LEA provides 15 tools with explicit JSON Schema definitions in agentflow/tools.py. All tools have names starting with action verbs (list_, read_, write_, edit_, grep, glob, run_, git_, save_, finish, echo, sleep) and descriptions. However, many parameter descriptions are minimal or missing entirely. For example, 'list_dir' lacks a description for its 'path' parameter beyond 'Relative directory. Default \'.\''. The 'save_skill' tool has good parameter documentation, but tools like 'grep' and 'glob_files' have sparse descriptions. Output schemas are not documented, LLMs cannot infer what fields to expect from responses. Error handling is minimal; no recovery guidance or actionable error messages are evident. The 'run_shell' tool is high-risk (IRREVERSIBLE) but lacks warnings or dry-run capability. Overall, definitions are functional but lack the depth and LLM-optimization expected of production tools.

• Document output schemas for all tools. E.g., 'list_dir returns {files: [string], dirs: [string], total: int}' so LLMs know what to extract.
• Add dry-run or confirmation step to run_shell. E.g., 'dry_run: bool' parameter that shows the command without executing, or require explicit confirmation for destructive patterns (rm, delete, drop).
• Expand parameter descriptions with format constraints and examples. E.g., 'glob: filename glob pattern (e.g., *.py, src/**/*.ts), supports * and ** wildcards'.
• Add error recovery guidance to tool descriptions. E.g., 'If file not found, call list_dir() to verify the path exists.' or 'Returns error code 404 if path does not exist, check workspace structure.'
• Clarify finish() semantics. Document what blocking_issues and followups mean, how they affect task completion, and whether they trigger downstream actions.