MegaPad has 5 tools with basic descriptions but critical gaps in schema documentation and parameter clarity. Tool names follow verb_noun convention (megapad_compare, megapad_consult_peer, megapad_council_code_review, megapad_list_models, megapad_status). However, input schemas visible in the source show incomplete parameter documentation. Descriptions range 60-180 chars (within baseline 34-392), but lack actionable context for LLM selection. Parameters like 'models' and 'reviewers' accept arrays but lack enum constraints or format guidance. No output schemas documented. Error handling and recovery guidance absent. Tool composition is reasonable (each does one thing), but parameter design forces LLMs to guess valid model provider IDs.

• Document output schema for each tool. E.g., megapad_compare should return {results: [{model: string, response: string, tokens: {input: number, output: number}}], total_tokens: number}. This enables LLMs to extract and chain results.
• Replace 'e.g. [claude, openai, deepseek]' with an explicit enum constraint in the schema: {type: 'array', items: {enum: ['claude', 'openai', 'deepseek', 'gemini', 'grok']}}. Add to parameter description: 'Valid providers: claude, openai, deepseek, gemini, grok.'
• Add error handling guidance to descriptions. E.g., 'If a model provider is unavailable, returns partial results with available models. If all providers fail, returns error with retry guidance.'
• Expand tool descriptions to clarify selection criteria. E.g., megapad_compare: 'Use when you need responses from ALL available models in parallel. Use megapad_consult_peer for a single model opinion. Use megapad_council_code_review for structured code review.'
• Add parameter constraints to descriptions. E.g., 'prompt (required, 1-10000 chars): The question or code to analyze. system (optional, 1-5000 chars): Custom system instructions to override defaults.'