Six tools with basic definitions but significant quality gaps. All tools have descriptions (10-100 chars, mostly under 50), but descriptions lack actionable context for LLM selection. Parameters are minimally documented, most lack type constraints, enums, or format guidance. No output schemas documented. Tool names are descriptive but lack action verbs (e.g., 'swahili_english_glossary' vs 'search_swahili_glossary'). All tools are read-only and demo-only, limiting real-world utility. Error handling is absent, no recovery guidance or validation feedback.

• Rename tools with action verbs: 'search_swahili_glossary', 'get_kikuyu_guide', 'lookup_document_terms', 'detect_language', 'search_civic_terms'. This helps LLMs infer intent from the name alone.
• Expand parameter descriptions to 50 - 150 chars with format and constraint guidance. E.g., 'term (string, 1 - 50 chars): Swahili or English word to search. Returns exact and partial matches. Leave empty to list all ~30 terms in the civic glossary.'
• Document output schemas explicitly. E.g., 'Returns {source: string, term: string, swahili_to_english: string|null, english_to_swahili: string|null, note: string}'. This enables LLMs to plan downstream extraction.
• Add error handling and recovery guidance. E.g., 'If term not found, returns {matches: {}} with a note suggesting related terms or a full glossary lookup. LLM should offer alternatives or ask for clarification.'
• Replace 'DEMO' static data with real API integration or document the demo scope clearly. If this is intentionally a demo, state 'This tool returns hardcoded demo data for 6 Swahili terms and 10 Kenya documents. For production use, integrate with a real translation API or database.'