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Analyzes the sentiment of text using the HuggingFace Inference API with a Spanish sentiment analysis model
Single tool 'analyze_text' has a basic description (47 chars, within 10-1024 range) but lacks critical depth. Input schema is present with proper JSON Schema structure (type, properties, required), but the 'text' parameter has NO description, violating the requirement that every parameter needs a description explaining what it controls. The tool description does not explain WHEN to use it, WHAT it returns, or any prerequisites. No output schema is documented. No error handling guidance. The description is in Spanish ('Analiza profesionalmente...') which may confuse English-speaking LLMs. No parameter constraints (length, format, examples). Tool naming 'analyze_text' is acceptable (verb_noun pattern) but generic, does not distinguish this from other sentiment tools.
Analiza profesionalmente el sentimiento de un texto.
Missing parameter description: 'text' parameter has no description. LLMs cannot infer that this is the input to analyze for sentiment.
No output schema documented. Tool returns TextContent with unstructured text. LLMs cannot plan downstream operations or extract structured sentiment data (label, confidence, etc.).
Tool description lacks context: does not explain WHEN to use it, WHAT it returns, or how to interpret results. Description is in Spanish, potentially confusing English-speaking LLMs.
No error handling guidance. Service catches all exceptions and returns generic 'Error en el análisis: ...' string. LLM cannot determine if error is retryable, user-fixable, or fatal.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | F | 40 | 2026-07-28+ | v2 |
No input validation or constraints. 'text' parameter accepts any string with no length limits, format constraints, or language hints. Empty text returns 'El texto está vacío' but no guidance on minimum length.