kaggle-mcp

Server Quality Checklist

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Latest release: v0.2.0
Disambiguation5/5
Every tool has a clear resource prefix (competition_, dataset_, kernel_, model_, discussion_) followed by a distinct action verb. Overlaps are minimal and resolved by descriptions (e.g., dataset_download vs. dataset_download_file). The only minor issue is kernel_output's description being a copy-paste error, but tool names are unambiguous.
Naming Consistency5/5
All tool names follow a consistent snake_case pattern of resource_prefix + action verb (e.g., competition_get, dataset_create, discussion_comments). No mixing of styles across the entire set.
Tool Count3/5
With 51 tools, this is on the high side for a single MCP server. While each tool serves a specific purpose and the Kaggle API is broad, the number feels heavy, especially with 12+ discussion-related tools. It's borderline but still manageable for an agent.
Completeness5/5
The tool surface covers nearly all key Kaggle resources: competitions (list, get, submit, leaderboard, data), datasets (full CRUD, versions, downloads), kernels (push, pull, sessions), models (create, delete, instances, versions), discussions (search, list, comments), and file upload. Missing actions (e.g., delete submission/kernel) are minor and uncommon. Very comprehensive.
Average 3.3/5 across 51 of 51 tools scored. Lowest: 2.5/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
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{
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}
```
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description must disclose all behavioral traits. It only says 'Create an interactive kernel session,' with no information about side effects, idempotency, authentication needs, or what happens if a session already exists.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise with a clear one-line purpose, but the parameter descriptions slightly repeat the tool name. No wasted words, though integrating parameters into a narrative could improve structure.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that an output schema exists, return values don't need explanation. However, the description lacks context about what an interactive kernel session entails, when to create one, or any usage scenario. This is incomplete for the tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description must compensate. It adds minimal meaning: 'Kernel owner username' clarifies the role of user_name, but kernel_slug is just restated. This barely adds value beyond the schema titles.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Create an interactive kernel session,' which specifies the verb and resource. This distinguishes it from sibling tools like kernel_session_cancel or kernel_session_status, though it doesn't explicitly differentiate.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance provided on when to use this tool versus alternatives like kernel_push or kernel_pull. No prerequisites or context for invocation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. The description says 'Delete' but gives no details about permanence, required permissions, cascading effects, or whether deletion can be undone. For a destructive action, this omission is significant.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short but includes parameter lines that duplicate schema content, reducing conciseness. It could be trimmed to a single sentence without the parameter block.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that this is a destructive tool with no output schema details (though output schema exists, it is not explained), no behavioral annotations, and minimal parameter info, the description is incomplete for safe and correct usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%. The description restates parameter names (owner, dataset_slug) without adding meaning beyond what the schema provides. No explanation of what constitutes a dataset slug or any constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states 'Delete a dataset.' which clearly indicates the action and resource. It distinguishes from sibling tools like dataset_create or dataset_get, but lacks details about scope or consequences.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives such as dataset_create_version or model_delete. No prerequisites or conditions for deletion are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It only states 'Get dataset metadata' without disclosing any behavioral traits such as read-only nature, authentication needs, or output structure. The output schema exists but the description adds no 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.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short but includes an Args block that essentially restates parameter names. It is not overly verbose, but the structure could be improved by front-loading the purpose and removing redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having an output schema that covers return values, the description omits any details about what metadata is returned, the scope of the data, or any constraints. For a two-parameter tool, this is insufficient context for an agent to use it effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, yet the description's Args section merely repeats the parameter names with minimal elaboration ('Dataset owner username', 'Dataset slug name'). This adds negligible value beyond the schema titles. With no enums or nested objects, the description should compensate but does not.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get dataset metadata' clearly states the verb and resource. However, it does not differentiate from sibling tools like dataset_get, which likely also retrieves metadata. A more specific scope or distinction would improve clarity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. There is no mention of context, prerequisites, or exclusions. The agent receives no help in choosing this tool over similar ones.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose side effects, idempotency, or authorization requirements. For a destructive operation, 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.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short and to the point, but lacks important context. It is not verbose, but the brevity sacrifices completeness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the existence of sibling tools like kernel_session_status and kernel_session_create, the description should provide more context about cancellation behavior, such as whether it is reversible or what happens if the session is already stopped. The output schema exists but is not referenced to explain return values.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description only repeats the parameter names without adding constraints, formats, or examples. The schema provides titles but no additional semantics, so the description fails to compensate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool cancels a running kernel session. The verb 'Cancel' and the resource 'running kernel session' are specific, and it distinguishes from sibling tools like kernel_session_create or kernel_session_status.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. For example, there is no mention of prerequisites (e.g., session must be running) or comparison with kernel_session_create or kernel_session_status.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits, but it only states the basic action. No details about permissions, rate limits, or side effects are mentioned.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short and to the point. It front-loads the purpose and lists parameters, but the structure is minimal and could be slightly better organized.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that an output schema exists, the description provides enough basic understanding for a simple retrieval tool. However, it lacks context about the output format or any caveats.