Single tool 'execute_skill_action' has a minimal description (97 chars) that lacks actionable context for LLM selection. Parameter 'query_payload' is a generic string with no format guidance, constraints, or examples of valid payloads. No output schema is documented, the tool returns a hardcoded JSON string with 'status' and 'message' fields, but this structure is not declared in the tool definition. No error handling guidance, no parameter validation rules, and no indication of what 'deterministic, zero-dependency' operations are actually supported. The tool name 'execute_skill_action' is vague (what skill? what action?) and does not follow verb_noun convention clearly. No evidence of idempotency, pagination, or composition with other tools.

• Rename tool to a specific verb_noun pattern: e.g., 'search_terminal_history', 'suggest_cli_command', or 'analyze_shell_session', something that clearly conveys the operation.
• Expand parameter 'query_payload' into explicit, typed fields: e.g., 'natural_language_query' (string, 10-500 chars), 'session_shell' (enum: bash|zsh|fish|powershell), 'max_results' (integer, 1-100, default 10). Add descriptions for each.
• Document the output schema explicitly in the tool definition. Include fields like 'search_id', 'suggested_cli_command', 'relevance_score', 'execution_safety_grade', and their types. This enables LLMs to chain calls and extract data.
• Rewrite tool description to be 50-200 chars and answer: 'Search terminal session history using natural language queries. Returns suggested CLI commands with safety grades and relevance scores. Use this to find previously-executed commands matching a user intent.'
• Add error handling guidance: document what happens if the query is malformed, if no matching commands are found, or if the session shell is unsupported. Return structured errors with recovery hints, e.g., 'No commands found for query. Try a simpler query or specify a different shell.'