The server defines 10 tools with schemas visible in src/index.ts using Zod validation. However, critical gaps severely impact quality: (1) Tool descriptions lack strategic context, they state WHAT but not WHEN or WHY to use each tool vs. alternatives. Most descriptions are 40 - 80 chars, below the 10 - 1024 baseline and well short of the 194-char average for A+ tools. (2) Parameter descriptions are sparse or generic. For example, 'entry_point' in trace_execution_path has no description explaining what 'line' and 'function_name' do. (3) Output schemas are not documented, LLMs cannot predict what fields to extract or chain to downstream tools. (4) No error recovery guidance. Tools return structured errors (ApiError, SessionError types exist in src/errors/index.ts) but the MCP handlers do not map these to actionable recovery messages. (5) All 10 tools operate on complex, poorly-described nested objects (claude_context, code_scope) with incomplete field documentation. The schema properties exist but lack descriptions for nested fields. For example, 'attempted_approaches' is documented as 'What Claude Code already tried', but 'partial_findings' has no description, the LLM must guess whether this is a list of strings, objects, or raw findings. (6) No enum constraints on repeated choice fields (e.g., analysis_type is an enum, good, but impact_types array in cross_system_impact lacks enum per-item validation in the visible schema). (7) Three tools (start_conversation, continue_conversation, finalize_conversation) manage stateful sessions but lack descriptions of session lifecycle, expiration, or retry semantics. POSITIVE: Schemas ARE present and properly typed with Zod. Naming follows verb_noun convention. Error classes suggest thoughtful error design. But execution gaps and missing descriptions drop the score significantly.

• Expand tool descriptions to 150 - 250 characters. Include: (1) What the tool does, (2) When to use it vs. similar tools (e.g., 'Use escalate_analysis when Claude Code hits reasoning limits; use trace_execution_path to understand execution flow without escalation'), (3) Expected output type (e.g., 'Returns a deep analysis report with identified root causes').
• Add descriptions to ALL nested object fields. For each parameter, document: type (string, array, object), expected content, constraints. Example: 'attempted_approaches (array of strings): List of debugging approaches Claude already tried. Each entry should briefly describe the approach (e.g., "checked variable scope", "traced async callbacks").'
• Document output schemas in the tool definitions. Add a structured 'returns' object to each tool's description or a separate returns schema. Example for escalate_analysis: 'Returns {analysis_id: string, root_cause: string, recommendations: array, confidence: 0 - 1}'.
• Add explicit error documentation to each tool. Include common failure modes and recovery steps. Example: 'On RATE_LIMIT_ERROR (429), retry after the retryAfter duration. On SESSION_NOT_FOUND, call start_conversation to initialize a new session. On ApiError from Gemini, check GEMINI_API_KEY environment variable.'
• Document session lifecycle for conversation tools. Add to start_conversation description: 'Initiates a stateful session lasting up to 1 hour. Sessions are single-threaded (concurrent requests with same session_id will return SESSION_LOCKED). Use continue_conversation to extend; finalize_conversation to close and retrieve final results.'