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, yet the description merely restates the parameter names and types from the schema without adding deeper meaning (e.g., how to obtain the slug).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and the resource 'a notebook's source code'. It is a specific action distinct from sibling tools like kernel_output or kernel_push, though it does not explicitly differentiate them.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidelines are provided. The description does not indicate when to use this tool over alternatives, nor does it mention any prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It only mentions 'top 20' but does not disclose whether pagination exists, how scores are sorted, or any side effects. The behavioral insight is minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short but includes a docstring-style 'Args' block that redundantly restates the parameter. Removing that block would improve conciseness without losing information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the output schema exists, the description could omit return details, but it still lacks context on what the leaderboard contains (e.g., rank, score, entries). It is minimally adequate but not complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%. The description says 'Competition URL suffix' for the parameter, adding some context but no format examples or validation details. With only one parameter, more explicit guidance is expected.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'View competition leaderboard (top 20)', specifying the verb (View), resource (competition leaderboard), and scope (top 20). It effectively distinguishes from sibling tools like competition_leaderboard_download.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. Sibling tools like competition_data_summary or competition_leaderboard_download are not mentioned, leaving the agent without criteria for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description should disclose behaviors. It only states 'Download' and 'Returns download URL', omitting details like authentication, expiry of URLs, or side effects. 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Very concise with a clear structure including an Args section. Could be more front-loaded with the purpose, but overall efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 2 required parameters and existence of output schema, the description lacks context on how to obtain values (e.g., what is a kernel slug) and what the output URL contains. Incomplete for a tool with no annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0% (no descriptions in schema). The description adds brief explanations for both parameters ('Kernel owner username', 'Kernel slug name'), which is helpful but minimal. Does not specify format or examples.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it downloads competition data files and returns a download URL. However, the tool name 'kernel_output' suggests it might be for kernel output, while the description says 'competition data files', causing slight ambiguity. It distinguishes from sibling 'competition_download' only by name but not explicitly in description.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives like 'competition_download' or 'kernel_session_output'. No prerequisites or context provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description focuses only on parameter listing without disclosing behavioral traits like error handling, authentication requirements, or side effects (e.g., overwriting existing kernels). The tool's side effects (pushing a notebook) are implied but not detailed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short but includes a unnecessary docstring format. It could be more front-loaded, and the bullet list is clear but not dense.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 5 parameters (2 required), no schema descriptions, and no annotations, the description is incomplete. It does not explain return values (though an output schema exists) or prerequisites like Kaggle API authentication.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the tool description must compensate. However, each parameter is merely restated (e.g., 'title: Notebook title.') without additional constraints, formats, or examples. This adds minimal value over the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Push/save a notebook to Kaggle', which is a specific verb+resource combination. It distinguishes the tool from siblings like kernel_pull and kernel_output, which handle retrieval and output.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as kernel_pull or kernel_output. The description does not mention when not to use it or any prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, yet the description only states the action without detailing behavior, such as what the status contains, side effects, or performance characteristics.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short and front-loaded, but lacks substance beyond the bare minimum. It is concise but at the expense of completeness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema, return values are covered, but the description still fails to provide sufficient behavioral and usage context for this read-only tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The parameter list adds little beyond the schema; schema descriptions are 0% coverage, and the description does not explain concepts like 'kernel slug' or provide validation details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action 'Get' and the resource 'status of a kernel session', with parameter names listed. It is specific and distinct from sibling tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like kernel_output or kernel_session_output. Context for usage is implicitly clear but not explicitly stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description carries full burden but only states the core action. It does not disclose read-only nature, permission requirements, or rate limits. Basic behavioral context is missing.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise (one main sentence plus a short Args list). It is front-loaded with the primary action. The Args section is slightly redundant with the schema but adds clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple get tool with an output schema, the description covers the basic purpose and parameters. However, it lacks prerequisites (e.g., model existence) and error conditions. Overall adequate but not thorough.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, but the description adds meaning to both parameters by explaining 'owner' as model owner username and 'model_slug' as model slug/name. This provides necessary context beyond the schema's bare titles. However, no format or constraints are given.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get detailed information about a specific model,' using a specific verb and resource. It distinguishes well from sibling tools like models_list (listing) and model_delete (deletion).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., model_instance_get or models_list). The description lacks explicit usage context or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; description only says 'Create...' which implies mutation but does not disclose side effects, permission needs, or error conditions. Does not confirm whether it overwrites or appends versions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is short but uses an Args list format that is somewhat redundant with the schema. Could be more concise by omitting parameter details (already in schema) and focusing on usage context.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Output schema exists, so return value explanation not needed. However, for a creation tool, missing behavioral context like idempotency, uniqueness of versions, or required parent resources (must model instance exist?).
