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1 | | -You are setting up altimate-code for a data engineering project. Guide the user through environment detection and warehouse connection setup. |
| 1 | +Please analyze this codebase and create an AGENTS.md file containing: |
| 2 | +1. Build/lint/test commands - especially for running a single test |
| 3 | +2. Code style guidelines including imports, formatting, types, naming conventions, error handling, etc. |
2 | 4 |
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3 | | -Step 1 — Scan the environment: |
4 | | -Call the `project_scan` tool to detect the full data engineering environment. Present the results clearly to the user. |
| 5 | +The file you create will be given to agentic coding agents (such as yourself) that operate in this repository. Make it about 150 lines long. |
| 6 | +If there are Cursor rules (in .cursor/rules/ or .cursorrules) or Copilot rules (in .github/copilot-instructions.md), make sure to include them. |
5 | 7 |
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6 | | -Step 2 — Review what was found: |
7 | | -Summarize the scan results in a friendly way: |
8 | | -- Git repository details |
9 | | -- dbt project (name, profile, model/source/test counts) |
10 | | -- Warehouse connections already configured |
11 | | -- New connections discovered from dbt profiles, Docker containers, and environment variables |
12 | | -- Schema cache status (which warehouses are indexed) |
13 | | -- Installed data tools (dbt, sqlfluff, etc.) |
14 | | -- Configuration files found |
15 | | - |
16 | | -Step 3 — Set up new connections: |
17 | | -For each NEW warehouse connection discovered (not already configured): |
18 | | -- Present the connection details and ask the user if they want to add it |
19 | | -- If yes, call `warehouse_add` with the detected configuration |
20 | | -- Then call `warehouse_test` to verify connectivity |
21 | | -- Report whether the connection succeeded or failed |
22 | | -- If it failed, offer to let the user correct the configuration |
23 | | - |
24 | | -Skip this step if there are no new connections to add. |
25 | | - |
26 | | -Step 4 — Index schemas: |
27 | | -If any warehouses are connected but not yet indexed in the schema cache: |
28 | | -- Ask the user if they want to index schemas now (explain this enables autocomplete, search, and context-aware analysis) |
29 | | -- If yes, call `schema_index` for each selected warehouse |
30 | | -- Report the number of schemas, tables, and columns indexed |
31 | | - |
32 | | -Skip this step if all connected warehouses are already indexed or if no warehouses are connected. |
33 | | - |
34 | | -Step 5 — Show next steps: |
35 | | -Present a summary of what was set up, then suggest what the user can do next: |
36 | | - |
37 | | -**Available skills:** |
38 | | -- `/cost-report` — Analyze warehouse spending and find optimization opportunities |
39 | | -- `/dbt-docs` — Generate or improve dbt model documentation |
40 | | -- `/generate-tests` — Auto-generate dbt tests for your models |
41 | | -- `/sql-review` — Review SQL for correctness, performance, and best practices |
42 | | -- `/migrate-sql` — Translate SQL between warehouse dialects |
43 | | - |
44 | | -**Agent modes to explore:** |
45 | | -- `analyst` — Deep-dive into data quality, lineage, and schema questions |
46 | | -- `builder` — Generate SQL, dbt models, and data pipelines |
47 | | -- `validator` — Validate SQL correctness and catch issues before they hit production |
48 | | -- `migrator` — Plan and execute warehouse migrations |
49 | | - |
50 | | -**Useful commands:** |
51 | | -- `warehouse_list` — See all configured connections |
52 | | -- `schema_search` — Find tables and columns across warehouses |
53 | | -- `sql_execute` — Run queries against any connected warehouse |
| 8 | +If there's already an AGENTS.md, improve it if it's located in ${path} |
54 | 9 |
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55 | 10 | $ARGUMENTS |
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