of detail leaves the behavior opaque.

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

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

The description is extremely concise and to the point, with no unnecessary words. It focuses on the core action and endpoint, making it easy to parse.

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

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

Given the lack of annotations and output schema, the description fails to cover important contextual aspects like return type, error handling, or the relationship with the file system. It is too sparse for a tool with multiple parameters and potential variations.

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

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

The description only mentions the 'file' parameter implicitly through the endpoint, and completely omits the 'exif' parameter. The schema provides no additional meaning, so the description adds minimal value beyond the raw schema.

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

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

The description clearly states the tool's function: retrieving a thumbnail for an output file. It identifies the endpoint and the primary file parameter, making the purpose unambiguous.

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

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

No guidance is provided on when to use this tool versus alternatives like the file browser or image retrieval endpoints. The description does not specify the context or edge cases where this tool is appropriate.

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

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

No annotations are provided, so the description must carry the burden. It discloses that it can make any method (GET, POST, PUT) and accepts arbitrary paths, which is helpful, but it does not clarify potential side effects (e.g., destructive actions, rate limits, authentication requirements) or what happens on errors. This is average given the tool's generic nature and absence of annotations.

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

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

The description is concise (two sentences) and front-loaded with the core purpose. It includes essential examples and usage guidance without unnecessary fluff. Slight deduction because the path format explanation could be integrated more seamlessly, but overall it's efficient.

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

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

Given the tool's generic nature, the description covers key aspects: path handling, method flexibility, and usage context. It lacks details on response handling (e.g., 'returns raw JSON') and error cases, but since it's a passthrough, that might be expected. The description is sufficient for an agent to select and call the tool correctly, with the schema handling parameter specifics.

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

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

Schema description coverage is 100%, with each parameter (path, body, query, method) having descriptions in the schema. The description adds minimal extra parameter info, mostly clarifying path formats (absolute vs relative) and the fallback behavior, which is a small addition. Baseline 3 is appropriate since the schema already documents all parameters.

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

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

The description clearly states the tool's purpose: 'Call any SD.Next REST endpoint directly', specifying the resource (SD.Next REST endpoints) and the verb (call). It distinguishes itself from sibling tools by explicitly mentioning 'v1 or v2, any method' and providing examples of valid paths, which sets it apart from dedicated sdnext_* tools.

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

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

The description provides explicit usage guidance: 'Use only when no dedicated tool fits; prefer dedicated sdnext_* tools.' This clearly indicates when to use the tool (generic endpoint access) and when not to (when a dedicated tool exists), and even names the alternative category (sdnext_* tools).

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

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

No annotations are provided, so the description carries the burden of behavioral disclosure. It does add useful context about mode variants and the analyze breakdown, but it does not disclose side effects, response format, or whether the operation is purely read-only.

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

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

The description is two well-structured sentences, front-loaded with the core purpose and endpoint, followed by key parameter behavior. Every sentence earns its place without redundant filler.

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

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

With 12 parameters, 50% schema coverage, and no output schema, the description is too thin to be considered complete. It covers the core purpose, modes, and analyze flag, but omits return-value expectations and the numerous tuning parameters, leaving the agent with significant ambiguity for a non-trivial tool.

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

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

Schema coverage is 50%, and the description adds some meaning to `mode` and `analyze` by listing mode values and the specific breakdown categories. However, many parameters like `num_beams`, `max_length`, `flavor_count`, and `clip_model` are left unexplained, so the description only partially compensates for the schema gap.

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

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

The description clearly states the tool generates a text caption/prompt from an image using OpenCLIP+BLIP and identifies the endpoint. It is specific and unambiguous, but it does not explicitly distinguish this tool from nearby siblings like sdnext_tagger, sdnext_vqa, or sdnext_caption_dispatch.

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

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

The description offers mode and analyze guidance, but no guidance on when to choose this tool over alternatives such as tagger, vqa, or analyze. There are no exclusions, prerequisites, or sibling comparisons.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only mentions that the response is 'unified' and depends on the backend, but says nothing about safety, side effects, prerequisites, or error conditions. This leaves significant ambiguity for an agent deciding whether to call this tool.

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

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

The description is extremely concise, consisting of two short sentences that convey the dispatch functionality, the list of backends, and the nature of the response. Every word adds value, and it is easy to parse quickly.

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

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

For a tool with 30 parameters, no output schema, and no annotations, the description is severely under-specified. It explains the basic dispatch concept but fails to detail parameter usage, backend-specific behavior, or operational details, making it incomplete for an agent to use correctly in most scenarios.

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

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

Schema coverage is only 10% (3 of 30 parameters documented), and the description does not compensate. It merely restates the backend enum values already present in the schema and notes the response depends on the backend, without explaining any of the other 27 parameters that remain undocumented.

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

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

The description clearly states it is a 'unified caption dispatch' and lists the four backends ('openclip', 'tagger', 'vlm', 'analyze') and response types, making the tool's purpose immediately apparent. However, it does not explicitly contrast itself with sibling tools like sdnext_caption or sdnext_tagger, so it does not earn a 5 for sibling differentiation.

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

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

The phrase 'pick backend' implies when to use this tool (when you want to select a specific captioning backend), but there is no explicit guidance on when to use this dispatcher versus the individual sibling captioning tools, nor any when-not-to-use conditions or alternative recommendations.

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

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

No annotations are provided, so the description carries the full burden. It states the HTTP endpoint (POST) which implies a mutation, but doesn't disclose whether the ban is permanent, whether it affects existing downloads, whether it requires authentication, or what happens if the name is already banned. The description is minimal and doesn't add behavioral context beyond the action itself.

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

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

The description is a single sentence, front-loaded with the action. It includes the endpoint in parentheses, which is useful for technical context. No wasted words, though it could be slightly more informative without becoming verbose.

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

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

For a simple one-parameter mutation tool, the description is minimal but functional. However, with no annotations and no output schema, it doesn't explain the effect of the ban (e.g., does it prevent downloads? does it apply to future searches?), nor does it mention any prerequisites or side effects. Given the tool's simplicity, a bit more context would be expected.

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

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

The schema has 100% coverage for the single parameter 'name' with description 'Model name to ban.' The description repeats this exactly, adding no additional meaning. Baseline 3 is appropriate since the schema already documents the parameter fully.

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

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

The description clearly states the action ('Ban a CivitAI model name') and identifies the resource (CivitAI model). It distinguishes from siblings like sdnext_civitai_remove_banned (which un-bans) and sdnext_civitai_banned (which lists banned models), though it doesn't explicitly name them.

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

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

No guidance on when to use this tool versus alternatives. It doesn't mention that this is for banning a model name (as opposed to a specific model ID or version), nor does it reference the related list/remove banned tools. The context is implied by the name and sibling tools but not stated.

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

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

With no annotations, the description carries full responsibility for behavioral disclosure. It only says 'Bookmark a CivitAI model name' and lists the endpoint, but does not indicate side effects, idempotency, duplicate handling, authentication needs, or return values. For a state-changing POST operation, this is insufficient.

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

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

The description is a single clear sentence that front-loads the action and includes the endpoint in parentheses. There is no redundant content, filler, or repetition; every part contributes to identifying the tool's purpose.