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Parameter descriptions add minimal value beyond names (e.g., 'owner: Model owner username'). With 0% schema coverage, the description should compensate but only restates obvious information. No constraints or formatting examples.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Create a new version for a model instance,' which is a specific verb-noun pair. This distinguishes it from siblings like model_create, model_instance_create, etc.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., model_create, model_instance_versions). No mention of prerequisites or context for using this version creation action.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fails to disclose important behavioral traits such as side effects, success/failure behavior, authentication needs, or destructive nature (submitting creates a new entry).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is concise with a front-loaded purpose statement and an Args block. However, the Args block redundantly repeats parameter info that is already in the schema.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Does not mention the output schema (despite having one), prerequisites like uploading a file first, or any error conditions. Incomplete for a tool that requires prior steps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Given 0% schema coverage, the description adds basic meaning to parameters (e.g., 'Competition URL suffix', 'Blob file token from upload'), but lacks detail on format or relationship to other tools.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Submit predictions to a competition' with a specific verb and resource, distinguishing it from sibling tools like competition_leaderboard or competition_download.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives, no prerequisites or context for when to invoke it, and no mention of not using it in certain cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; description only mentions returning a download URL. Missing behavioral traits such as authentication needs, error handling, or file size limits. The description does not compensate for the lack 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is concise and front-loaded with purpose, but could include more useful context without becoming verbose. The arg list is clear.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given simple string parameters and output schema presence, the description is minimally adequate but lacks context on prerequisites, error scenarios, or behavior under different conditions.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so description should add meaning. It lists parameters with minimal context (e.g., 'Owner dataset username') but does not define 'dataset_slug' or 'file_name' format, leaving ambiguity.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the action ('Download a single file from a dataset') and the output ('Returns download URL'), distinguishing it from sibling tools like dataset_download (whole dataset) and dataset_files (list files).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like dataset_download, nor any prerequisites or limitations. Implied usage but lacks explicit differentiation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavioral traits. It only states the basic purpose and parameter meanings, omitting details like pagination behavior, ordering, or any side effects (though likely none). The output schema (present externally) is not referenced, but the description does not actively mislead.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise (three lines) and front-loaded with the main purpose. However, the parameter descriptions are presented as plain text rather than structured, which slightly reduces readability.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple retrieval tool with two parameters and an output schema, the description covers purpose and parameter semantics. It lacks usage guidelines and sibling differentiation, leaving gaps in context. The presence of an output schema reduces the need to describe return values, so overall it is adequate but not fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description compensates by explaining discussion_id as numeric and page_size as number of comments with a max of 50. However, it does not mention the default value of 20 (which is inferable from schema) or elaborate on the output structure.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb (Get) and resource (comments for a discussion). However, it does not differentiate from sibling tools like discussion_comments_search or discussion_detail, which could cause confusion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives such as discussion_comments_search (for filtered queries) or discussion_detail (for metadata). No when-to-use or when-not-to-use context is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It mentions page_size with a max of 50, but lacks details on sorting, pagination, or what happens with no discussions. This is minimal for a list tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with one sentence and an Args docstring. Every sentence provides necessary information without waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 1 optional parameter and an output schema, the description is minimal but sufficient for a simple list operation. However, it lacks explanation of output fields, sorting, or filtering, leaving gaps for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 1 parameter with no description, but the description adds 'max 50' which is not in the schema. This adds some value, but the coverage is low (0%), so a 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists the current user's discussions, which distinguishes it from sibling tools like discussions_list that likely list all discussions. However, it could be more explicit about authentication context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like discussions_list or discussions_by_source. The description does not 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.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It mentions search/list but does not disclose behavioral traits like idempotency, rate limits, or whether it's read-only. The description is minimal and insufficient for a tool with no annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with a single sentence and an Args list. It is front-loaded with the main action. No extraneous text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 5 parameters (all optional) and an output schema present, the description covers the basic search/filter capability but lacks usage context. It is minimally complete for a listing tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, yet the description merely repeats parameter names with defaults. For 'sort_by', it lists example values but not as enums. The description adds little meaning beyond what the schema field names imply.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Search and list Kaggle notebooks/kernels' with specific verb and resource. The name 'kernels_list' combined with the description distinguishes it from sibling tools like 'competitions_list' or 'datasets_list'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. With many sibling tools, explicit when-to-use or when-not-to-use is missing, leaving the agent to infer context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and description does not disclose behavioral traits like auth requirements, idempotency, error handling, or side effects. The description only states the action without further context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is concise with a clear purpose followed by a bullet-like list of parameters. No redundant sentences, well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers all parameters but lacks information about return values or behavior (e.g., does it return the created model? what happens on conflict?). With an output schema available, description could still benefit from brief return info.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but description adds one-line explanations for each parameter (e.g., 'Owner username.'). Adds some meaning beyond the schema's titles and defaults, but lacks detail on constraints or formats.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states 'Create a new Kaggle model' with specific verb and resource. Lists required parameters. Does not explicitly differentiate from siblings like model_update or model_instance_create, but purpose is clear.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives (e.g., model_instance_create). No prerequisites or exclusions mentioned. Usage is only implied by the action.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must fully disclose behavioral traits. It only states that it creates an instance and lists parameters. It does not mention idempotency, authentication needs, rate limits, or whether creation might overwrite existing instances.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is structured as a Python docstring with a purpose sentence followed by an Args list. It is concise and front-loaded, though the parameter list could be more compact.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Although an output schema exists and return values are not required, the description misses important behavioral context for a creation tool, such as whether the operation is idempotent, if it triggers side effects, or how it interacts with other model operations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It provides brief explanations for each parameter, including examples for 'framework' and defaults for 'license_name' and 'is_private'. However, it largely repeats the schema and adds limited new meaning beyond parameter names.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Create a new instance for a Kaggle model,' which is a specific verb+resource combination. It differentiates from sibling tools like 'model_create' (creates the model itself) and 'model_instance_version_create' (creates a version of an instance).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It lacks information on prerequisites, when not to use it, or how it compares to related tools such as 'model_create' or 'model_instance_version_create'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description implies a read-only operation by stating it returns a download URL, but it does not explicitly confirm this or disclose any potential side effects. Since no annotations are provided, the description carries the burden, and it is minimally sufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short and front-loaded with the main action. However, it includes a docstring-style parameter listing that could be streamlined or omitted if the schema already provides the same info.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given an output schema exists and no annotations, the description covers the core functionality and parameters. However, it lacks details on rate limits, file size limits, or behavior when downloading multiple files.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With schema description coverage at 0%, the description adds brief explanations for each parameter (e.g., 'owner: Dataset owner username.'). While this adds basic meaning, it does not provide constraints, formats, or examples beyond what the schema shows.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Download dataset files. Returns download URL.' which specifies the action and resource. However, it does not differentiate from the sibling tool 'dataset_download_file', which likely has a similar purpose but with a different scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'dataset_download_file'. It does not mention any prerequisites, context, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description only states 'List files', implying a read operation. There is no disclosure of pagination, rate limits, or any behavioral traits beyond the obvious.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with two sentences plus a parameter list. It is front-loaded with the purpose and wastes no words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a list tool, the description omits critical details like whether results are paginated, sorted, or limited. While an output schema exists, behavioral gaps (e.g., no mention of file listing behavior) reduce completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description lists each parameter with a brief explanation (e.g., 'owner: Dataset owner username'), adding meaning beyond the bare parameter names in the schema. With 0% schema description coverage, this significantly aids the agent.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'List files in a dataset' with a clear verb and resource. However, it does not differentiate from sibling tools like dataset_download_file or datasets_list, which could cause confusion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives (e.g., dataset_download or dataset_download_file). No context on prerequisites or preferred scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided; the description carries the full burden. It indicates mutation (update) but does not disclose side effects (e.g., overwriting of non-provided fields), permission requirements, or idempotency. The description lists parameters but lacks behavioral traits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with a clear 'Args' block listing parameters and their semantics. No superfluous text. However, it could be slightly more structured (e.g., grouping optional vs required).
