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High-performance execution layer for AI agents — filesystem, multi-language code analysis, process management

Project description

Agentic Executor

The execution layer for AI agents that need real hands

Version Python License No deps


AI agents are powerful thinkers but poor actors. They call one tool, wait for a result, call another tool, wait again. Every step is a round-trip.

Agentic Executor gives the agent a Python interpreter and a set of high-performance commands. Instead of ten tool calls, it writes one script. Loops, conditionals, error handling — all in a single thought.

# One thought. Ten files. Zero round-trips.
python -m agentic_executor.cli --thought-stdin <<'EOF'
files = execute('search', {'pattern': '*.py'})
for f in files['data']['files']:
    result = execute('read', {'path': f, 'lines': 5})
    if result['success']:
        print(f"=== {f} ===")
        print('\n'.join(result['data']['lines']))
EOF

Install

pip install agentic-executor

No dependencies. Works immediately with Python's built-in ast for Python files.
For full multi-language support (20+ languages via tree-sitter):

pip install "agentic-executor[languages]"

Activate the /exec skill

After installing, deploy the /exec skill to your AI agent of choice:

exec-install                       # Claude Code  (default)
exec-install --agent cursor        # Cursor
exec-install --agent windsurf      # Windsurf
exec-install --agent kiro          # Kiro
exec-install --agent codex         # Codex
exec-install --agent copilot       # GitHub Copilot
exec-install --agent opencode      # OpenCode
exec-install --agent aider         # Aider
exec-install --agent claw          # OpenClaw
exec-install --agent hermes        # Hermes
exec-install --agent trae          # Trae
exec-install --agent droid         # Factory Droid
exec-install --agent all           # All at once

Check status at any time:

exec-install --list

How it works

Everything goes through one function: execute(command, args).

The agent writes Python code that calls execute(). That code runs locally, with full Python logic — loops, conditions, error handling, chaining results between steps.

# Standard return format — every command
{
    "success": bool,
    "data":    Any,       # command result
    "error":   str|None   # message if failed
}

Always check result['success'] before reading result['data'].


Commands

Filesystem

execute('read',    {'path': 'file.txt'})                                   # first 200 lines (default)
execute('read',    {'path': 'file.txt', 'limit': 0})                      # full file, no limit
execute('read',    {'path': 'file.txt', 'limit': 500})                    # custom limit
execute('read',    {'path': 'file.txt', 'lines': 20})                     # first N lines
execute('read',    {'path': 'file.txt', 'start': 10, 'end': 30})          # range
execute('write',   {'path': 'out.txt', 'content': 'hello'})
execute('write',   {'path': 'log.txt', 'content': 'x\n', 'mode': 'a'})  # append
execute('replace', {'path': 'f.py', 'line': 42, 'new': '    # fixed'})   # line mode
execute('replace', {'path': 'f.py', 'old': 'foo()', 'new': 'bar()'})     # text mode
execute('copy',    {'src': 'a.txt', 'dst': 'b.txt'})
execute('move',    {'src': 'old.txt', 'dst': 'new.txt'})
execute('delete',  {'path': 'file.txt'})
execute('mkdir',   {'path': 'new/dir'})
execute('ls',      {'path': '.'})

Search

execute('search', {'pattern': '*.py', 'path': '.', 'recursive': True})
# → {"files": ["src/main.py", ...]}

execute('grep', {'pattern': 'TODO:', 'file_pattern': '*.py', 'path': '.'})
# → {"matches": [{"file": str, "line": int, "text": str}, ...]}

execute('info', {'path': 'file.txt'})
# → {"exists": bool, "type": "file"|"dir", "size": int, "modified": float}

Codebase intelligence

# Scan — supports Python, JS, TS, Go, Rust, Java, C, C++, Ruby, C#, Kotlin, Scala, PHP, Swift, Lua...
execute('scan_codebase', {'path': '.'})
# Writes cache to .agentic_executor/metadata.json

execute('get_metadata', {'type': 'summary'})
# → total files, functions, classes, imports

execute('get_metadata', {'type': 'structure'})
# → per-file: functions (name, line), classes, imports

execute('get_metadata', {'type': 'imports'})
# → import graph: who imports whom (bidirectional)

execute('get_metadata', {'type': 'all', 'filter': {'file': 'src/main.py'}})
# → single-file detail

Process

execute('run', {'cmd': 'pytest tests/', 'timeout': 60})
# → {"stdout": str, "stderr": str, "returncode": int}

Usage patterns

Batch operations

python -m agentic_executor.cli --thought-stdin <<'EOF'
files = execute('search', {'pattern': 'test_*.py'})

for f in files['data']['files']:
    result = execute('read', {'path': f, 'lines': 3})
    if result['success']:
        print(f"--- {f} ---")
        for line in result['data']['lines']:
            print(line)
EOF

