Server defines 6 tools with basic schemas and minimal descriptions. All tools have input schemas with type definitions and required fields properly marked. However, descriptions are extremely terse (8-35 chars, well below the 50-200 char baseline for LLM-optimized tools). Parameter descriptions are sparse or missing entirely. No output schema documentation. Error handling exists but lacks recovery guidance. Tools follow a consistent read-only pattern but lack the depth needed for production use.

• Expand tool descriptions to 50-150 chars. Example: 'search: Search the data.gov.au CKAN catalogue by keyword, organization, or tag. Returns matching datasets with metadata. Use this to discover datasets before fetching details with package().'
• Add descriptions to all parameters. Example: 'query (string, required): Search term(s) matching dataset names, descriptions, or tags. E.g. "bushfire", "transport", "health data". Solr syntax not supported in query field, use fq for advanced filters.'
• Document output schemas inline or in a README. Example: 'search() returns {success: bool, result: {count: number, results: [{id, name, title, organization, tags, ...}]}}'. Include which fields are safe to pass to downstream tools.
• Enhance error messages with recovery hints. Example: Instead of 'data.gov.au: not found', return 'Package "xyz" not found. Try search() with a keyword to discover available datasets, or check the organization name with organizations().'
• Add min/max bounds to numeric parameters. Example: 'limit (number, 1-1000, default 100): Maximum results to return. Larger limits may timeout; use pagination (start parameter) for large datasets.'