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema, the description does not need to explain return values. It covers the essential inputs and their behavior. However, it lacks information on success/error responses and constraints (e.g., title length limits).
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description compensates by explaining that empty strings mean 'leave empty to keep current'. This adds semantic meaning beyond the schema types and defaults. Without this, agents might misinterpret empty strings as clearing fields.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Update dataset metadata (title, description, license)' which specifies the verb and resource. It lists the specific fields that can be updated. However, it does not differentiate from sibling tools like dataset_create_version which also modifies datasets.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., dataset_create_version, dataset_delete). No context on prerequisites like dataset existence or ownership. The description implies usage for existing datasets but does not explain exclusivity.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must cover behavioral traits. It mentions sorting by hotness and a max page size, but omits any side effects, authentication needs, rate limits, or response structure beyond what the output schema may convey.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise, with a single purpose sentence followed by a clean parameter list. No extraneous information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple tool and presence of an output schema, the description is adequate but lacks usage context relative to sibling tools and deeper behavioral details. It could be more complete by explaining when to choose this over similar discussion tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, so the description compensates well by listing source_type values and page_size max. However, it does not explain the meaning of 'source_type' values or hotness sorting, leaving some ambiguity.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Browse trending discussions sorted by hotness,' which clearly identifies the action and resource. However, it does not explicitly differentiate from sibling tools like discussions_list or discussions_search, limiting differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It neither states when to use it (e.g., for trending content) nor when not to use it (e.g., for filtering by specific discussion attributes).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears the full burden of behavioral disclosure. However, it only states 'List all versions' without revealing any behavioral traits such as destructive potential, authentication needs, rate limits, or error handling. This is insufficient for a tool with no annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise: a single-line purpose followed by a parameter list. It is not overly verbose, and the essential information (purpose) is front-loaded. However, the parameter block feels redundant with the schema, slight inefficiency.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having an output schema, the description does not mention any contextual details like ordering, pagination, or filtering of versions. For a list tool, these are important for correct invocation. The description is too minimal to be considered complete given the tool's complexity and 4 required parameters.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, meaning no parameter descriptions in the schema. The description lists parameters and provides minimal explanations (e.g., 'owner: Model owner username') that essentially restate the parameter names. It adds little beyond what the parameter names already convey, failing to compensate for the schema's lack of detail.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'List all versions of a model instance.' This directly specifies the action (list) and the resource (versions of a model instance), making the tool's purpose unambiguous. Among sibling tools like model_instance_create and model_instance_get, this one is distinctly for listing versions, so differentiation is clear.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not provide any guidance on when to use this tool versus alternatives, nor does it mention prerequisites or context. The sibling list implies a context, but the description itself lacks explicit usage guidelines. It is adequate but missing this dimension.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavior. It indicates a read operation ('Get') but lacks details on permissions, side effects, rate limits, or what the returned leaderboard contains (e.g., columns, ordering).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise: one sentence followed by a structured docstring listing each parameter. It front-loads the action and resource without unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
An output schema exists, so the return value structure is defined elsewhere. The description covers the parameters adequately for a simple read operation. However, it could mention if there are any default sorts or pagination.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The docstring within the description explains each parameter's purpose: owner_slug (owner or org slug), benchmark_slug (slug name), and version_number (specific version, 0 for latest). Since the schema has no property descriptions, this text adds valuable context beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description begins with 'Get the leaderboard for a Kaggle benchmark', clearly stating the action and resource. The tool name itself distinguishes it from the similar competition_leaderboard sibling, but no explicit differentiation is provided.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given on when to use this tool versus alternatives like competition_leaderboard or other sibling tools. There are no use cases, prerequisites, or exclusions mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. The description does not disclose behavioral traits such as whether the tool is read-only, side effects, rate limits, or pagination behavior. Minimal info beyond basic purpose.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, with a single line purpose and a list of parameters. No redundant information, though it could be slightly more structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 4 parameters and an output schema, the description is minimal. It does not explain the output, pagination, or provide examples. Lacks completeness for a search/list tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%. The description provides brief semantics for each parameter (e.g., 'search term', 'sort order'), adding meaning beyond names but lacking allowed values or format details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Search and list Kaggle datasets.' It is a specific verb+resource combination and distinguishes from sibling tools like dataset_get or competitions_list.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for searching/listng datasets but does not explicitly state when to use this vs alternatives (e.g., dataset_get for a single dataset). No exclusions or context provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description must fully convey behavior. It only states the action but fails to disclose traits like read-only nature, pagination behavior, or rate limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences plus a readable argument list. No extra words, front-loaded with purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has an output schema (not shown) which reduces the need to describe return values. Still, the description omits context on result ordering, search semantics, or pagination handling. Adequate but not comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description adds value by explaining 'query' as a search query string and 'page_size' as number of results (max 50). However, it lacks details on syntax, defaults (20 is not mentioned), or constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Search' and the resource 'comments across all Kaggle discussions', differentiating it from sibling tools like 'discussions_search' which likely search discussion threads.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives such as 'discussions_search' or 'discussion_comments'. No context on prerequisites or typical use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It only states 'Delete' without disclosing side effects (e.g., cascade delete of versions, irreversibility, required scopes). Does not mention output or error scenarios despite an output schema existing.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short and to the point. The Args list is somewhat redundant with the schema, but it's not overly verbose. Front-loads the purpose in the first line.