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Single tool with moderate naming and minimal documentation. Tool is explicitly registered with schema in server.py, but descriptions are generic and parameter documentation is sparse. No error handling guidance, no output schema documentation, no security considerations addressed. Input schema present but lacks constraints and detailed parameter descriptions.
Download and extract a Kaggle dataset.
Tool description is generic and lacks action context. 'Download and extract a Kaggle dataset.' does not explain when to use this tool, what prerequisites exist (Kaggle API credentials), or what the return value structure is. LLMs cannot determine selection priority.
Parameter 'competition_id' lacks detailed description. Current description 'The Name of the Kaggle competition to download the dataset from.' is minimal (77 chars). Should specify format, examples, and how to find valid competition IDs. Does not mention that case sensitivity or exact naming rules.
No output schema documented. Tool returns TextContent with generic success message, but LLMs cannot see expected response structure. Should document: what fields are in the response, data types, and what subsequent tools can expect.
Inferred effective spec: <=2025-11-25.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-22 | F | 39 | <=2025-11-25 | v2 |
| 2026-03-09 | F | 28 | - | v1 |
No error handling or recovery guidance. Tool can fail in multiple ways: invalid competition_id, missing Kaggle credentials, API rate limits, network errors, extraction failures. Current code raises generic exceptions with no guidance for LLM on what to do next (retry, ask user for credentials, etc.).
No input validation or constraints. Parameter 'competition_id' accepts any string with no enum, pattern, or length constraints. Code validates presence but not format. LLMs can pass invalid IDs, leading to API errors without guidance.
Tool modifies state (downloads files, creates directories) but description does not indicate this is a destructive/irreversible operation. Missing destructive hint annotation. Agents should know this has side effects and is not idempotent without safeguards.
Kaggle API credentials required but not documented in tool description. Users/agents need to know to set up kaggle.json or KAGGLE_CONFIG_DIR before calling this tool. Current code will silently fail during authenticate_kaggle_api() with a PermissionError but tool description gives no hint.
No pagination or result limiting. If a competition has large datasets, extraction and storage could be unbounded. Tool description should state expected output size or warn about disk space requirements.