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

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

For a one-parameter tool with no output schema, the description covers the basic action and endpoint, but it omits behavioral context such as what happens on success, whether duplicate bookmarks are rejected, or if there are side effects. The missing return-value and mutation details make it adequate but not fully complete.

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

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

Schema description coverage is 100%, so the parameter 'name' is already documented as 'Model name to bookmark'. The description adds only the 'CivitAI' context, which is marginal. It does not provide additional format, examples, or edge-case guidance beyond the schema, so the baseline 3 is appropriate.

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

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

The description states a precise action and resource: 'Bookmark a CivitAI model name'. It also includes the exact endpoint (POST /sdapi/v2/civitai/bookmarks), which unambiguously differentiates it from sibling tools like sdnext_civitai_remove_bookmark and sdnext_civitai_bookmarks.

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

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

No explicit when-to-use or alternative guidance is provided. The tool name and sibling names imply it is for adding bookmarks, but the description does not state that this is for creating a bookmark versus removing or listing them, nor does it mention any prerequisites or conditions.

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

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

With no annotations provided, the description carries the burden of behavioral disclosure. It states the HTTP method (GET) and the exact endpoint, which conveys a safe, read-only operation. However, it does not disclose return format, possible emptiness, or whether any authentication/configuration is required, leaving some ambiguity.

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

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

The description is a single sentence that is immediately understandable and contains no filler. The title and description align, and the endpoint is included for precision.

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

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

This is a trivial zero-input list tool, and the description is sufficient to convey its purpose and scope. The lack of an output schema is mitigated because the tool's return value is essentially 'banned model names'. It is minimally complete, though slightly more context about the response format would strengthen it.

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

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

The tool has zero parameters, and the schema has 100% coverage, so no parameter documentation is needed. The description adds value by specifying the endpoint and the semantics of what is being listed.

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

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

The description uses a specific verb ('List') and clearly identifies the resource ('banned CivitAI model names'), with an explicit API endpoint. This distinguishes it from related CivitAI mutation tools like sdnext_civitai_add_banned or remove_banned.

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

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

The intended use is implied: call this tool to get the list of banned CivitAI model names. However, it does not explicitly state when to prefer this over other listing tools or mention any exclusions or alternatives, though for a zero-parameter read operation the implied usage is reasonably clear.

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

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

No annotations are provided, so the description carries the transparency burden. The GET method and 'list' verb imply a read-only operation, but the description does not disclose whether authentication is required, how results are ordered or paginated, or whether the data comes from a local cache or the CivitAI API. It is not misleading, but it offers only 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.

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

The description is a single, front-loaded sentence that conveys the action, resource, and endpoint with no filler or redundant phrasing. Every word earns its place.

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

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

For a parameterless list operation, the description is largely complete: it states the verb and noun clearly and provides the endpoint. Some additional detail about output shape or authentication would be helpful, especially since no output schema exists, but the low complexity keeps this from being a major gap.

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

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

The tool has zero parameters, so the baseline is 4. The description adds no parameter-specific details, but none are needed since the input schema is empty and there is nothing to explain.

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

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

The description states a specific action ('List') and resource ('bookmarked CivitAI models'), and includes the exact API endpoint. This clearly distinguishes it from sibling tools like sdnext_civitai_add_bookmark, sdnext_civitai_remove_bookmark, and sdnext_civitai_search.

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

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

The intended use is implied by the tool name and description: use it when you want to see bookmarked CivitAI models. However, it does not explicitly explain when to use this tool versus related tools like history or banned lists, nor does it mention any exclusions or prerequisites.

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

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

With no annotations, the description carries the full burden. It states the action (checking presence) but does not disclose potential behaviors such as read-only nature, response format, or error handling. However, the action is straightforward and not misleading, so a neutral score is appropriate.

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

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

The description is a single, front-loaded sentence that efficiently conveys the purpose and provides the endpoint. Every word earns its place, with no redundancy.

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

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

The tool is simple with one parameter and no output schema. The description implicitly indicates the result (which hashes are present) and provides the endpoint, making it sufficiently complete for such a straightforward operation.

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

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

The schema covers the only parameter (hashes) with a clear description. The tool description adds no extra meaning beyond what the schema provides, giving a baseline score of 3.

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

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

The description clearly states the tool's purpose: checking which given file hashes are already present locally. It includes the endpoint for reference, and it is distinct from sibling tools like sdnext_civitai_version_by_hash, which fetches version info rather than checking local presence.

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

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

No guidance is provided on when to use this tool versus alternatives, such as sdnext_civitai_version_by_hash or other Civitai tools. It does not mention any prerequisites, exclusions, or context that would help the agent decide to call this tool.

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

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

No annotations are provided, so the description carries the full burden. It discloses the underlying HTTP method (POST) and the semantic operation (DELETE), which indicates the destructive nature. However, it does not detail side effects like irreversibility or impact on other data, but for a simple clear action this is sufficient.

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

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

The description is a single sentence that is concise, front-loaded, and includes all necessary information: the action and the endpoint. No wasted words.

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

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

Given the tool has no parameters and no output schema, the description fully explains the tool's purpose and mechanism. It is complete for a simple destructive operation, and no further details are needed.

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

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

There are zero parameters, and the schema coverage is 100% (empty schema). As per the baseline for 0 params, the score is 4. The description adds no parameter info because none exist, which is appropriate.

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

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

The description clearly states the action ('Clear CivitAI search history') with a specific verb and resource, and also specifies the HTTP endpoint. It distinguishes from siblings like sdnext_civitai_history which likely retrieves history, making the purpose unambiguous.

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

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

The description implies the tool is used to clear search history but does not explicitly mention when to use it versus alternatives or provide any when-not guidance. Since there are no direct alternatives for clearing history, this is acceptable but not thorough.

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

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

With no annotations, the description carries the full burden for behavioral disclosure. It only reveals that this is a GET request (read-only), but provides no details on pagination behavior, search semantics, return format, or any side effects. The endpoint hint is minimal and doesn't add meaningful transparency.

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

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

The description is a single, compact sentence that includes the endpoint. It is front-loaded and contains no fluff. However, it is so brief that it sacrifices useful elaboration, but for what it says, it is concise.

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

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

Given the lack of annotations, output schema, and parameter descriptions, the description is too thin. An agent would not know what a creator is, how search matches, whether results are paginated in a certain way, or what the response contains. More context is needed for reliable invocation.

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

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

Schema description coverage is 0%, so the description must compensate. However, it only says 'Search' and does not explain the 'query', 'page', or 'limit' parameters. While parameter names are somewhat intuitive, the description adds no explicit meaning, leaving ambiguity about how query filtering works or defaults.

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

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

The description uses the specific verb 'Search' with the resource 'CivitAI creators', clearly distinguishing it from sibling tools that search models, tags, or images. The explicit endpoint (GET /sdapi/v2/civitai/creators) further reinforces the action and scope.

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

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

There is no guidance on when to use this tool versus alternatives like sdnext_civitai_search or sdnext_civitai_model. The description simply states the function without any context, prerequisites, or exclusions.

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

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

With no annotations, the description carries the full burden. It reveals the side effect (download to models dir) and asynchrony via 'Queue', which is valuable. However, it omits details about authentication/token fallback, potential rate limits, or whether queued downloads can be monitored or cancelled—important behavioral traits for a network-triggering tool.