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 2 parameters, no annotations, and an output schema, the description does not explain what the output is, success/error behavior, or access requirements. For a destructive action, more context is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 0% description coverage; titles are generic ('Owner', 'Model Slug'). The description adds 'Owner username' and 'Model slug to delete', clarifying the meaning of each parameter. This adds value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Delete a Kaggle model.' It uses a specific verb (delete) and resource (Kaggle model). Among siblings like model_create, model_update, model_get, this tool is well-distinguished.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus others like model_update or model_instance_version_delete. No prerequisites, exclusions, or context on ownership or permissions. With many model-related siblings, usage guidance is needed.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Lacks annotations, but the description implies a safe read operation. However, no additional behavioral traits (e.g., authentication, response format) are disclosed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Highly concise: purpose stated upfront, followed by a clear parameter list. Every sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Does not explain the role of model_instance relative to model, or why all four parameters are needed. With zero schema coverage, more context is necessary.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, yet the description only repeats parameter names with minimal context (e.g., 'Model owner username.'). No additional meaning or constraints beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a clear verb 'get' and specific resource 'details of a specific model instance', distinguishing it from sibling tools like model_get and model_instances_list.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool over alternatives like model_get or model_instances_list, and no exclusions or prerequisites are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states the return type (download URL) but does not disclose behavioral traits such as authentication needs, side effects, rate limits, or error handling. This is insufficient for a download tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise at three sentences and front-loads the purpose. It is efficient, though a bit more structure (e.g., listing parameters) could improve clarity without adding length.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's 2 parameters and output schema, the description is adequate but misses details like authentication requirements, existence checks for competition, and exact behavior for empty file_name. With many sibling tools, it could be more complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must add meaning. It explains competition as URL suffix and file_name as specific or empty. This adds value but does not clarify what happens when file_name is empty (e.g., download all files as archive).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it downloads competition data files and returns a download URL. The verb 'download' and resource 'competition data files' are specific, and it distinguishes from sibling tools like competition_files or competition_leaderboard which do different actions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains that competition is the URL suffix and file_name can be specific or empty. However, it does not explicitly state when to use this tool over alternatives, nor does it mention any prerequisites or exclusions. Usage is implied but not elaborated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It mentions 'detailed info' but does not specify scope, side effects (read-only), or any constraints. For a get tool, minimal disclosure of behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, directly to the point. However, the second sentence is a Python docstring that could be merged into a single sentence. Still efficient overall.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With output schema present, description need not detail return format. However, lacking annotations, more behavioral context (like read-only nature) would improve completeness. Adequate for a simple 1-param tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Adds meaning beyond schema: provides example ('titanic') and clarifies it's a URL suffix. This compensates for zero schema description coverage, helping the agent construct valid arguments.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Title and description clearly state 'Get detailed competition info', specifying the resource (competition) and action (get). The example differentiates from siblings like competitions_list (list all competitions) and competition_leaderboard (leaderboard), making purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. Does not mention prerequisites, or scenarios where other tools (e.g., competitions_list for browsing) might be more appropriate. The agent has no context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations are absent, so the description carries full burden for behavioral disclosure. It does not mention side effects, authentication, rate limits, or what 'details' entail. The existence of an output schema partially mitigates, but the description itself is sparse.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, with a clear purpose statement followed by parameter details. It is front-loaded and wastes no words, though the parameter formatting could be tighter.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the low complexity, existence of output schema, and clear purpose, the description is mostly adequate. However, it lacks usage context and behavioral transparency, making it not fully complete for an agent to rely on alone.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description adds meaningful context: 'competition' is a URL suffix unused in routing, and submission_id is numeric. This compensates for the schema's lack of descriptions, though could be more precise.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get details for a single submission,' which is a specific verb+resource. It distinguishes from sibling tools like competition_submissions (list) and competition_submit (create). The parameter descriptions add context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives. The description only states its purpose without mentioning exclusions or related tools, leaving the agent to infer usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It only mentions parameters and allowed values, but does not disclose behavioral traits like pagination, rate limits, data freshness, or what the output contains. The existence of an output schema is not referenced.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with a clear Args list. It is front-loaded with a one-line purpose. However, it could be slightly more structured (e.g., separate sections) and the Args list is part of the same paragraph.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a browsing tool with an output schema, the description covers the essential parameters and filtering options. However, it lacks context on use cases, error handling, or relationship to other discussion tools. It is minimally complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must add meaning. It lists allowed values for source_type and sort_by, and notes max page_size, which are missing from the schema. However, it does not explain the purpose of query or page_size beyond defaults.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Browse discussions by source type' with a specific verb and resource. The parameter list further clarifies the filtering by source_type, distinguishing it from sibling tools like discussions_list or discussions_search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives such as discussions_list or discussions_search. There is no mention of prerequisites or scenarios where this tool is preferred.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description implies read-only behavior (browse) and lists sorting and pagination. However, no annotations are provided, so the description does not disclose additional traits like rate limits or authentication requirements. The presence of an output schema may reduce the burden slightly, but overall transparency is average.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise: one line summarizing the tool's purpose followed by a structured parameter list. Every sentence adds value, with no unnecessary text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity and the presence of many sibling tools, the description does not fully explain how this tool fits into the broader discussion ecosystem. The output schema is noted but not shown; however, the description is adequate for the core action. More context on return values and relationship to other tools would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description adds meaning by explaining the purpose of each parameter: competition filter, sort options, and page size limit (max 50). This goes beyond the schema's type and default information, providing necessary context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool browses competition solution write-ups, with a specific verb 'browse' and resource 'competition solution write-ups'. It mentions parameters for filtering and sorting, but does not explicitly differentiate from sibling tools like discussions_writeups or discussions_list, which could cause confusion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. For example, it doesn't explain that this is for competition-specific solutions as opposed to general discussion browsing. The description lacks explicit when-to-use or when-not-to-use advice.