Metadata-driven analysis

python -m agentic_executor.cli --thought-stdin <<'EOF'
execute('scan_codebase', {'path': '.'})
meta = execute('get_metadata', {'type': 'structure'})

# Find the most complex files
by_size = sorted(
    ((path, len(data['functions'])) for path, data in meta['data']['files'].items()),
    key=lambda x: x[1], reverse=True
)
for path, count in by_size[:5]:
    print(f"{count:3}  functions  {path}")
EOF

Conditional logic + cache

python -m agentic_executor.cli --thought-stdin <<'EOF'
info = execute('info', {'path': '.agentic_executor/metadata.json'})

if not info['data']['exists']:
    execute('scan_codebase', {'path': '.'})

meta = execute('get_metadata', {'type': 'summary'})
s = meta['data']['summary']
print(f"Files: {s['total_files']}  Functions: {s['total_functions']}  Classes: {s['total_classes']}")
EOF

Orchestrate external tools

python -m agentic_executor.cli --thought-stdin <<'EOF'
# Run any CLI tool and process its output with Python
result = execute('run', {'cmd': 'git log --oneline -10'})
if result['success']:
    commits = result['data']['stdout'].strip().split('\n')
    print(f"Last {len(commits)} commits:")
    for c in commits:
        print(f"  {c}")
EOF

Error handling

result = execute('read', {'path': 'file.txt'})

if result['success']:
    print(result['data']['content'])
else:
    print(f"Error: {result['error']}")
    # fallback logic

Multi-language support

Without tree-sitter (default): Python files via ast, other languages via regex patterns.
With pip install "agentic-executor[languages]": accurate parsing for 20+ languages.

Language Extension Parser
Python .py tree-sitter / ast
JavaScript .js .jsx .mjs tree-sitter / regex
TypeScript .ts .tsx tree-sitter / regex
Go .go tree-sitter / regex
Rust .rs tree-sitter / regex
Java .java tree-sitter / regex
C / C++ .c .h .cpp .hpp tree-sitter / regex
Ruby .rb tree-sitter / regex
C# .cs tree-sitter / regex
Kotlin .kt tree-sitter / regex
Scala .scala tree-sitter / regex
PHP .php tree-sitter / regex
Swift .swift tree-sitter / regex
Lua .lua tree-sitter / regex
Elixir, Bash, R, Dart ... regex

To install tree-sitter parsers separately:

exec-install --languages        # 9 essential languages
exec-install --full             # all 16

CLI reference

# Execute a thought inline
python -m agentic_executor.cli --thought "result = execute('ls', {'path': '.'}); print(result['data'])"

# Execute from stdin (recommended for multi-line code)
python -m agentic_executor.cli --thought-stdin <<'EOF'
# your Python code
EOF

# JSON output (for subprocess use)
python -m agentic_executor.cli --thought "..." --json-output

# Show available commands
python -m agentic_executor.cli --help-commands

Use --thought-stdin with heredoc for any script longer than one line or containing quotes. It avoids all shell escaping issues.


Tips

Raw strings for file content with escape sequences:

# Wrong — double escaping needed
content = 'def f():\n    print("hello")'

# Right — raw string, no escaping
content = r'''
def f():
    print("hello")
'''
execute('write', {'path': 'f.py', 'content': content})

Reading large files — use the truncation notice:

result = execute('read', {'path': 'big.py'})   # returns max 200 lines by default
data = result['data']

if data.get('truncated'):
    print(data['truncation_notice'])
    # → [...output truncated at 200 lines — 1225 more lines not shown.
    #    Use execute('read', {'path': 'big.py', 'start': 201, 'end': 1425}) to continue.]

# Read all at once when needed:
result = execute('read', {'path': 'big.py', 'limit': 0})

Scan before querying metadata:

execute('scan_codebase', {'path': '.'})   # always first
meta = execute('get_metadata', {'type': 'summary'})

Cache location: .agentic_executor/metadata.json — add to .gitignore.


Project structure

agentic_executor/
├── __init__.py          public API
├── cli.py               --thought / --thought-stdin interface
├── install.py           exec-install command
├── skills/
│   └── exec/
│       └── skill.md     /exec skill for Claude Code and others
└── code_parts/
    ├── executor.py      core execute() function
    └── commands.py      14 commands + multi-language scanner

pyproject.toml           pip packaging

When to use it

Use Agentic Executor when the task needs more than two steps or a loop.
For single reads or writes, use your agent's native tools directly — they're simpler.


Part of the Logeion projects

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