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

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

Two sentences, front-loaded with the action, includes the endpoint, and contains a practical tip about path resolution. No filler or redundant restatement of the title.

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

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

For a 13-parameter mutation tool with no annotations and no output schema, the description is too sparse. It does not mention how to check download status or cancel (despite sibling tools), auth prerequisites for protected models, or behavior on duplicate/conflicting files. The agent would be left guessing on many operational aspects.

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

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

Schema description coverage is only 31%, so the description must compensate. It adds meaning for url and model_id/version_id but provides no guidance for 9 other parameters like nsfw, token, filename, expected_hash, or version_name. The majority of the 13 parameters remain semantically unexplained.

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

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

The description opens with a specific verb and resource: 'Queue a model file download to the models dir'. It names the POST endpoint, clarifies that url is required, and indicates how model_id/version_id relate to search results. This clearly differentiates it from siblings like sdnext_civitai_legacy or sdnext_civitai_download_status.

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

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

It gives clear context that downloads should be based on identifiers from search results and that url is mandatory. It does not explicitly list alternatives or when-not-to-use, but the instruction 'use model_id/version_id from search results to resolve paths' strongly implies the prior step (search) and helps the agent decide when this tool fits.

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

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

With no annotations provided, the description carries the full burden, and it does convey the core behavior (canceling a download) and the endpoint, which implies a state change (cancellation). However, it does not mention potential side effects, error conditions (e.g., what if the download is not queued?), or success/failure responses. It adds some value beyond the name by including the endpoint and 'queued' qualifier, but could be more explicit.

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

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

The description is a single, information-dense sentence that front-loads the action and includes the endpoint for developer verification. No wasted words; every part contributes to understanding.

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

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

For a simple cancel operation with one parameter and no output schema, the description is largely complete. It clearly communicates the action and the endpoint, and the 'queued' qualifier provides essential context. Missing are any caveats about idempotency or error behaviors, but given the low complexity, this is a minor gap.

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

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

The schema documentation (100% coverage) already explains that download_id is from sdnext_civitai_download, and the tool description does not add extra meaning to this parameter beyond that. Since schema coverage is high, the baseline of 3 is appropriate; the description does not need to repeat parameter details.

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

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

The description clearly states the action ('Cancel a queued CivitAI download') with a specific verb and resource, and includes the full REST endpoint. This distinguishes it from sibling download-related tools by explicitly indicating the 'cancel' operation. The mention of 'queued' adds important scope nuance.

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

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

The description implies the tool is used to cancel downloads but provides no explicit guidance on when to use it versus alternatives, nor any prerequisites or exclusions (e.g., only works on queued downloads, not already completed ones). While the 'queued' qualifier hints at context, it does not explicitly tell the agent when to invoke this tool or what happens if invoked inappropriately.

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

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

No annotations are provided, so the description bears full responsibility for disclosing behavior. It states 'list' which indicates a read-only operation, and the HTTP method GET further reinforces this. No side effects are mentioned, but none are implied or expected beyond a status query.

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

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

The description is a single, concise sentence that includes the HTTP method and endpoint. It contains no redundancy, fluff, or irrelevant details, making it highly efficient and well-structured.

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

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

For a simple status-listing tool with no parameters and no output schema, the description is adequately complete. It names the action and resource, though it does not specify the structure of the returned data. Given the simplicity, this is acceptable and not a significant gap.

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

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

The tool has zero parameters, so the schema provides complete coverage. The description does not need to elaborate on parameters, and the baseline score of 4 applies. The description adds no extra parameter information because none exists.

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

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

The description clearly states the tool lists queued/in-progress CivitAI downloads, which is a distinct function from sibling tools like download and download_cancel. The verb 'list' and the resource 'download/status' are unambiguous, making the purpose immediately apparent.

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

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

The description implies usage for checking download status but does not explicitly contrast with alternatives like download or download_cancel. However, the endpoint and verb make the intended scenario clear (monitoring ongoing downloads), so it is well-guided without being overly verbose.

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

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

No annotations are provided, and the description does not disclose any side effects or explicitly confirm read-only behavior. Given it is a GET request, it is likely safe, but the description leaves this implicit rather than stated.

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

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

The description is a single, concise sentence that directly communicates the tool's purpose without unnecessary detail.

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

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

The tool lacks an output schema, so no return format is described. The description does not mention any limitations, pagination, or relationship to other history-related tools, but for a simple list it may be sufficient. Still, more context about the returned history entries would improve completeness.

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

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

The parameter 'search_type' has a vague description: 'Filter: query, tag, filter.' This is confusing and does not clarify the allowed values or how the filter works. It adds some meaning but not enough for a user to know how to use it effectively.

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

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

The description clearly states the tool lists CivitAI search history, with a specific resource and action. It is unambiguous and distinguishes it from other tools that might perform different operations.

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

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

The description implies usage for retrieving history but does not explicitly state when to use this tool versus alternatives. It could benefit from noting that it is read-only and separate from other CivitAI operations like search or download.

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

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

The description does not disclose any behavioral aspects such as read-only nature, permissions, or side effects; the GET URL is implied but not stated as a behavioral guarantee.

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

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

The description is a single sentence, concise and to the point.

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

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

The tool is simple but lacks parameter explanations and usage context, making it incomplete for effective use.

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

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

The description does not explain the parameters limit, model_id, or model_version_id, leaving their semantics unknown.

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

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

The description clearly states the tool lists images for a CivitAI model or version, distinguishing it from sibling tools like search or model details.

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

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

No guidance is provided on when to use this tool versus alternatives such as sdnext_civitai_search or sdnext_civitai_model.

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

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

The description discloses it is a legacy endpoint and indicates a GET request, implying read-only behavior. However, it lacks explicit statements about side effects or permissions, though for a search these are likely minimal.

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

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

The description is two concise sentences, directly stating purpose and alternative, with no unnecessary fluff.

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

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

The description is minimal, lacking explanation of parameters, output, or the exact differences from the v2 endpoint. It does not sufficiently cover the tool's functionality given its complexity.

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

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

The description provides no additional meaning for any of the 10 parameters. The schema itself has no descriptions, so the description fails to compensate for the low schema coverage.

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

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

The description clearly states it is a legacy CivitAI search endpoint and differentiates it from the v2 alternative, making its purpose unambiguous.

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

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

It explicitly instructs to use sdnext_civitai_search for the v2 API, clearly indicating when to avoid this tool and pointing to the preferred alternative.

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

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

No annotations are provided, so the description carries full responsibility. It only notes the token requirement and that it returns the authenticated user, but does not disclose response format, error behavior, or whether it makes network calls. Given the zero-parameter natureainer, some baseline behavior could be assumed, but more transparency is expected.

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

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

Two sentences, both informative and direct. The endpoint reference adds technical precision without bloat. Slightly more could be added about return data, but it is acceptably concise.

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

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

For a zero-parameter read-only tool, the description is mostly sufficient. However, it does not describe what data is returned (user profile fields) or any error conditions (e.g., token missing/invalid). The sibling context shows many civitai tools, but this one stands alone for user info. Overall, it meets the minimum but could be enhanced.