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. Description only states 'List output files' without disclosing read-only nature, error handling, pagination, or output format. The behavioral burden is on the description, which is minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Very concise: one-sentence description plus Args section. No extraneous words, but could be slightly more informative without losing brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Has output schema but does not explain return format. With 0% schema coverage and no annotations, the description is too sparse for a tool that lists files. Lacks details on behavior when session does not exist or when no output files are available.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description adds meaningful context: 'Kernel owner username' and 'Kernel slug name'. This clarifies parameter purpose beyond the bare schema titles.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'List output files from a kernel session' with specific verb 'List' and resource 'output files from a kernel session'. It specifies the two required arguments, distinguishing it from sibling tools like kernel_output or kernel_session_status.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. Does not mention scenarios where kernel_output or other list tools would be preferred, nor any prerequisites or caveats.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. Description is minimal, not disclosing read-only behavior, error handling, or rate limits. Only states 'List data files' 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise: two sentences covering purpose and parameter. No unnecessary words, efficient for a simple tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Output schema exists, so return values need less explanation. However, description omits details like pagination, file format, or listing behavior. Adequate but not thorough.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 0% description coverage. Description adds an example ('titanic') clarifying the parameter format, which helps but is not extensive.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states 'List data files for a competition' with a specific verb and resource. It distinguishes from sibling tools like competition_get or competition_download.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool vs alternatives. It implies utility for browsing available files before downloading but lacks exclusion criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states the operation (search/list) without mentioning that it is read-only, any rate limits, authentication needs, or pagination behavior beyond the page parameter.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief and the parameter list is well-structured. It avoids extraneous text, but the parameter descriptions could be more concise (e.g., integrating hints about default values).
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (4 parameters, no required fields, output schema exists), the description covers the main intent. However, it lacks information about pagination limits, error handling, or authentication, which are minor gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description compensates for 0% schema description coverage by providing plain-English explanations for each parameter: search term, category filter, sort order values, and page number. This adds useful meaning beyond the schema's default values and names.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Search and list' with the resource 'Kaggle competitions', clearly indicating a filtered listing operation. It distinguishes from sibling tools like competition_get (single competition retrieval) and competition_submissions (list submissions).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives such as competition_get or the other competition list endpoints. The description implies usage for searching/filtering, but does not clarify exclusivity 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.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It only states the action and lists parameters, with no disclosure of behavioral traits such as auth requirements, rate limits, or consequences of creating a version (e.g., immutability).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single clear sentence followed by a structured parameter list, with no unnecessary information. All content earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the existence of an output schema and moderate parameter count (4), the description covers the basic purpose and parameters but lacks information about return values or side effects, making 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.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, but the description adds brief explanations for each parameter (e.g., 'Dataset owner username', 'Comma-separated file tokens from file_upload'), providing meaning beyond the schema's type-only definitions. However, the descriptions are minimal and could be more detailed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Create a new version of an existing dataset' uses a specific verb 'create' and resource 'version of a dataset', clearly distinguishing it from siblings like 'dataset_create' (create new dataset) and 'dataset_update_metadata' (update metadata).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage by stating the action and listing required parameters, but it does not provide explicit guidance on when to use this tool versus alternatives or any prerequisites (e.g., existing dataset).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description describes a read operation ('List all instances') but does not disclose potential behavioral traits like pagination, sorting, or handling of empty results. It is minimally adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and structured with an 'Args' section, but the docstring format is slightly verbose for a tool description, yet every sentence serves a purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the existence of an output schema, the description does not need to explain return values, but it lacks context about ordering or limits, and could be more complete for a list tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description explains the parameters ('owner: Model owner username. model_slug: Model slug/name.'), adding meaningful context beyond the schema titles.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'List all instances of a Kaggle model' with a specific verb and resource, and distinguishes from sibling tools like model_get or model_instance_get by focusing on listing all instances.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like model_instance_get or model_instance_versions, nor any prerequisites or context for usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It implies read-only behavior via 'browse' but does not explicitly state non-destructiveness, authorization needs, or output format. Adequate but not thorough.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
