Both tools have clear, descriptive descriptions (194-200 chars, within baseline 34-392 range) and explicit input schemas with typed parameters. However, critical gaps prevent higher scoring: (1) Parameter descriptions are minimal, 'prompt' is described as 'A complete, self-contained instruction for Claude' but lacks guidance on format, length, or constraints. (2) No output schema is documented; callers cannot predict the structure of the response (ok/text fields are inferred from code, not declared). (3) No error handling guidance, when Claude fails, the tool returns {ok: false, text: '...'} but the description does not explain recovery steps or error categories. (4) Tool names lack verb-noun clarity: 'ask_claude' and 'ask_claude_write' are somewhat clear but do not follow the canonical verb_noun pattern (e.g., 'query_claude_read', 'query_claude_write' would be more consistent). (5) No mention of idempotency, side effects, or prerequisites. The tools are functional but fall short of production-grade documentation.

• Document the output schema explicitly: {type: 'object', properties: {ok: {type: 'boolean'}, text: {type: 'string'}}, required: ['ok', 'text']}. Include in tool description or as a separate schema field.
• Add constraints to 'prompt' parameter: max length (e.g., 10000 chars), required format (e.g., 'plain text, no binary'), and examples of well-formed prompts.
• Categorize errors in responses: return {ok: false, error_type: 'timeout'|'invalid_input'|'claude_error', text: '...', retry_after_seconds: N} to guide LLM recovery.
• Add a dry-run or confirmation step for 'ask_claude_write': require a separate 'confirm' parameter or return {ok: false, requires_confirmation: true, changes: [...]} before executing file edits.
• Rename tools to follow verb_noun pattern: 'query_claude_readonly' and 'query_claude_write', or 'ask_claude_read' and 'ask_claude_write' with explicit 'read' vs 'write' distinction in names.