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

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

The tool has no parametersroughly the schema is fully documented (100% coverage), so no param explanation is needed. The description appropriately notes the token requirement as a semantic prerequisite, which adds value beyond the schema.

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

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

The description clearly states the tool fetches the authenticated CivitAI user via a specific endpoint. While it doesn't explicitly differentiate from sibling tools, 'me' is a distinct concept among the civitai_* siblings, making the purpose reasonably clear.

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

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

No explicit guidance on when to use this versus other CivitAI tools (e.g., civitai_search, civitai_download). The description mentions a token requirement, which is a prerequisite, but does not clarify scenarios where this tool is preferred or when to avoid it.

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

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

No annotations are provided, so the description carries full responsibility for explaining behavior. It mentions 'scan' which implies a read-only operation, but it does not explicitly state that it does not modify or download anything. It also does not describe any side effects, required permissions, or what happens if metadata is missing. Given the tool's low complexity, a brief note on non-destructiveness would have been sufficient.

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

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

The description is a single sentence, front-loaded with the action and resource, and includes the API endpoint for reference. It is concise with no filler or redundancy.

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

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

Given the tool's simplicity (no parameters, no output schema), the description is adequate for basic understanding. However, it could be more complete by explicitly noting that the operation is read-only and describing what the output is (e.g., a list of detected metadata). Since there is no output schema, the description could have filled that gap. But for a simple scan tool, it is acceptable.

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

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

The tool has zero parameters, and the schema is empty. The description correctly indicates that the tool operates on local files without requiring additional input. This is effectively a baseline for a no-parameter tool, and the description provides clarity on what it does without any parameter ambiguity.

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

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

The description clearly states the action (scan), the object (local model files), and the goal (match CivitAI metadata). It also references the underlying API endpoint, which adds specificity. Although it doesn't explicitly differentiate from siblings, the verb 'scan' and the reference to 'metadata' make it distinct from related tools like 'sdnext_civitai_metadata_update' (which implies a write operation) and 'sdnext_civitai_check_local' (likely a different check).

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

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

The description implies the tool is used for scanning local model files to match CivitAI metadata, but does not explicitly state when to use it versus alternatives like 'sdnext_civitai_check_local' or 'sdnext_civitai_metadata_update'. There are no exclusions or alternative tool references, leaving some ambiguity for an agent deciding between similar tools.

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

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

Annotations are absent, so the description must fully disclose behavioral traits. It implies a mutation via 'POST' but does not explain side effects (e.g., file modifications, potential failures) or any required preconditions. This is minimal and leaves ambiguity about what 'sidecar metadata' entails.

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

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

The description is a single, concise sentence that includes the endpoint. It is front-loaded with the purpose and contains no fluff. Excellent brevity.

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

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

Given no annotations, no output schema, and zero parameters, the description is the sole guide. It does not explain what 'sidecar metadata' is, what local models it applies to, or any conditions for success. While the tool is simple, the lack of explanatory context makes it minimally adequate but not complete.

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

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

There are no parameters, so the schema already fully documents the input (empty object). The description adds minimal value beyond the schema, but with zero parameters, the baseline of 4 is appropriate. It does not need to explain parameters.

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

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

The description clearly states the action: 'Update sidecar metadata for local models' with a specific verb and resource. It distinguishes from siblings like sdnext_civitai_metadata_scan (which scans metadata) by focusing on the update operation. The endpoint is also provided, adding precision.

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

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

No guidance on when to use this tool versus alternatives. It does not mention prerequisites, typical workflows (e.g., scan first then update), or exclusions. The description is purely a statement of function without contextual usage instructions.

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

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

No annotations are provided, so the description carries the full burden. It does not disclose potential rate limits, auth requirements, or what happens when the model ID is invalid or not found. It simply states the API call without 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.

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

The description is a single, concise sentence with no fluff. It front-loads the purpose and includes the endpoint for reference, which is useful for developers.

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

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

Given that there are no annotations, no output schema, and only one parameter, the description is minimal. It doesn't explain what the response contains, how to handle errors, or any rate limiting, which could be important for an agent using this tool.

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

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

Schema description coverage is 100% for the single parameter, so baseline is 3. The description adds the context that the ID refers to CivitAI model, but the schema already states 'CivitAI model ID.' No additional meaning is provided.

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

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

The description clearly states the tool fetches a single CivitAI model by ID, referencing the exact API endpoint. It distinguishes itself from related tools like sdnext_civitai_search and sdnext_civitai_version by specifying 'single model by ID'.

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

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

The description implies when to use this tool (when you have a specific model ID) but doesn't mention alternatives or when not to use it, such as searching by name or getting versions. Context is clear but lacks explicit exclusions.

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

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

No annotations are provided, and the description only mentions the HTTP method. It does not disclose side effects, idempotency, error behavior, or what happens when the name does not exist, leaving the agent with incomplete understanding.

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

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

The description is a single sentence that is direct and free of fluff, making it highly efficient.

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

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

For a simple removal operation with one parameter, the description covers the core action. However, it omits details about the expected response or outcome, especially when the name is not currently banned, which could be relevant for the agent.

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

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

The only parameter 'name' has a description that matches its purpose. Since schema coverage is 100%, the baseline is 3; the description does not add significant extra context beyond the schema.

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

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

The description clearly states the action ('Remove a banned model name') and includes the HTTP method and endpoint, leaving no ambiguity about the tool's purpose.

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

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

It is evident this tool is for unbanning a model, and sibling tools like sdnext_civitai_add_banned provide contrast. However, it does not explicitly mention when to prefer this over alternatives or any conditions for use.

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

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

Annotations are absent, so the description owns the burden. It discloses that the operation is a DELETE via POST, but does not mention side effects like irreversibility, authentication requirements, or what happens if the bookmark does not exist. The single sentence is thin on behavioral context beyond the endpoint.

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

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

The description is a single concise sentence that names the action and the endpoint. It front-loads the purpose ('Remove a CivitAI bookmark') and includes the HTTP method and path, with zero wasted words.

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

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

For a simple one-parameter tool, the description is minimal but lacks any usage context, error behavior, or idempotency notes. It is adequate for basic understanding but does not fully equip the agent to use it correctly in all situations (e.g., what happens if the bookmark doesn't exist).

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

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

The schema describes the only parameter 'name' fully ('Bookmark name to remove'), and coverage is 100%. The description adds no extra semantics beyond what the schema already provides, so it meets the baseline but does not enhance understanding.

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

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

The description clearly states it removes a CivitAI bookmark, uses a specific verb (Remove) and resource (bookmark), and indicates the HTTP endpoint. It distinguishes itself from sibling tools like sdnext_civitai_add_bookmark and sdnext_civitai_remove_banned by naming the exact resource type.

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

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

No guidance on when to use this tool versus alternatives, no prerequisites, and no mention of when not to use it. It only states the action without any context for selection, so the agent has to infer based on the name.

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

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

With no annotations provided, the description carries the full burden. It only says 'Resolve the local save path' and includes a GET endpoint, which implies a read-only operation, but it does not disclose authentication needs, error behavior, or what happens when no match is found. This is minimal transparency.

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

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

The description is a single, front-loaded sentence with no fluff. The parenthetical endpoint is useful. However, it is so terse that it sacrifices necessary detail, but for what it includes, it is concise and well-structured.

