tool-selection

## Tool Selection Rubric When evaluating tool selection in agent traces: ### 1. MCP Over Bash If a Databricks MCP tool exists for the operation, the agent MUST use it: - SQL queries → `mcp__databricks__execute_sql` (not `Bash` + `databricks sql`) - File uploads → `mcp__databricks__upload_to_volume` (not `Bash` + `databricks fs cp`) - Job management → `mcp__databricks__create_job`, `mcp__databricks__run_job` (not REST API via curl) - Cluster ops → `mcp__databricks__create_cluster` (not CLI via Bash) - Workspace files → `mcp__databricks__workspace_get_object` (not Bash + `databricks workspace export`) ### 2. Correct Tool for Task - SQL execution → `execute_sql` (not notebook execution) - Reading docs → `Read` tool (not fetching via curl) - File creation → `Write` tool for local, volume upload for remote - Schema inspection → `execute_sql` with `DESCRIBE` or `SHOW` (not `list_tables` for column details) ### 3. No Shell Workarounds The following patterns indicate incorrect tool selection: - `Bash('databricks ...')` when an MCP tool exists - `Bash('curl ...')` for Databricks REST APIs when MCP tools cover it - `Bash('python -c ...')` for operations that have dedicated tools - Multiple Bash calls that could be one MCP call ### 4. Reasonable Call Count - Simple queries: 1-3 tool calls expected - Multi-step tasks: count should be proportional to steps - Excessive retries suggest the agent is confused, not efficient - Reading the same file multiple times is wasteful ### 5. Error Recovery - On tool failure, the agent should try an alternative approach - Should NOT blindly retry the same failing call - Should report unrecoverable errors to the user See [MCP tool guide](references/MCP_TOOL_GUIDE.md) for the full tool catalog.