5 tools with mixed quality. All have descriptions (10-200 chars, mostly adequate), but input schemas are present but lack rigor: parameters have types and descriptions, but many lack enums for constrained values, and output schemas are undocumented. Tool naming follows verb_noun convention (analyze_, check_, optimize_, call_, inspect_) but lacks clarity on scope and side effects. No error handling guidance, no recovery paths, no idempotent/destructive hints. Security concerns: call_mcp_tool accepts arbitrary env vars and tool args as JSON strings, risking injection. Composition is reasonable (each tool has one job), but no pagination, no batch variants, and responses are not documented.

• Add output schemas to all tools. Document the structure of returned objects (e.g., analyze_session returns {tool_calls: {[name]: count}, input_tokens: int, output_tokens: int, waste_estimate: int}). This enables LLM planning and field extraction.
• Validate and sanitize 'args' parameter in call_mcp_tool. Parse JSON strictly, reject unknown keys, and validate against the target tool's schema. Reject 'env' values that contain shell metacharacters or path traversal sequences (../, /etc/).
• Add enums or regex patterns to free-form string parameters. E.g., 'server' in check_mcp_health should accept only configured server names (enum). 'project_dir' should validate it is a valid filesystem path.
• Add error handling guidance to all tool descriptions. E.g., 'If session files not found, check ~/.claude/projects/ exists. If timeout occurs, increase timeout parameter and retry.' Include categorization: retryable vs user-fixable vs fatal.
• Add tool annotations: mark optimize_mcp_config with destructiveHint=true (writes .mcp.json), call_mcp_tool with destructiveHint=true (may invoke side-effect tools), and all read-only tools with readOnlyHint=true.