Skip to main content

Codigest

Codigest is a standalone CLI tool designed to extract, structure, and track the context of your codebase for Large Language Models (LLMs).

Unlike simple copy-paste tools, Codigest employs a Context Anchor system (Shadow Git) to track changes locally without polluting your main version control history. It also features Semantic Analysis to detect structural changes in your code.

Note: You can use the short alias cdg instead of codigest for faster typing.

Quickstart

uv tool install codigest

cdg scan                  # whole project as LLM-ready XML (copied to clipboard)
cdg init && cdg diff      # set an anchor, later get only what changed
cdg cap -- pytest -q      # run a command and keep its output
cdg term -f               # hand the last failed command + output to your LLM
claude mcp add codigest -- cdg mcp   # let AI agents call all of the above

Core Philosophy

  • Read-Only & Safe: Codigest never modifies your source code. It only reads, analyzes, and formats context.
  • Context-Aware: Instead of dumping raw text, it structures code into XML snapshots designed for LLM comprehension.
  • Session-Based Tracking: It maintains an internal anchor to track "work-in-progress" changes independently of your Git commits.
  • Environment Isolated: Runs in its own isolated Python 3.15 environment via uv, ensuring it never conflicts with your project's dependencies.

Installation

Codigest runs as a global tool. You don't need to add it to your project's requirements.txt. We strongly recommend using uv for the best experience.

Step 1: Install uv

If you don't have uv installed, use Winget (Windows) or curl (macOS/Linux).

# Windows (via Winget)
winget install --id astral-sh.uv

# macOS/Linux
curl -LsSf https://astral.sh/uv/install.sh | sh

Step 2: Install codigest

Install Codigest globally. uv will automatically manage the required Python 3.15 environment for you.

uv tool install codigest

Step 3: Update Path (Important!)

To run codigest (or cdg) from any terminal, ensure your tools directory is in your PATH.

uv tool update-shell

> Note: Restart your terminal (or VS Code) after this step to apply changes.


Workflow & Commands

Once installed, use the cdg command anywhere.

1. Initialization

Sets up the .codigest directory and captures the initial baseline anchor.

cdg init

2. Full Context Snapshot (scan)

Scans the codebase and generates a structured XML snapshot. Includes a Pre-flight Check to prevent accidental token overflow.

  • Output: .codigest/snapshot.txt (or stdout with -s)
  • Features:
  • Smart Confirmation: Automatically skips confirmation for small contexts, but warns you for large ones (>30k tokens).
  • Dependency Resolution (-r): Automatically finds and includes local files imported by your target files.
  • Scope Control: You can specify folders or files to scan.
  • Terminal Output (-s / --stdout): Output directly to stdout instead of saving to file.
# Basic scan (Interactive confirmation if large)
cdg scan

# Scan specific folder with dependency resolution (Smart Context)
cdg scan src/main.py -r

# Force execution without confirmation (Good for CI/CD)
cdg scan -y --message "Automated snapshot"

# Output directly to stdout
cdg scan -s

3. Incremental Changes (diff)

Tracks text-based changes between the last scan and the current working tree.

  • Output: .codigest/changes.diff (or stdout with -s)
  • Use Case: "I modified 3 files. Here is exactly what changed since the last snapshot."
  • Note: Checks against the internal Shadow Git, enabling tracking without committing to the real Git.
cdg diff

# Output directly to stdout
cdg diff -s

4. Semantic Analysis (semdiff)

Analyzes structural changes (AST-based) rather than line-by-line text differences.

  • Output: .codigest/semdiff.txt (or stdout with -s)
  • Use Case: "I refactored the API. Show me added/removed functions or signature changes."
  • Benefit: Reduces token usage by ignoring formatting/comment changes.
cdg semdiff

# Output directly to stdout
cdg semdiff -s

5. Project Tree (tree)

Visualizes the project structure. Respects .gitignore.

  • Style: Professional, cleaner output without emojis for better readability.
  • Use Case: Quickly verifying which files are being tracked.
cdg tree

6. Architecture Digest (digest)

Generates a high-level outline of the project structure (Classes, Functions, Methods only).

  • Output: .codigest/digest.txt (or stdout with -s)
  • Use Case: "Don't read the implementation details. Just understand the class hierarchy."
cdg digest

# Output directly to stdout
cdg digest -s

7. Environment Status (status)

Displays the health of .codigest, anchor snapshot baseline, pending working tree changes, and generated artifacts.

  • Use Case: "Check what files have changed since my last snapshot and inspect the state of generated context artifacts."
cdg status

8. Environment Cleanup (clean)

Removes the .codigest/ environment and resets all context anchors and artifacts.

  • Use Case: "Clean up context files and resets Codigest tracking."
# Interactive confirmation
cdg clean

# Force clean without prompt
cdg clean -y

9. Terminal Capture & Recall (cap, term)

Runs a command transparently (output still streams live) and records its command line, combined stdout/stderr, exit code and cwd in a machine-global store. term then recalls recent entries as a <terminal_history> block for your LLM. Works in any directory, no cdg init needed.