One clear sentence followed by a structured list of arguments. No redundant or filler text; every sentence adds value and is front-loaded with purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers purpose and parameters adequately but lacks context on return format (despite output schema existing), pagination behavior, and comparison with sibling tools. Adequate for a simple read tool with moderate richness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds valuable information beyond the schema: lists allowed values for write_up_type, explains query as optional search filter, and specifies page_size maximum. Since schema descriptions are missing (0% coverage), this compensates well.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Browse Kaggle write-ups by type,' which specifies the action (browse) and the resource (write-ups), and differentiates from sibling tools like discussions_list, discussions_search, etc., by focusing on write-ups organized by type.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives such as discussions_list or discussions_solutions. The description only explains what the tool does without contextual comparison.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description only mentions 'Upload' without detailing side effects, authentication requirements, rate limits, or other behavioral traits. It does not sufficiently compensate for the lack 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short and front-loaded, with two sentences and an Args section. No extraneous information is present.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has a simple interface with two parameters and an output schema, but the description omits details like file size limits, supported file types, and the format of the returned token, which are necessary for full completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description adds meaning by providing examples for file_name ('data.csv', 'config.json') and clarifying that content is 'File content as text', which goes beyond the schema's type specifications.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Upload a file to Kaggle and get a token for dataset_create', specifying the verb, resource, and purpose. It distinguishes this tool from siblings, which include various dataset operations but no direct file upload.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage as a preliminary step for dataset_create, but it does not explicitly state when to use it versus alternatives, nor does it provide conditions or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It explains update behavior and how to preserve existing values via empty strings or None. However, it omits permissions, idempotency, and response details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the main purpose and then provides a clear bulleted list of parameters. While the Args section is somewhat lengthy, it is necessary given the lack of schema descriptions.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers all parameters and their usage, but does not address error conditions, preconditions (e.g., model existence), or return value. The presence of an output schema reduces the need for return value explanation, so completeness is adequate but not exceptional.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description fully explains each parameter: owner and model_slug are required, title/subtitle/description can be left empty to keep unchanged, is_private can be None to keep existing. This adds value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description starts with 'Update an existing Kaggle model,' clearly stating the primary action and resource. This distinguishes it from sibling tools like model_create, model_delete, and model_get.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives. It does not mention prerequisites (e.g., ownership) or scenarios where other tools would be more appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description implies a read operation but does not explicitly state side effects, permissions, or rate limits. With no annotations, more transparency would be beneficial, but the purpose is adequately conveyed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short and front-loaded with the core purpose. It could be slightly more structured (e.g., separating parameter docs), but there is no waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter) and the presence of an output schema, the description is mostly complete. It lacks behavioral details but is sufficient for basic usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter 'competition' lacks description in the schema (0% coverage). The description adds 'Competition URL suffix (e.g. 'titanic')', which provides needed context beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Get data files summary for a competition' with a clear verb and resource, and includes an example for the competition parameter. This distinguishes it from sibling tools like competition_files or competition_download.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given on when to use this tool versus alternatives. Given the many competition-related sibling tools, explicit usage context would help an agent choose correctly.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must convey behavioral traits. It indicates a read operation ('Get'), which is non-destructive, but does not detail potential permissions needed, rate limits, or whether the returned info is fully comprehensive. For a simple retrieval, it is adequate but lacks depth.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: one sentence stating the core action followed by a compact argument list. Every sentence is necessary and front-loaded. There is no extraneous information, making it easy for an agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that an output schema exists, the description does not need to detail return values. It covers both required parameters with meaningful explanations. However, it could mention that the dataset must exist or handle potential error scenarios. Overall, it is sufficient for a straightforward retrieval tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage (only titles), so the description's argument documentation adds significant value. It explains that 'owner' is the dataset owner username and 'dataset_slug' is the dataset slug name, clarifying their semantic roles beyond the schema's generic titles. This helps the agent construct correct invocations.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get full dataset info.' with a specific verb and resource. Among siblings like dataset_create, dataset_delete, and dataset_download, this tool is uniquely positioned as a retrieval operation. The word 'full' suggests comprehensive information, distinguishing it from potentially partial fetches like dataset_metadata.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool vs. alternatives such as dataset_metadata or datasets_list. It does not specify prerequisites, when not to use it, or any context for selecting this over similar tools. The agent must infer usage solely from the tool name and basic purpose.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose behavioral traits such as read-only nature, authentication requirements, rate limits, or side effects. The description is minimal in this regard.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured with a clear docstring format including Args. Every sentence is purposeful and there is no unnecessary content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has only 2 parameters, no nested objects, and an output schema exists, the description is adequate. It explains the parameters well, though it does not describe the return format (but output schema covers that).
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds value beyond the input schema by explaining the purpose of the 'competition' parameter (narrow search, recommended for accuracy). Schema coverage is 0%, so the description compensates well.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get discussion content by ID', which is a specific verb and resource. It distinguishes from sibling tools like discussion_comments and discussions_list by focusing on getting content by ID.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit when-to-use or when-not-to-use guidance. The description recommends using a competition slug for accuracy, but does not differentiate from sibling tools like discussion_comments or discussions_search.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description adequately indicates a read operation ('View submission history'). However, it does not disclose potential side effects, authentication requirements, or limits (e.g., pagination).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: one line for purpose and one docstring line for the parameter. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While the tool is simple and an output schema exists, the description does not mention whether results are paginated, ordered, or if authentication is needed. It is minimally adequate for a basic list view.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter 'competition' is described as 'Competition URL suffix' in the docstring, adding clarity beyond the bare schema (which has no description). Schema coverage is 0%, but the tool description compensates well for this single required param.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states 'View submission history for a competition,' providing a clear verb (View) and resource (submission history). This distinguishes it from sibling tools like competition_get_submission (single submission) and competition_submit.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives the basic purpose but does not explicitly guide when to use this tool versus alternatives like competition_get_submission or competition_submit. No 'when not to use' 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.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description bears full burden. It states 'Search' and lists parameters, but lacks behavioral details like request limits, response size, or effect on data. Adequate but 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is concise with a clear title and parameter list. Every sentence is useful, though it could be slightly more structured (e.g., separating Args from description).