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

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

Despite having 8 optional parameters, no output schema, and no annotations, the description only states the core action. It lacks information about return values, how parameters combine, required inputs, and behavioral side effects, making it inadequate for an agent to use the tool correctly.

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

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

The schema has 8 parameters with 0% description coverage, and the description does not mention any parameter or explain how to specify a model/version. It simply says 'model/version' without indicating how the 8 optional fields (model_id, version_id, model_name, etc.) are used, providing no added meaning beyond the schema.

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

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

The description clearly states the tool's function: 'Resolve the local save path for a CivitAI model/version' with the specific endpoint. This distinguishes it from sibling tools like download, search, or model info. It also includes the HTTP method, adding specificity.

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

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 sdnext_civitai_download or sdnext_civitai_check_local. It does not mention any prerequisites, conditions, or which parameters are typically needed, leaving the agent without context for selection.

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

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

No annotations are provided, so the description carries the full burden. The description states the HTTP method (GET) and endpoint, which implies a read-only operation. However, it does not disclose whether auth or API keys are required, rate limits, or what happens if the search is empty or the API is unreachable. The enumeration of parameters gives some behavioral hints (e.g., nsfw as a separate filter), but it doesn't describe the return format or pagination behavior beyond the cursor parameter.

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

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

The description is a single, compact sentence that lists all filters and includes the endpoint. It is front-loaded with the purpose and immediately enumerates the parameters without fluff. It could have been structured as a list, but a single line is efficient. No unnecessary words or repetition.

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

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

With 11 parameters, no required ones, and no output schema, the description provides a good overview but lacks depth on edge cases (e.g., default behaviors, error handling, and the meaning of 'cursor' for pagination). The schema covers parameter details, but the description doesn't explain the tool's integration with the rest of the CivitAI ecosystem (e.g., how search results relate to sdnext_civitai_model). It is adequate but not exhaustive.

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

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

The schema description coverage is 91%, meaning nearly every parameter has a description in the schema. The tool description adds a concise list of all filter names and examples for some (e.g., sort values are given in the schema, not the description). The description does not add new semantics beyond the schema's descriptions, but it does organize them in a single sentence, which is convenient. Since the schema already does the heavy lifting, a baseline 3 is appropriate.

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

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

The description clearly states the tool searches CivitAI models and explicitly names all filter parameters. It includes the exact API endpoint and conveys the primary action (search) with a specific resource (CivitAI models). While the sibling tools are similar (e.g., sdnext_civitai_model for getting a model by ID, sdnext_civitai_tags for tags), the description's enumeration of filters and the search context distinguishes it sufficiently from the other CivitAI tools.

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

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

The description lists all filter categories, implicitly conveying that the tool is the primary search interface for CivitAI. It does not explicitly state when to prefer this over sdnext_civitai_legacy or other CivitAI list tools, but the mention of filters like query, tag, types, and the pagination parameter clearly implies a broad search use case. The absence of explicit exclusions or alternatives is a minor gap 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.

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

With no annotations, the description carries full burden. It mentions server-side validation of the token but doesn't disclose whether updates are partially applied, require authentication, or if any fields are mutually exclusive. It implies a mutation (update) but lacks consequences or side effects.

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

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

Single sentence, packs endpoint and key fields, front-loaded purpose. No fluff, earns its place, though it could be slightly more structured (e.g., bullet list of settings).

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

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

For a settings-update tool with 4 parameters, no output schema, and no annotations, more is needed. It doesn't explain which fields are optional, defaults, or the effect of toggles like 'save_subfolder_enabled'. The endpoint reference is helpful but incomplete.

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

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

Schema description coverage is only 25% (only token is described). The description lists parameter names but adds little meaning beyond the names. For example, 'save_subfolder_enabled' likely controls whether 'save_subfolder' is used, but the description doesn't explain semantics. It partly compensates by listing fields but insufficiently.

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

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

Description clearly identifies the tool as updating CivitAI integration settings, names the endpoint and lists key fields (token, save_subfolder, etc.). It is distinct from siblings like 'sdnext_civitai_search' or 'sdnext_civitai_download', which serve different purposes, though it doesn't explicitly contrast with them.

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

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

No guidance on when to use this tool versus others. It doesn't mention prerequisites, when settings would need updating, or which fields are optional. The sibling context includes many CivitAI-related tools, but this description doesn't help distinguish usage scenarios.

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

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

No annotations are provided, so the description must carry behavioral disclosure. It correctly implies a read operation ('Get') and states the HTTP method (GET), which is helpful. However, it doesn't detail any side effects (likely none) or what the response contains. Given the tool is a simple GET, the endpoint method adds transparency, but the description could clarify that it returns the current settings object.

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

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

The description is a single concise sentence with no filler. It includes the resource, operation, and endpoint. It is front-loaded with the purpose and provides a technical reference, earning every character.

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

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

For a zero-param read tool, the description is complete: it names the operation, resource, and endpoint. It doesn't provide return format details, but no output schema exists, so some context about what settings are included could be useful. However, given the low complexity and clear endpoint, the description suffices.

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

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

The tool has zero parameters, so schema coverage is 100% trivially. The description doesn't need to explain parameters; the schema already vacuous. A baseline 4 is appropriate because there is nothing to add.

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

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

The description clearly states the tool retrieves CivitAI integration settings via a specific HTTP endpoint (GET /sdapi/v2/civitai/settings). It distinguishes from sibling tools like sdnext_civitai_set_settings, which sets settings, and other CivitAI tools focused on search, download, etc. Though it could better differentiate from the broader sdnext_get_options, it clearly identifies its resource.

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

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

The description implies usage for reading current CivitAI integration settings, but provides no explicit context on when to use vs. alternatives. It doesn't note that this complements sdnext_civitai_set_settings for modifications. The endpoint reference gives a hint, but no explicit 'when to use' guidance.

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

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

With no annotations, the description must fully disclose behavior. It only states the action and endpoint, omitting pagination, authentication, rate limits, or result format. No contradictions, but no added value beyond the schema.

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

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

The description is a single sentence with no redundancy, making it concise. However, it is under-specified, lacking essential details, so it earns only a middle score for efficiency.

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

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

For a simple search tool with three parameters and no output schema, the description is extremely minimal. It fails to describe query behavior, pagination, or return structure, making it inadequate for correct usage.

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

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

Schema description coverage is 0%, so the description must explain parameters. It does not mention 'page', 'limit', or 'query', offering no semantics beyond the schema's defaults.

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

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

The description clearly states 'Search CivitAI tags', using a specific verb and resource. It distinguishes from sibling tools like civitai_search or civitai_model, which target other entities. The endpoint adds clarity.

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

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

No guidance is provided on when to use this tool versus alternatives such as civitai_search or civitai_creators. There is no mention of exclusions or context for selection.

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

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

No annotations are provided, so the description must carry the full transparency burden. It only says 'Get' and shows the GET endpoint, implying a read operation, but it does not disclose potential external network calls, authentication requirements, rate limits, or error behavior. The description is minimal and leaves important behavioral details unspecified.

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

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

A single, front-loaded sentence that clearly states the action and target. No wasted words; the endpoint is appended for extra precision without bloat.

