Server provides 12 tools with basic schemas and descriptions, but quality is inconsistent. All tools have descriptions (10-50 chars, mostly short), and input schemas are present with type definitions. However, descriptions are generic and lack actionable context for LLM selection. Parameter descriptions are sparse or missing entirely. No output schemas documented. Error handling is minimal, most tools return raw JSON without recovery guidance. Tool naming follows verb_noun convention (good), but composition issues exist: execute_command is a security risk without sanitization guidance, and wait_for_threshold/sample_metrics are polling utilities that could be better integrated. No tool annotations (readOnlyHint, etc.) despite all being read-only. Average tool score: 52/100.

• Add output schemas for all 12 tools. Document the structure of returned metrics (e.g., cpu_stats returns {percent: number, cores: number, ...}). This enables LLMs to chain tools and extract specific fields.
• Expand tool descriptions to 80-150 chars with actionable context. Example: 'Get current CPU usage as a percentage and per-core breakdown. Use this for instant snapshots; use sample_metrics() for time-series data. Requires no special permissions.'
• Add readOnlyHint: true annotation to all 12 tools. This signals to LLMs that these calls are safe to retry and have no side effects.
• Document execute_command security constraints explicitly: 'WARNING: Sanitize all user input before passing to args. Do not pass unsanitized shell commands. Use args array, not shell string concatenation. Timeout: 15s, max output: 4MB.'
• Add parameter descriptions to all tools. Example for process_list: 'limit: Maximum number of processes to return (1-1000, default 20). Larger limits may timeout on systems with many processes.'