environment-discovery

Solid

Systematic exploration of unknown environments before starting work

AI & Automation 859 stars 98 forks Updated yesterday MIT

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Quality Score: 93/100

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100
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Issue Health 10%
50
License 10%
100
Description 5%
100

Skill Content

# Environment Discovery When dropped into an unfamiliar environment, ALWAYS explore before acting. ## Step 1: Understand the workspace ``` ls -la /app/ # or the working directory find . -type f | head -50 ``` - What files exist? What are their sizes? - Are there READMEs, Makefiles, config files? - What languages/frameworks are involved? ## Step 2: Inspect data files Before writing any code that reads data, understand the format: - `file <filename>` — detect file type (binary, text, encoding) - `head -20 <file>` — first lines of text files - `xxd <file> | head -20` — hex dump for binary files - `wc -l <file>` — line count for text files - `stat <file>` — exact file size in bytes - `python3 -c "import struct; ..."` — parse binary headers ## Step 3: Check available tools ``` which python3 gcc g++ make cmake node npm cargo rustc java go pip list 2>/dev/null | head -20 ``` - What compilers/interpreters are installed? - What libraries are available? - What package managers can you use? ## Step 4: Read existing code If there are existing source files: - Read them FULLY before modifying - Understand the build system (Makefile, CMakeLists.txt, pyproject.toml) - Check for existing tests ## Key Principles - NEVER assume file formats — always inspect first - NEVER assume tools are installed — always check - A 500MB file is NOT a "small file" — plan for it - Binary files need byte-level inspection, not `cat` - Spend 30 seconds exploring to save 5 minutes debugging

Details

Author
vstorm-co
Repository
vstorm-co/pydantic-deepagents
Created
6 months ago
Last Updated
yesterday
Language
Python
License
MIT

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