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

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

For a simple single-parameter getter, the description is functional but not complete. It does not describe the return value, potential 404 or error conditions, or whether the data is fetched live from CivitAI. No output schema exists, so the description should have provided more context about the response.

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

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

Schema description coverage is 100% (version_id is described as 'CivitAI version ID'). The description adds no extra parameter meaning beyond the schema, so the baseline of 3 applies.

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

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

Description states a specific verb ('Get') and resource ('CivitAI model version by ID'), with the exact API endpoint. It clearly distinguishes this from the sibling sdnext_civitai_version_by_hash by specifying 'by ID'.

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

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

No guidance on when to use this tool versus alternatives. It does not mention that sdnext_civitai_version_by_hash is the option when only a hash is available, nor any other exclusions. The simple use case is implied but not stated.

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

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

With no annotations, the description carries the full burden of transparency. It does not mention potential errors, rate limits, authentication requirements, or side effects, which are critical for a lookup endpoint.

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

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

The description is a single, concise sentence that front-loads the action and resource. It avoids redundancy and is well-structured for quick understanding.

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

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

Given the simplicity of the tool and lack of output schema, the description is adequate. It could mention that it returns version information, but this is not critical for basic usage.

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

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

The schema already provides a clear description for the 'hash' parameter ('SHA256 file hash'), so the tool description adds no extra meaning. This meets the baseline expectation of 3.

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

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

The description clearly states the tool's purpose: to resolve a CivitAI version by file hash. It distinguishes this from other CivitAI tools by specifying the hash-based lookup, making the intent unambiguous.

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

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

The description does not explicitly state when to use this tool versus alternatives (e.g., searching by model ID or listing versions). It lacks guidance on use cases or conditions, leaving the user to infer that it's for hash lookups.

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

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

No annotations are provided, so the description carries the full burden. It properly implies this is a read-only, non-mutating operation with a side-effect-free GET. However, it doesn't disclose what the payload looks like at all—flags could be returned as a flat list of strings, key-value pairs, or a structured object—and there's no mention of potential variability based on server configuration. A bit more context (e.g., 'includes paths, server URL, and launch-time options') would help.

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

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

The description is brief and front-loaded with the key action word 'Get.' However, given the availability of sibling tools and the lack of other documentation, a single clarifying phrase about use cases (e.g., 'Use for debugging or checking launch configuration') would add value without bloat.

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

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

For a zero-parameter, read-only informational endpoint, the description is arguably complete. Yet the lack of details about output format or returned data structure is a gap given there's no output schema to backfill it. The description is also not explicit about whether this returns all server options or just those passed via command-line flags (which may be ambiguous for the agent).

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

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

There are zero parameters and the schema coverage is 100% (trivially). The description is not expected to explain parameters that don't exist. However, since no output schema is provided, the agent receives no hints about what the returned flags' structure might be. Score of 4 reflects that zero-parameter means the baseline is high, but some pointer to output structure would make it a 5.

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

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

The description clearly states the tool gets all command-line flags the server was started with, using a specific verb ('Get') and a well-defined resource ('command-line flags'). The description is distinct from sibling tools like sdnext_get_options and sdnext_status by virtue of being a system-level configuration report, and the endpoint path is included for reference.

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

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

No explicit when-to-use vs alternatives guidance is provided. However, the endpoint is so simple and domain-specific that the intended usage is largely self-evident. A score of 3 reflects that the description is minimal on contextual guidance but not misleading for a zero-parameter, read-only endpoint.

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

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

No annotations are present, so the description bears the full transparency burden. It discloses that the tool returns images and preprocessor maps, but gives no context about compute costs, whether images are saved to disk despite the save_images flag, or potential side effects. One sentence is too thin for a generation endpoint with 49 parameters.

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

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

The description is a single front-loaded sentence that states the action, endpoint, key requirement, and return value with no wasted words.

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

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

For a 49-parameter tool with no output schema and no annotations, the description is not contextually complete: it omits usage guidance relative to sdnext_txt2img, any explanation of control_units structure (despite that being the required nested object), and default behaviors (e.g. whether images are returned/saved). The rich schema descriptions mitigate but do not replace missing high-level context.

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

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

Schema coverage is high (92%), so the baseline is 3; the description adds real value by enumerating what kinds of control units are supported (controlnet / t2i adapter / xs / lite / reference / ip), which the control_units schema entry only crosses-references. However, it adds no semantics for the remaining 48 parameters.

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

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

The description opens with an action verb ('Run'), identifies the exact endpoint (/sdapi/v1/control), names the key input concept (control units), lists supported types, and states expected outputs. This clearly differentiates it from sibling tools like sdnext_txt2img and sdnext_img2img.

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

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

The phrase 'with one or more control units' and the listed types imply this is the tool to use for ControlNet/adapter-guided generation, but it never explicitly contrasts it with sdnext_txt2img, explains prerequisites, or says when not to use it. No alternative tools are named.

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

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

Annotations already declare destructiveHint: true and readOnlyHint: false, so the 'DESTRUCTIVE' warning in the description adds little beyond what structured metadata provides. The description does not contradict the annotations, but it also contributes minimal additional behavioral insight beyond the endpoint URL and repetition of destructiveness.

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

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

The description is extremely tight—one sentence plus a one-word emphatic warning. There is zero wasted wording and the destructive warning is front-loaded and highly visible. Slightly more useful content could be added, but as-is it is efficiently structured.

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

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

For a single-parameter tool with strong annotations and no output schema, the description is mostly adequate. However, it misses opportunities to cover edge-case context like whether the operation is reversible, permission requirements, or whether the deleted file is permanently removed versus moved to trash. Minimal but passable.

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

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

Schema description coverage is 100%, and the schema itself thoroughly documents the 'file' parameter, including relative path semantics and allowed directory examples. The description adds nothing about parameters, which is acceptable given the schema covers the bases. This hits the baseline of 3 for high schema coverage.

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

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

'Delete a file' uses a clear verb+resource construction and includes the raw HTTP endpoint (DELETE /sdapi/v1/delete-file) which adds precision. It could better distinguish itself from sibling tools like sdnext_delete_image or sdnext_file, but the core purpose is unambiguous.

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

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. Given the presence of similar siblings (sdnext_file, sdnext_delete_image, sdnext_upload) that might overlap, an explicit note on file deletion semantics or constraints would help. No when-to-use or when-not-to-use context is offered.

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

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

Annotations already declare destructiveHint=true, so the description adds 'DESTRUCTIVE' as a redundant emphasis. It adds the endpoint path and the 'generated image' scope, but no new behavioral traits beyond the annotations. Given the annotation coverage, it meets the baseline but does not go further.

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

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

The description is a single sentence plus a warning, front-loaded with the core action. Every word adds value; there is zero redundancy or irrelevant detail.

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

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

The tool is simple (1 param, clear schema, annotations cover destructiveness, no output schema). The description provides the essential purpose and endpoint, and the schema/annotations fill in the rest. It could mention irreversibility, but that is already implied by 'DESTRUCTIVE' and the destructiveHint, so it is sufficiently complete for its complexity.

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

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

The schema already provides a comprehensive description of the 'file' parameter (relative path and allowed directories), with 100% coverage. The description adds no additional parameter insight, so the baseline 3 applies.

