AITree exposes 4 well-named, read-only tools with clear descriptions and complete input schemas. Tool names follow verb_noun convention (aitree_get_tree, aitree_read_file, aitree_get_stats, aitree_get_changed). Descriptions are detailed (150 - 250 chars) and explain WHAT, WHEN, and prerequisites. All parameters have type annotations and descriptions. However, output schemas are not formally documented, responses are returned as strings (JSON-serialized or plain text) without explicit schema declarations. Error handling is present but minimal; some errors return JSON objects while others return plain strings, creating inconsistency. Security is strong (path traversal checks, no secrets in params). Composition is clean, each tool has one responsibility. Missing: pagination guidance, structured output schema documentation, and actionable error recovery hints.

• Document output schemas explicitly in tool descriptions. E.g., 'Returns JSON with fields: files (array of {path, size, type}), total_files (int), total_size (int), token_count (int, if tokens=true).'
• Standardize error responses to always return JSON with {error: string, suggestion?: string, retryable?: boolean}. Add recovery hints: 'Path not found. Verify the path exists or call aitree_get_tree with a parent directory.'
• Add a 'max_depth' or 'max_results' parameter to aitree_get_tree and aitree_get_stats with documented defaults (e.g., depth=10, max_files=1000) to prevent unbounded output.
• Validate gitpython availability in aitree_get_changed before execution. Return a clear error: 'gitpython not installed. Run: pip install paracci-aitree[git]' if missing.
• Add tool annotations (readOnlyHint=true) to all four tools to signal to MCP clients that these are safe, non-destructive operations.