  • Use Case: "This test failed. Here's exactly what I ran and what it printed."
  • Safety: Known secret shapes (API keys, tokens, password=...) are redacted before anything touches disk. Output of credential commands (env, printenv, gh auth token, ...) is never stored.
  • Fallback: Commands not run through cap are read from the native shell history (PowerShell, bash, zsh, fish), without output.

Automatic capture (PowerShell): cdg term install hooks your PowerShell profile so every command is captured without the cap prefix. Commands run in your current session (cd, variables and functions behave normally). Editors, pagers, REPLs and ssh are skipped automatically.

  • Skip one command: start the line with a space.
  • Skip more programs: $env:CODIGEST_CAP_SKIP = '^\s*(myrepl|mytui)\b'
  • Disable for a session: $env:CODIGEST_NOCAP = 1. Remove: cdg term uninstall.
  • Trade-off: captured programs write to a pipe, not a TTY, so some lose colors or progress bars.
cdg term install    # PowerShell: capture everything automatically

# Run and capture (prefix with -- so flags reach the command)
cdg cap -- pytest -q
cdg cap "npm run build | tail -20"

# Recall
cdg term            # last command
cdg term -n 3       # last 3 commands
cdg term -i 2       # only the command from 2 runs ago
cdg term -f         # last failed command

cdg term path       # where captures are stored (override with CODIGEST_HOME)
cdg term clear      # delete all captures

10. For AI Agents (mcp)

cdg mcp serves Codigest as an MCP server over stdio, so coding agents can pull context themselves instead of asking you to paste it.

Tool Returns
terminal_history Recent commands with output and exit code (count, failed)
scan Project snapshot (targets, resolve, message)
diff / semdiff Text / structural changes since the anchor
digest Signatures and docstrings only
tree Directory tree
# Claude Code
claude mcp add --scope user codigest -- cdg mcp

Other clients (Cursor, VS Code, Claude Desktop): add a stdio server with command cdg and args ["mcp"].


Configuration

You can customize behavior in .codigest/config.toml.

[filter]
# Target extensions
extensions = [".py", ".ts", ".rs", ".md", ".json"]

# Exclude patterns (Gitignore syntax)
exclude_patterns = [
    "*.lock",
    "tests/data/",
    "legacy_code/"
]

[output]
format = "xml"

Architecture Details

Context Anchor (Shadow Git) Codigest maintains a hidden, lightweight Git repository inside .codigest/anchor/.shadow_git.

  • It is renamed to .shadow_git to prevent VS Code and other IDEs from confusing it with your project's actual repository.
  • When you run scan, the current state is committed to this anchor.
  • When you run diff, the tool compares your working directory against this anchor.

Safety Mechanisms

  • Pre-flight Check: Calculates estimated token count before processing to prevent context overflow errors.
  • Structure-Aware Dedent: Ensures XML tags are perfectly aligned (flush-left) to prevent indentation artifacts in LLM prompts.
  • XML Injection Protection: Automatically escapes content within XML tags.

License

MIT. See LICENSE.

Metadata

Release files for codigest 0.4.1

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for codigest 0.4.1
File Size Uploaded
codigest-0.4.1.tar.gz 49.0 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for codigest 0.4.1
File Interpreter ABI Platform
codigest-0.4.1-py3-none-any.whl Python 3 none any Details

Total release size: 107.5 kB

Release files / codigest-0.4.1.tar.gz

Download URL codigest-0.4.1.tar.gz
Size 49.0 kB
Tags Source
SHA-256 checksum
How to use checksums
ee68bf4aadfba7b5a343c61a0be9230824d3f9f32e99d229553da73d67a03057
BLAKE2b-256 checksum
How to use checksums
2e2c19b03ec0b35323d5c9a4c2e955a03dd45dfbdaac4529b1346ed6e89fbe14
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/7.0.0 CPython/3.13.14

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Oct 15, 2026.

Transparency log

Release files / codigest-0.4.1-py3-none-any.whl

Download URL codigest-0.4.1-py3-none-any.whl
Size 58.6 kB
Tags Python 3
SHA-256 checksum
How to use checksums
0046c1a36eb9a9c0bdf6fe5057e94e03d7e8592de41df5845dbed077c79cb3e2
BLAKE2b-256 checksum
How to use checksums
a519517c233940c758730319b0db0a4f12ad9d459160f7ae1c0d7d265e1d4f67
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/7.0.0 CPython/3.13.14

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Oct 15, 2026.

Transparency log

Release history Release notifications | RSS feed

0.5.0

2 release files

0.4.3

2 release files

0.4.2

2 release files

This release

0.4.1 This release

2 release files

0.4.0

2 release files

0.3.9

2 release files

0.3.8

2 release files

0.3.7

2 release files

0.3.6

2 release files

0.3.5

2 release files

0.3.3

2 release files

0.3.2

2 release files

0.3.1

2 release files

0.3.0

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page