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

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

The description clearly states the action ('Delete') and the resource ('generated image file'), and includes the exact endpoint for precision. It differentiates from catalog query tools and even from the sibling 'sdnext_delete_file' by specifying 'generated image file'.

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

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

No guidance is provided on when to use this tool versus alternatives like 'sdnext_delete_file'. It does not mention exclusions, required permissions, or typical use cases. The reader must infer that this is for deleting generated images specifically.

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

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

With no annotations, the description must explain side effects, return values, and runtime behavior. It only states it is 'a standalone operation' and mentions the fallback logic. It does not say whether the operation mutates stored state, its compute cost, what happens on detection failure, or the response format. Since no output schema exists, this lack of behavioral detail is a serious gap.

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

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

The description is brief (one sentence plus a fallback note) and correctly names the endpoint. However, for a 31-parameter standalone API call, it is severely under-specified; the front-loaded 'standalone' concept is good, but critical context like model selection, expected input format, and result handling is absent. Conciseness is good, but at the cost of completeness.

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

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

With no annotations, no output schema, and only 6% schema coverage, the description bears the full burden. It fails to explain return values, error cases (e.g., no detections), or the interplay between detailer_* flags Mkargs. The fallback note is helpful but insufficient for a 31-parameter complex tool. The context about 'standalone vs. base pass' is the only contextual anchor.

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

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

Schema coverage is only 6%, with 31 parameters. The description adds no per-parameter meaning beyond the fallback note. It does not define what 'detailer_*' parameters control, how segmentation/thresholding work, or what the resolution/strength values do. The fallback sentence is the only parametric insight and it's vague about the source of global defaults.

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

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

The verb 'run' and resource 'YOLO detailer' are clear, and 'standalone operation' with 'no base generation pass' distinguishes it from a combined txt2img+detailer flow. It does not explicitly name sibling tools like sdnext_txt2img or sdnext_extra_network_detail to differentiate, but the edge case is understandable. Score 4.

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

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

The description implies use for detail-only processing of an existing image ('standalone operation'), but does not explicitly state when to choose this over sdnext_img2img or how parameter fallback affects selection. It also does not mention the companion sdnext_list_detailers tool for model discovery, despite its clear relevance. The phrase 'fields fall back to global settings' is useful but under-specified. No explicit 'use when' guidance—only a negative constraint.

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

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

No annotations are provided, so the description carries the behavioral disclosure burden. It does disclose return categories (classes, labels, boxes, crops, scores) and the endpoint, but it does not mention default model behavior, no-detection responses, errors, or confirm that the operation is non-mutating.

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

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

The description is a single well-structured sentence that front-loads the action and resource, then gives the endpoint and return values. There is no redundancy or filler.

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

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

For a simple two-parameter tool with full schema coverage and no output schema, the description is mostly complete: it states the task, method, endpoint, and return categories. A small gap is lack of guidance on model defaults or how to choose from the possible model values, but the schema partially covers the latter.

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

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

The schema already documents both parameters fully, including accepted image formats and the model name source (sdnext_list_detailers). The description adds no parameter-level detail beyond the schema, so the baseline score of 3 is appropriate.

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

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

Description uses a specific verb ('Detect'), names the resource ('faces/objects'), identifies the technique (YOLO), gives the exact API path (/sdapi/v1/detect), and lists return categories. This clearly distinguishes it from sibling tools such as sdnext_nudenet, sdnext_tagger, or sdnext_caption.

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

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

The usage context is implied: use this tool when face/object detection on an image is needed. However, it does not explicitly contrast with detection- or analysis-related siblings like sdnext_nudenet, sdnext_tagger, sdnext_vqa, or sdnext_analyze, and gives no 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.

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

No annotations are provided, so the description must disclose behavioral traits. The description is minimal, only stating the HTTP endpoint and the action. It does not disclose what 'detailed metadata' includes, potential errors (e.g., item not found), or any side effects (though likely read-only). The description adds little beyond what the schema and title already imply.

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

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

The description is very concise, a single sentence that clearly states the tool's purpose and the underlying API endpoint. It is appropriately sized and front-loaded with the essential purpose, though it could benefit from a little more behavioral context.

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

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

The tool is simple (2 required parameters, no output schema), and the schema fully covers parameter semantics. However, the lack of output description or behavioral details (e.g., what metadata is returned) means the description is minimally sufficient but not complete. It covers the essential purpose but leaves out return value details.

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

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

Schema description coverage is 100% (both parameters have descriptions), so the baseline is 3. The description itself does not add any additional parameter meaning beyond the schema, but it is adequate because the schema already documents 'name' and 'page'.

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

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

The description clearly states the tool retrieves detailed metadata for one extra network item, with a specific verb ('Get') and resource ('extra network item'). The title 'Extra Network Detail' is similar to sibling 'sdnext_extra_network_details', but the description's focus on 'one item' distinguishes it from the plural 'details' tool.

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

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

The description implies usage (get details for one item) but does not explicitly state when to use this versus alternatives like sdnext_extra_network_details (which likely lists multiple) or sdnext_list_extra_networks. No exclusions or alternatives are mentioned, but the context is clear enough for a simple lookup tool.

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

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

No annotations are present, and the description provides no information about side effects, permissions, rate limits, or pagination limits. The word 'fetch' suggests a read-only operation, but this is not explicitly stated, leaving behavior largely unspecified.

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

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

The description is a single concise sentence that conveys the core function without redundant details. It is well-structured and free of unnecessary words.

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

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

The description is too brief to cover the tool's complexity: it does not explain what 'full details' includes, how pagination parameters interact, or what the response format is. Without an output schema, essential return information is missing, making the tool under-documented.

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

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

The description does not explain any of the eight parameters (hash, name, page, limit, title, offset, filename, fullname). With zero schema descriptions, the description must compensate, but it remains silent on parameter meaning, making usage ambiguous.

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

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

The description clearly states the tool fetches full details for extra network items in batch mode with pagination. It distinguishes itself from singular detail or list tools through the explicit 'batch-fetch' verb.

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

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

The term 'batch-fetch' implies this tool should be used when multiple items are needed at once, but no explicit guidance on when to prefer it over alternatives (e.g., individual detail calls) is provided. The usage scenario is only implied, not directly stated.

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

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

The description discloses the security constraint (must be inside allowed dir) and that it returns raw content. However, it does not mention error handling, response format details, or that it is a read-only operation. Without annotations, this leaves some behavioral aspects unclear.

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

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

The description is concise and front-loaded, stating the action first and then the constraint. It avoids unnecessary verbosity and is well-structured for quick comprehension.

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

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

The description covers the core functionality and key constraints, and mentions the output as raw content. It lacks explicit details on error scenarios or security implications beyond the directory restriction, but for a simple fetch tool it is largely complete.

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

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

The parameter description adds significant meaning beyond the schema: it clarifies that the file path can be relative or absolute, gives an example, and explains the allowed directories. This is detailed and helpful for correct usage.

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

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

The description clearly states the tool's purpose: fetching a file from the server as raw content via a GET request. It specifies the HTTP method and endpoint, and the allowed directory constraint, making it distinct from sibling tools that list or manipulate files.