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a search tool with 4 parameters and an output schema, the description covers parameter semantics well. It does not describe return format, but output schema exists. Adequate for complexity level.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so description compensates by explaining each parameter's meaning, including valid values for sort_by and source_type, and page_size max. Adds significant value beyond bare schema names.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Search Kaggle discussions' with a specific verb and resource. Among siblings like discussions_list and discussion_detail, this tool is distinct for search functionality.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains parameters but does not provide explicit guidance on when to use this tool versus alternatives like discussions_list or discussions_by_source. It implies usage via search but lacks when-not or exclusion criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries burden. Lists parameters but lacks behavioral details like authentication needs, rate limits, or return structure. The presence of an output schema reduces burden slightly, but still insufficient for full transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise: a short paragraph with clear bullet-point style. Every sentence adds information without redundancy. Front-loaded with purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Coverage is good for a list tool with 4 parameters and an output schema. However, no guidance on pagination or filtering behavior beyond individual parameters, which could be expanded.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0% (no schema descriptions), so description must compensate. Provides meaning for all 4 parameters, including sort_by options (hotness, downloadCount, etc.). Adds value beyond schema, though could be more detailed for page_size.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states 'Search and list Kaggle models.' The verb 'list' and resource 'models' are specific, and it distinguishes from siblings like model_get or model_create which focus on single models or creation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Describes parameters but does not explicitly state when to use this tool instead of alternatives. Siblings like model_get for single model or datasets_list for datasets are not mentioned, leaving the agent to infer usage from context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full transparency burden. It discloses key behaviors: since_hours 'fetches up to 100 results and filters client-side' and new_only toggles between createTime/updateTime filtering. However, it does not mention pagination beyond page_size, or what happens when both competition and dataset are empty.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a clear first sentence and a bulleted argument list. It is concise (~90 words) without fluff. Minor overhead from the 'Args:' section, but it aids readability.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 5 parameters (none required) and an output schema (not shown), the description lacks context on default behavior when no filters are applied (e.g., lists all discussions?). It explains since_hours and new_only well, but omits ordering, total count, or pagination details beyond page_size.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 0% description coverage, so the description fully compensates. It explains the meaning of each parameter: competition slug, dataset ref, page_size max 50, since_hours client-side filtering, and new_only logic (createTime vs updateTime). This adds significant value beyond the raw schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description begins with a clear verb+resource: 'List discussions for a competition or dataset.' This distinguishes it from sibling tools like discussion_detail (single discussion) or discussions_search (search-based).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The parameter descriptions imply usage (e.g., filtering by time or new_only), but there is no explicit guidance on when to use this tool versus alternatives, nor any when-not-to-use advice. Usage context is roughly 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.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries burden. It mentions prerequisite file_upload but doesn't disclose side effects, success/failure behavior, or rate limits. Adequate but not thorough.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Purpose is front-loaded. Args list is structured but slightly verbose. Could be more concise, but overall clear and organized.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers main behavior and all parameters. Does not describe return values or errors, but output schema may cover that. With 6 parameters and no nested objects, description is fairly complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, but description explains each parameter: owner, slug, title, file_tokens (comma-separated from file_upload), license_name (with examples), is_private (boolean). Adds significant meaning beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Create a new dataset' clearly, specifying the action and resource. It also differentiates from sibling tools like dataset_create_version by mentioning file_upload and file tokens.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says 'Use file_upload first to get file tokens,' guiding when to use this tool. No explicit exclusions for alternatives, but sibling list implies distinction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. The description discloses important behavioral details: the API does not return scores for active competitions, and scores shown are extracted from notebook titles. This informs the user about potential missing data.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise: a clear one-line purpose followed by a succinct numbered list of parameters. No wasted words, front-loaded with the key action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool complexity, parameter count, and lack of annotations/output schema details, the description covers the purpose, parameters, and a key behavioral nuance (missing scores for active competitions). It is complete for a list-oriented tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Adds significant meaning beyond the schema: explains competition as 'Competition URL suffix' with example, lists all possible sort_by values, and gives page_size with max limit. With 0% schema coverage, the description fully compensates.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists top public kernels for a competition sorted by public score, distinguishing it from sibling tools like competition_leaderboard or kernels_list.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides some usage context by noting that the API doesn't return score values for active competitions but still sorts by score. However, it does not explicitly compare to alternatives like competition_leaderboard or kernels_list.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses that the tool returns a download URL, implying no side effects. Without annotations, it adequately covers the main behavioral trait (non-destructive). Could mention authentication or rate limits, but not necessary for a simple download.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise: two sentences plus a parameter description. No redundant information; front-loaded with the key action and return value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, output schema present), the description is fully adequate: it states the purpose, argument, and return value. No missing context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Adds meaning with 'Competition URL suffix (e.g. 'titanic')', which clarifies the parameter format beyond the schema's minimal type/string definition.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the verb 'download' and resource 'full competition leaderboard', and specifies the return value 'download URL'. This distinguishes it from siblings like 'competition_leaderboard' (which likely just displays the leaderboard).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Implicitly indicates to use when needing to download the leaderboard. Does not explicitly mention alternatives or when not to use, but the context of sibling names provides sufficient differentiation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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