minor fixes

Author: pranav_a

skills/tinyml-agentic-skill/references/skill_setup_guide.md

@@ -30,9 +30,8 @@ If `success: false`, show the user the `errors` and `hint` fields and ask them t
 **Setup repo and environment for working**
 
 Once the repository is installed and the installation is verified, also verify if the repository has been set-up with a virtual environment and is ready for use. 
-First check to find a virtual environment which may be present at the root level of the tinyml-tensorlab repository (installed at `$TINYML_BASE_PATH`).
-Try `source .venv/bin/activate` or `source venv/bin/activate`.
-Then try running the following script:
+
+Try running the following script:
 ```python
 
    import tinyml_modelmaker
@@ -99,4 +98,6 @@ ls $TINYML_TENSORLAB_DOCS_PATH/getting_started/ 2>/dev/null | head -3
 ```
 If this returns no output or an error, the path is wrong. Correct value is `$TINYML_BASE_PATH/docs/source/`. Fix it before writing to `.env`.
 
-**ALWAYS CREATE A LOCAL `.env` FILE WITH ALL OF THE ABOVE 4 ENV VARIABLES**
+**ALWAYS CREATE A LOCAL `.env` FILE WITH ALL OF THE ABOVE 4 ENV VARIABLES**
+
+After the `tinyml-tensorlab` repository is fully set up, index the repository and ensure you understand it fully. You must be able to retrieve relevant context whenever necessary going forward.

skills/tinyml-agentic-skill/scripts/dataset_format_tools.py

@@ -519,7 +519,6 @@ def _check_regression(path: str, is_zip: bool) -> Tuple[List[str], List[str], bo
             warnings.append(
                 "No annotations/ directory found. "
                 "ModelMaker will auto-generate train/val splits using split_factor from config. "
-                "Call reorganize_dataset to generate annotation files explicitly."
             )
         else:
             if not os.path.exists(os.path.join(ann_dir, "instances_train_list.txt")):
@@ -541,9 +540,7 @@ def validate_dataset_format(
     format for the given task_type.
 
     Call this tool immediately after the user provides input_data_path, BEFORE
-    generating the dataset config section. If validation fails (is_valid=False),
-    call reorganize_dataset to fix the layout, then continue with config generation
-    using the new_input_data_path returned by reorganize_dataset.
+    generating the dataset config section.
 
     Supported input: local directory path or local .zip file.
     Remote URLs cannot be validated — skip validation and proceed with config generation.
@@ -562,7 +559,6 @@ def validate_dataset_format(
           — ALWAYS show this to the user when validation fails
         - issues: list of errors blocking correct data loading
         - warnings: list of non-fatal issues (ModelMaker may still work)
-        - can_auto_reorganize: True if reorganize_dataset can fix all issues automatically
         - reorganize_hints: instructions for the user if can_auto_reorganize is False
           (e.g., which parameters to provide to reorganize_dataset)
         - success: True if the validation check itself completed without internal errors
@@ -574,7 +570,6 @@ def validate_dataset_format(
             "expected_structure": _EXPECTED_STRUCTURES[_get_task_family(task_type)],
             "issues": [],
             "warnings": ["Remote URL provided — format validation skipped. Ensure dataset matches expected structure."],
-            "can_auto_reorganize": False,
             "reorganize_hints": "Download the dataset locally to run format validation.",
             "success": True,
         }
@@ -586,7 +581,6 @@ def validate_dataset_format(
             "expected_structure": _EXPECTED_STRUCTURES[_get_task_family(task_type)],
             "issues": [f"Path does not exist: {input_data_path}"],
             "warnings": [],
-            "can_auto_reorganize": False,
             "reorganize_hints": "Verify the path and try again.",
             "success": True,
         }
@@ -608,7 +602,6 @@ def validate_dataset_format(
             "expected_structure": _EXPECTED_STRUCTURES[family],
             "issues": [f"Validation failed with internal error: {e}"],
             "warnings": [],
-            "can_auto_reorganize": False,
             "reorganize_hints": "",
             "success": False,
         }
@@ -619,7 +612,6 @@ def validate_dataset_format(
         "expected_structure": _EXPECTED_STRUCTURES[family],
         "issues": errors,
         "warnings": warnings,
-        "can_auto_reorganize": can_fix if errors else True,
         "reorganize_hints": hints if errors else "",
         "success": True,
     }

skills/tinyml-agentic-skill/scripts/dataset_section_tools.py

@@ -156,10 +156,8 @@ def validate_dataset_section(
                 "effective_input_data_path": None,
                 "format_validation": format_validation,
                 "errors": [
-                    "Dataset format is incorrect. "
-                    "Show the user the expected_structure and issues from format_validation, "
-                    "then gather the required parameters described in reorganize_hints and "
-                    "call reorganize_dataset_stage_1."
+                    "Dataset format is incorrect."
+                    "Show the user the expected_structure and issues from format_validation."
                 ],
                 "warnings": [],
             }