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

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

The description provides a constraint (allowed directories) but does not explicitly state when to use this tool versus alternatives like listing or deleting files. The purpose is implied but not explicitly contrasted with other tools, so guidance is adequate but not explicit.

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

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

With no annotations provided, the description must carry the transparency burden. It discloses the operation as a GET (read-only side effect), but it does not specify what fields are returned (e.g., model name, hash) or any potential failure conditions (e.g., no checkpoint loaded). The description is not misleading but lacks depth for a tool with no output schema.

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

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

The description is a single, front-loaded sentence that states the purpose immediately. It includes the API endpoint as a helpful reference without any fluff. Every word earns its place, fitting the 'two sentences, zero waste' ideal.

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

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

For a simple getter with no parameters and no output schema, the description conveys the essential purpose. However, it could be more complete by briefly mentioning typical return fields (e.g., checkpoint name, hash) to reduce uncertainty for an agent. Still, the tool's simplicity and the clear distinction from siblings make it adequate.

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

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

The tool has zero parameters, so there is nothing for the description to explain beyond what the empty schema conveys. Per the rubric, a 0-parameter case warrants a baseline of 4, and the description does not introduce any necessary parameter details (it correctly omits them).

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

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

The description clearly states the action ('Get info') and the specific resource ('currently loaded checkpoint'), which unambiguously distinguishes it from siblings like sdnext_list_checkpoints (which lists all) and sdnext_select_checkpoint (which sets). The inclusion of the API endpoint adds technical clarity without ambiguity.

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

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

The description implies when to use this tool (when you need the active checkpoint's info) but does not explicitly contrast it with alternatives or state when not to use it. While the 'currently loaded' wording hints at the scope, there is no direct guidance for an agent choosing among sdnext_get_checkpoint, sdnext_list_checkpoints, or sdnext_select_checkpoint.

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

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

With no annotations, the description must carry all behavioral disclosure. It states it 'gets' options, implying a read-only operation, but does not explicitly mention that it makes no modifications, nor does it describe the response format (e.g., a JSON object) or any potential side effects like rate limits or caching. The description is minimal and leaves the agent to infer safety and output characteristics.

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

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

The description is a single, front-loaded sentence that includes the verb, resource, and even the underlying API path. It is concise with zero wasted words, ideal for a simple getter.

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

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

Given the simplicity (0 params, no output schema), the description might be sufficient, but it lacks any mention of the return structure or how this differs from the sibling 'options_info'. Since the tool is a simple getter, the description could be slightly more complete by stating 'returns a JSON object of current settings' or noting that it's the full options object. The absence of such detail leaves some ambiguity, though not critical.

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

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

The tool has zero parameters, so the empty schema is inherently complete. According to rubric, baseline for 0 params is 4, and the description doesn't add parameter info because none exist. No need for compensation.

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

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

The description clearly states 'Get all current UI/server options' with the specific HTTP endpoint, which clearly identifies the action and resource. It distinguishes itself from any potential write operations like 'set_options' by using 'Get'. While it doesn't explicitly contrast with the sibling 'options_info', the explicit scope and endpoint are specific enough.

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

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 'options_info' or 'set_options'. It does not mention any prerequisites, exclusions, or scenarios where another tool would be more appropriate. For a simple getter this might be acceptable, but the lack of context leaves ambiguity given the large sibling set.

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

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

No annotations provided, so description carries the burden. It states the endpoint and purpose but doesn't disclose any side effects (likely read-only) or data format. For a simple read, this is minimally adequate, but could note that it's a read-only operation.

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

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

Single sentence, perfectly sized, no fluff. Every word adds value.

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

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

Given the simplicity (0 params, no output schema), the description is largely sufficient. It could mention that it returns current GPU status, but not critical. The tool is simple enough that this is adequate.

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

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

The tool has zero parameters, and schema coverage is 100% (no params to describe). Baseline for 0 params is 4, and no additional parameter explanation is needed.

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

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

The description clearly states it retrieves GPU device info via a specific endpoint, distinguishing it from siblings like memory or status tools. It's concise and uses a clear verb+resource pattern.

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

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

The description implies use when GPU info is needed, but doesn't explicitly mention when not to use it or suggest alternatives among siblings. It's adequate for a simple info retrieval, but could be more explicit.

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

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

No annotations exist, so the description must disclose side effects or constraints. It mentions a GET endpoint, implying read-only, but does not explicitly state that, nor any potential latency, multi-GPU behavior, or error cases. The list of metrics is helpful but lacks deeper 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.

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

A single, clear sentence with no filler or repetition. The structure directly conveys the tool's purpose and expected output.

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

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

No annotations, no output schema, and no notes on units, multi-GPU behavior, or refresh rate. The description leaves the agent guessing about return structure and scope, which is risky when the tool may have multiple GPUs.

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

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

The schema has zero parameters (100% coverage), and the description implicitly confirms no input is needed. There is nothing ambiguous to clarify.

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

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

The description clearly states the tool gets detailed GPU metrics, listing specific metrics (name, utilization, memory, clocks). It is distinct as a general metrics tool, but does not explicitly differentiate from nearby siblings like sdnext_memory or sdnext_gpu.

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

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

It conveys that this tool is for detailed GPU metrics, but gives no guidance on when to choose it over alternatives (e.g., sdnext_memory for memory-specific queries). No exclusions or comparison to siblings.

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

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

The verb 'Get' implies a read-only operation, but the description does not explicitly state side effects, permissions, or potential impacts. With no annotations, this minimal information leaves users uncertain about behavior beyond the basic retrieval.

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

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

The description is extremely concise, consisting of a single sentence with no extraneous words. It efficiently conveys the core purpose and endpoint.

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

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

The description lacks essential context such as the return format, pagination details, or whether history is cleared after retrieval. For a simple read tool, this brevity leaves important gaps for a user unfamiliar with the API.

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

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

The input schema provides a description for the 'id' parameter ('Filter by task/job id.'), and the tool description adds no additional meaning. Since schema coverage is complete, the baseline score of 3 is appropriate.

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

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

The description clearly states the tool retrieves generation history entries and includes the API endpoint. It is specific about the resource, though it largely restates the title without adding further detail.

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

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 sdnext_latent_history or sdnext_list_latents. There is no mention of appropriate contexts or prerequisites.

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

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

With no annotations, the description carries the full burden of disclosing behavior. It only states the action (run through a guard model) but does not explain side effects, what happens to the image, or what output to expect. Lacks transparency.

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

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

The description is a single, concise sentence that conveys the essential function without unnecessary words. It is well-structured and easy to parse.

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

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

The description lacks important context such as the expected output format, how results are returned, or any caveats about the guard model. Given that no output schema exists, the description should provide more detail about the tool's behavior, but it remains minimal.

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

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

The schema already provides descriptive text for each parameter (image, model, policy), covering 100% of them. The description adds no additional context or clarification beyond the schema, so it meets the baseline but does not enhance understanding.

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

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

The description clearly states the tool's purpose: running an image through a content-safety guard model. The verb 'run' and resource 'image' are specific, and the intent (safety checking) is unambiguous, distinguishing it from other image-processing tools.

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

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

No guidance is provided on when to use this tool versus alternatives. The description does not mention any conditions, prerequisites, or scenarios where this tool is preferred over other safety-related or image-processing tools.

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