input-file-skill

name	input_file_skill
description	Parse, modify, validate, and patch simulator input files. Use when working with reservoir simulation input files, testing scenarios, or validating simulation configurations. This implementation supports reference format (.DATA); other simulators use different extensions (e.g., .afi, .DAT). Supports natural language modifications, keyword patching, and syntax validation.
license	Apache-2.0
metadata	{"author":"sim-agent","version":"1.0","category":"simulator"}
compatibility	Requires simulator tools and Python environment with langchain, pydantic, and nvidia-ai-endpoints packages

DATA File Processing Skill

This skill provides tools for working with simulator input files. The reference format uses .DATA as the primary input extension; other simulators use different extensions.

Overview

The DATA File Processing skill enables agents to:

• Parse simulator input files to understand their structure and sections
• Modify simulator input files using natural language instructions
• Validate simulator input files for syntax and consistency
• Patch specific keyword blocks without rewriting entire files

Tools

parse_simulation_input_file

Parses a simulator input file and returns its structure (sections found). Reference format uses .DATA extension.

Usage:

parse_simulation_input_file(file_path: str) -> str

Example:

parse_simulation_input_file("data/example_cases/SPE10/CASE/SPE10_TOPLAYER.DATA")

Returns: A string listing all sections found (e.g., "Sections found: HEADER, RUNSPEC, GRID, PROPS, SOLUTION, SUMMARY, SCHEDULE")

When to use: First step in scenario testing chain (TOOL_DECISION_TREE.md Section 2.4) or when user asks to parse/list sections of a simulator input file.

modify_simulation_input_file

Modifies a simulator input file based on natural language instructions. Can modify entire file or target specific keyword blocks.

Usage:

modify_simulation_input_file(
    file_path: str,
    modifications: str,
    output_path: Optional[str] = None,
    llm_model: Optional[str] = None,
    manual_context: Optional[str] = None,
    example_context: Optional[str] = None,
    target_keyword: Optional[str] = None
) -> str

Parameters:

• file_path: Path to the simulator input file to modify
• modifications: Natural language description of changes (e.g., "Increase water injection rate for well I1 to 55")
• output_path: Where to save modified file (default: overwrite original)
• llm_model: Optional model override for LLM-based modifications
• manual_context: Optional simulator manual excerpt for the relevant keyword
• example_context: Optional example DATA snippets for the relevant keyword
• target_keyword: If set, only this keyword block is edited; rest of file is copied unchanged

Example:

modify_simulation_input_file(
    file_path="SPE1CASE1.DATA",
    modifications="Increase water injection rate for well I1 in WCONINJE to 55",
    output_path="SPE1CASE1_AGENT_GENERATED.DATA",
    target_keyword="WCONINJE"
)

When to use: In scenario test chain (Section 2.4) after parse_simulation_input_file → simulator_manual → simulator_examples, or when user requests modifications to a simulator input file.

patch_simulation_input_keyword

Patches a specific keyword block in a simulator input file without modifying other parts. Useful for auto-fixes.

Usage:

patch_simulation_input_keyword(
    file_path: str,
    keyword: str,
    output_path: str,
    item_index: Optional[int] = None,
    new_value: Optional[str] = None,
    new_block_content: Optional[str] = None
) -> str

Parameters:

• file_path: Path to the simulator input file
• keyword: Keyword to patch (e.g., WELLDIMS, TABDIMS)
• output_path: Path for the new file (original is unchanged)
• item_index: 1-based index of the numeric item to replace
• new_value: New value for the item (used with item_index)
• new_block_content: Exact new block content (keyword line + data). If set, item_index/new_value are ignored.

Example:

patch_simulation_input_keyword(
    file_path="SPE1CASE1.DATA",
    keyword="WELLDIMS",
    output_path="SPE1CASE1_FIXED.DATA",
    item_index=1,
    new_value="10"
)

When to use: In HITL apply fix flow (Section 2.2) for auto-fixes, or when only a specific keyword needs to be changed.

Workflow Integration

This skill integrates with the Simulator Agent's decision tree (TOOL_DECISION_TREE.md):

1. Scenario Test Chain (Section 2.4):

   parse_simulation_input_file → simulator_manual → simulator_examples → modify_simulation_input_file → run_and_heal
   

2. HITL Apply Fix (Section 2.2):

   patch_simulation_input_keyword or modify_simulation_input_file → run_and_heal
   

Implementation Details

Tools are implemented as LangChain tools with Pydantic input schemas. The skill uses:

• utils.py: Shared utility functions for parsing, keyword finding, and LLM integration
• Tool modules: Individual tool implementations in separate modules
• LLM integration: Uses ChatOpenAI for natural language modifications

Error Handling

All tools return descriptive error messages if:

• Files are not found
• Syntax errors occur during parsing
• LLM modifications fail
• Validation checks fail

References

• OPM Flow Manual - Detailed keyword reference
• Tool Decision Tree - Routing logic
• Examples - Usage examples

Testing

Run the test suite:

python -m simulator_agent.skills.input_file_skill.test --file path/to/test.DATA

Or test individual tools:

python -m simulator_agent.skills.input_file_skill.test --file path/to/test.DATA --tool parse_simulation_input_file

The test script is located in test.py at the root of the skill directory.